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Journal articles on the topic "159. 953 – 057. 876 (043.2)"
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Marincowitz, Carl, Omar Bouamra, Tim Coates, et al. "1427 The effect of the COVID-19 pandemic on major trauma presentations and patient outcomes in English hospitals." Emergency Medicine Journal 39, no. 12 (2022): A960.2—A964. http://dx.doi.org/10.1136/emermed-2022-rcem2.2.
Full textAbstract:
Aims, Objectives and BackgroundThere is evidence that COVID-19 ‘lockdowns’ may have contributed to increased non-accidental injury, domestic violence and self-harm related to deteriorating mental health. Internationally, there is also evidence that the diversion of health care resources may led to worse outcomes for patients presenting with major trauma. There has been no previous national evaluation of ‘lockdown’ measures impact on the characteristics, treatment pathways and outcomes of trauma patients in EnglandWe aimed to assess the impact of successive lockdowns on the volume, demographics, injury mechanism, severity, treatment and outcomes of major trauma in England.Method and DesignDemographic characteristics and clinical pathways of TARN eligible patients in the first lockdown (24th March to 3rd July 2020 inclusive) and second lock down (1st November 2020 to 16th May 2021 inclusive) were compared to equivalent pre-COVID-19 periods in 2018–2019.A segmented regression model predicting the weekly risk adjusted survival was estimated and a discontinuity in the gradient (trend) or intercept (level) of the fitted model was tested for at the weekly time point of implementation of each lockdown.Abstract 1427 Figure 1Strobe diagram for inclusion of study populationAbstract 1427 Figure 2Interrupted time series analysis assessing the impact of COVID restrictions on likelihood of survival (red horizontal lines indicate introduction and relaxation of ‘lockdown’ measures)Abstract 1427 Table 1Comparison of demographics ‘lockdown’ and pre-COVID periodsPeriodPeriod24Mar19 – 03Jul19 (comparator)24Mar20 – 03Jul20 (lockdown 1)Absolute change [percentage point change (95%CI)] p-value01Nov18 – 16May19 (comparator)01Nov20 – 16May21 (lockdown 1)Absolute change [percentage point change (95%CI)] p-valueTotal2224317510-4733 (-21%)p<0.0001‡41016382622754 (–6.7%)p<0.0001‡Age (years), Median (IQR)67.6 (46.5–83.1)70.9 (50.3–84.2)3.3 (2.4 to 4.2)p<0.000169.1 (48.7–83.6)73.1 (53.3–85.1)4 (3.5 to 4.2)<0.0001Age bands, n(%)Age< 1138 (0.6%)130 (0.7%)-8 [0.1(-0.04 to 0.030)] p=0.14281 (0.7%)234 (0.6%)-47 [0.1 (-0.2 to 0.04)]p=0.1979Age <16942 (4.2%)674 (3.8%)-268 [-0.4 (-0.8 to 0]p=0.05311444 (3.5%)1218 (3.2%)-226 [-0.3(-0.6 to – 0.1)p=0.0084Age 16 – 649561 (43%)6974 (39.8%)-2587 [-3.2(-4.1 to -2.2)P<0.000117173 (41.9%)13980 (36.5%)-3193 [-5.3(-6 to -5)]p<0.0001Age 65 and over11740 (52.8%)9862 (56.3%)-1878 [3.5 (2.5 to 4.5)]p<0.000122399 (54.6%)23064 (60.3%)665 [5.7(5 to 6.3)]P<0.0001Age 85 and over4610 (20.7%)4047 (23.1%)-563 [2.4(1.6 to 3.2)]p<0.00018903 (21.7%)9731 (25.4%)828 [3.7 (3.1 to 4.3)]p<0.0001Male, n(%)12316 (55.4%)9512 (54.3%)-2804 [-1 (-2 to -0.6)]p=0.037322146 (54%)19769 (51.7%)-2377 [-2.3 (-3 to -1.6)]<0.0001CCI*, n(%)CCI 09359 (42.1%)6220 (35.5%)-3139 [ -6.5 (-7.5 to -5.6)] p<0.000116665 (40.6%)12806 (33.5%)-3859 [-7.1(-7.8 to -6.5)]p<0.0001CCI 1 – 58538 (38.4%)6896 (39.4%)-1642 [1 (0.3 to 2)]p=0.042615899 (38.8%)15667 (40.9%)-232 [2.2 (1.5 to 2.9)]p<0.0001CCI 6 – 103032 (13.6%)3061 (17.5%)29 [3.8 (3.2 to 4.6)]p<0.00015987 (14.6%)6863 (17.9%)876 [3.3(2.8 to 3.8)]p<0.0001CCI > 10927 (4.2%)1024 (5.8%)97 [1.7(1.2 to 2.1)]p<0.00011648 (4%)2410 (6.3%)762 [2.3(2 to 2.6)]p<0.0001Not recorded387 (1.7%)309 (1.8%)-88 [0.2 (-0.2 to 0.3)]p=0.8513817 (2%)516 (1.3%)-301 [-0.6(-0.8 to -0.5)]p<0.0001MOI**: RTC, n(%)Car occupant1247 (30.7%)551 (20.4%)-696 [-10.4(-12.4 to -8.2)]p<0.00012485 (35.2%)1551 (31.3%)-934 [-3.9(-5.6 to -2.2)]p<0.0001Pedestrian661 (16.3%)288 (10.6%)-373 [-5.6 (-7.2 to -4)]p<0.00011629 (23.1%)962 (19.4%)-667 [-3.7(-5.1 to -2.2)]p<0.0001Motorcycles1196 (29.4%)711 (26.3%)-485 [-3.2(-5.3 to -1)]p<0.00011524 (21.6%)976 (19.7%)-548[ -1.9(-3.3 to -0.4)]p<0.0001Cyclist912 (22.4%)1139 (42.1%)227 [19.6(17.4 to 21.9)]p<0.00011315 (18.6%)1396 (28.2%)81 [9.5(8 to 11.1)]p<0.0001Other11 (0.3%)<9 ()-10 [ -0.2(-0.4 to -0.06)p=0.025131 (0.4%)10 (0.2%)-21 [-0.23(-0.4 to -0.04)]p=0.0281MOI: Intentional, n(%)Intentional assault130 (0.6%)88 (0.5%)-42 [-0.08 (-0.2 to 0.06)]p=0.2724227 (0.6%)175 (0.5%)-52 [-0.1(-0.2 to 0.002)]P=0.0570Self harm276 (1.2%)284 (1.6%)8 [0.4 (0.1 to 0.6)]p=0.0014525 (1.3%)562 (1.5%)37 [0.2 (0.02 to 0.3)]p=0.0223NAI63 (0.3%)27 (0.2%)-36 [-0.1(-0.2 to -0.03)]p=0.007297 (0.2%)90 (0.2%)-7 [-0.001(-0.07 to 0.07)]p=0.9701Shooting34 (0.2%)40 (0.2%)6 [0.08(-0.01 to 0.2)]p=0.082680 (0.2%)56 (0.1%)-24 [ -0.05(-0.1 to 0.001)]p=0.0979Stabbing450 (2%)312 (1.8%)-138 [-0.2(-0.5 to 0.03)]p=0.0816791 (1.9%)589 (1.5%)-202 [-0.4 (-0.6 to -0.2)]p<0.0001Blows1174 (5.3%)647 (3.7%)-527 [-1.6(-1.9 to -1.2)]p<0.00012059 (5%)1299 (3.4%)-760 [-1.6(-1.9 to -1.3)]p<0.0001Unintentional, n(%)Falls>2m2055 (9.2%)1757 (10%)-298 [0.8(0.2 to 1.4)]P=0.00753740 (9,1%)3528 (9.2%)-212 [0.1(-0.3 to 0.5)]p=0.6181Falls<2m13384 (60.2%)11314 (64.6%)-2070 [4.4 (3.5 to 5.4)]p<0.000125505 (62.2%)26203 (65.8%)698 [6.3 (5.6 to 6.9)]p<0.0001Sport449 (2%)320 (1.8%)-129 [-0.2 (-0.5 to 0.01]p=0.1697615 (1.5%)489 (1.3%)-126 [-0.2 (-0.4 to -0.006)]p=0.0079GCS bands , n(%)Mild19609 (88.2%)15449 (88.2%)4160 [0.1 (-0.6 to 0.7)]p=0.826435831 (87.4%)34051 (89%)-1780 [1.6 (1.2 to 2.1)]p<0.0001Moderate689 (3.1%)625 (3.6%)-64 [0.5(0.1 to 0.8)]p=0.00901333 (3.2%)1127 (2.9%)-206 [-0.3 (-0.5 to -0.06)]p=0.0135Severe955 (4.3%)765 (4.4%)-190 [0.1 (-0.3 to 0.5)]p=0.71361886 (4.6%)1464 (3.8%)-422 [-0.8(-1 to -0.5)]p<0.0001Not recorded990 (4.5%)671 (3.8%)-319 [ -0.6(-1 to -0.2)]p=0.00221966 (4.8%)1620 (4.2%)-346 [-0.6(-0.8 to -0.3)]p=0.0002ISS***, median (IQR)9 (9–18)9 (9–18)09 (9–18)9 (9–17)0ISS bands, n(%)ISS 1 – 84545 (20.4%)3062 (17.5%)-1483 [-3 (-4 to -2)]p=<0.00018266 (20.2%)7838 (20.5%)-428 [0.3(-0.2 to 0.9)]p=0.2457ISS 9 – 159290 (41.8%)7728 (44.1%)-1562 [2.4(1.4 to 3.3)]p<0.000117207 (42%)16969 (44.3%)-233 [2.4(1.7 to 3.1)]p<0.0001ISS >158408 (37.8%)6720 (38.4%)-1688 [5.6(-0.4 to 1.5)]p=0.239115543 (37.9%)13455 (35.2%)-2088 [-2.7 (-3.4 to -2)]p<0.0001ISS >253995 (18%)3127 (17.9%)-868 [-0.1(-0.9 to 0.7 )]p=0.79217521 (18.3%)6201 (16.2%)-1320 [-2.1(-2.6 to -1.6)]p<0.0001Body regions, n(%)Head AIS 3+5911 (26.6%)4670 (26.7%)-1241 [0.1 (-0.8 to 1)]p=0.830111128 (27.1%)9629 (25.2%)-1499 [ -2(-2.6 to -1.3)]p<0.0001Face AIS 3+63 (0.3%)41 (0.2%)-22 [-0.05 (-0.1 to 0.05)]p=0.341699 (0.2%)69 (0.2%)-30 [-0.06 (-0.1 to 0)]p=0.0618Chest AIS 3+4787 (21.5%)3915 (22.4%)-872 [8.3 (0.2 to 1.6)]<0.04508515 (20.8%)8075 (21.1%)-440 [0.3 (-0.2 to 0.9)]p=0.2337Abdomen AIS 3+872 (3.9%)690 (3.9%)-182 [0.02 (-0.3 to 0.4)]p=0.91771465 (3.6%)1179 (3.1%)-286 [-0.5 (-0.7 to -0.2)]p=0.0001Spine AIS 3+1985 (8.9%)1561 (8.9%)-424 [-0.01(-0.6 to 0.5)]p=0.97443784 (9.2%)3459 (9%)-325 [-0.2(-0.6 to 0.2)]p=0.3654Pelvis AIS 3+758 (3.4%)600 (3.4%)-158 [0.02(-0.3 to 0.4)]p=0.91841501 (3.7%)1386 (3.6%)-115 [-0.04(-0.3 to 0.2)]p=0.7802Limb AIS 3+5707 (25.7%)4892 (27.9%)-815 [2.3 (1.4 to 3.2)]p<0.000110719 (26.1%)10122 (26.5%)-597 [0.3(-0.3 to 0.9)]p=0.3053Other AIS 3+217 (1%)199 (1.1%)-18 [0.2 (-0.04 to 0.3)]p=0.1176375 (0.9%)396 (1%)21 [0.1 (-0.01 to 0.2]p=0.0836Polytrauma1622 (7.3%)1350 (7.7%)-272 [0.4 (-0.1 to 0.9)]p=0.11602984 (7.3%)2429 (6.3%)-555 [-0.9(-1.2 to 0.6)]p<0.0001*CCI Charlson Comorbidity Index**MOI Mechanism of injury***ISS Injury Severity Score‡chi square test for uniform distributionAbstract 1427 Table 2Comparison care pathways ‘lockdown’ and pre-COVID periodsPeriodPeriod24Mar19 – 03Jul19 (comparator)24Mar20 – 03Jul20 (lockdown 1)Absolute Change01Nov18 – 16May19 (comparator)01Nov20 – 16May21 (lockdown 2)Absolute Change1stHospital MTC9908 (44.5%)7376 (42.1%)-2532 [-2.4 (-3.4 to -1.4)]p<0.000118099 (44.1%)15928 (41.6%)-2171 [-2.5 (-3.2 to -1.8)]p<0.0001Treated at MTC11176 (50.2%)8256 (47.2%)-2920 [-3 (-4 to -2)]p<0.000120395 (49.7%)17852 (46.7%)-2543[-3 (-4 to -2.4)]p<0.0001Consultant ED8140 (36.6%)5562 (31.8%)-2578 [-4.8(-5.8 to -3.9)]p<0.000114779 (36%)12577 (32.9%)-2202 [-3.2 (-3.8 to -2.5)]p<0.0001CT within 1 hr5062 (31.9%)3992 (30.9%)-1070 [-0.9(-2 to 0.1)]p=0.09449203 (31.6%)7776 (27.1%)-1427 [-4(-5 to -3.7)]p<0.0001Whole body CT3348 (15.1%)3210 (18.3%)-138 [3 (2 to 4)]p<0.00016040 (14.7%)6417 (16.8%)377 [2 (1.5 to 2.5)]p<0.0001ICU stay3092 (13.9%)2208 (12.6%)-884 [-1.3(-1.9 to -0.6) ]p=0.00025591 (13.6%)3850 (10.1%)-1741 [-3.6(-4 to -3)]p<0.0001Mortality*1417 (7.1%)1316 (8.3%)-101 [1.2 (0.6 to 1.7)]p<0.00012916 (7.9%)2858 (8.1%)-58 [0.2 (-0.1 to 0.6)] p=0.2040Discharge destination, n(%)Home (own)13800 (62%)10484 (59.9%)-3316 [-2(-3.1 to -1.2)]p<0.000124961 (60.9%)23368 (61.1%)-1593 [-0.7 (-1.4 to -0.05)]p=0.0340Home (relative/carer)473 (2.1%)372 (2.1%)-101 [0 (-0.3 to 0.3)]p=0.9890974 (2.4%)852 (2.2%)-122 [-0.1(-0.4 to 0.06)]p=0.1653Mortuary*1501 (6.7%)1323 (7.6%)-178 [0.8(0.3 to 1.3)]p=0.00193086 (7.5%)2977 (7.8%)-109 [0.1 (-0.3 to 0.5)]p=0.5113No fixed abode75 (0.3%)47 (0.3%)-28 (-37.3%)107 (0.3%)87 (0.2%)-20 (-18.7%)Not Known87 (0.4%)39 (0.2%)-48 (-55.2%)101 (0.2%)95 (0.2%)-6 (-5.9%)Nursing Home1190 (5.3%)1063 (6.1%)-127 [0.7(0.3 to 1.2)]p=0.00202448 (6%)2231 (5.8%)-217 [-0.2(-0.6 to 0.1)]p=0.1620Other Acute hospital2425 (10.9%)1736 (9.9%)-689 [-0.1(-1.6 to -0.4)]p=0.00144346 (10.6%)3313 (8.7%)-1033 [-0.1(-0.5 to 0.2)]p=0.4115Other institution526 (2.4%)516 (2.9%)-10 [0.6 (0.3 to 0.9)]p=0.0003980 (2.4%)870 (2.3%)-110 [-0.1 (-0.3 to 0.1)]p=0.2817Rehabilitation2077 (9.3%)1871 (10.7%)-206 [1.3(0.7 to 1.9)]p<0.00013851 (9.4%)4274 (11.2%)423 [ 1.7(1.3 to 2.2)]p<0.0001Social care63 (0.3%)50 (0.3%)-13 [0 (-0.1 to 0.1)]p=0.9657121 (0.3%)103 (0.3%)-18 [-0.2(-0.1 to 0.5)]p=0.4939*These totals do not correspond as mortality includes deaths in the community and is censored at 30 daysResults and ConclusionThe first ‘lockdown’ had a larger associated reduction in total trauma volume (-21%) compared to the pre-COVID period than the second ‘lockdown’ (-6.7%). Trauma volume increased for those 65 and over (3%) and 85 and over (9.3%) during the second ‘lockdown’.There was a reduction in likelihood of survival (-1.71; 95% CI:-2.76 to -0.66) associated with the immediate introduction of the first ‘lockdown’. However, this was followed by a trend of improving survival (0.25; 95% CI: 0.14 to 0.35) and likelihood of survival returned to pre-pandemic levels by the end of the first ‘lockdown’ period.Future research is needed understand the initial reduction in likelihood of survival after major trauma observed with the implementation of the first ‘lockdown’ to prevent this occurring if measures re-introduced.
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Sawattep, Jeeranut, Thad A. Howard, Noppawan P. Morales, et al. "Single Nucleotide Polymorphism (SNP) Discovery within the UGT1A Gene Complex: Allelic Frequencies and Ethnic Differences." Blood 104, no. 11 (2004): 3780. http://dx.doi.org/10.1182/blood.v104.11.3780.3780.
Full textAbstract:
Abstract The UDP-glycosyltransferase (UGT1A) gene complex plays an important role in the hepatic metabolism of many chemicals, toxins, and drugs including bilirubin and acetaminophen. In this large gene complex that spans over 200kb, there are at least 13 different coding regions that can serve as exon 1, followed by a common sequence that contains exons 2–5. These variable exon 1 sequences confer different chemical specificities for binding compounds, while exons 2–5 provide glycosyltransferase function (glucuronidation) that enhances water solubility and excretion. Mutations and polymorphisms within the UGT1A complex may help explain the phenotypic variability that is observed in drug metabolism for patients with hematological diseases. To date, several important polymorphisms have been identified in the coding regions of the UGT1A1 and UGT1A6 exon 1 sequences, but formal single nucleotide polymorphism (SNP) discovery has not been reported. Using genomic DNA obtained from a cohort of Thai patients with beta-thalassemia/HbE (n=37) and African-American patients with sickle cell anemia (n=12), flanking and coding sequences for UGT1A1 exon 1 (1.5kb), UGT1A6 exon 1 (1.5kb), and UGT1A common exons 2–5 (2.5kb) were fully sequenced in both directions. Polymorphisms that occurred more than once were compared to wildtype sequences obtained from NCBI, Accession Number AF297093. Single Nucleotide Polymorphisms in the UGT1A gene complex SNP NCBI nucleotide Location African-American Thai * indicates a SNP previously identified in NCBI g/c 109183 5′ 1A6 Exon 1 .875/.125 .676/.324 c/g 109301 5′ 1A6 Exon 1 .833/.167 1.000/.000 g/t 109628 1A6 Exon 1 .458/.542 .662/.338 c/t 109713 1A6 Exon 1 1.000/.000 .905/.095 a/g * 109924 1A6 Exon 1 .542/.458 .689/.311 a/g * 110150 1A6 Exon 1 .708/.292 .689/.311 a/c * 110161 1A6 Exon 1 .625/.375 .662/.338 t/g 110236 1A6 Exon 1 .750/.250 .973/.027 c/t 174679 5′ 1A1 Exon 1 .500/.500 .770/.230 g/c 174979 5′ 1A1 Exon 1 1.000/.000 .946/.054 g/a * 175253 1A1 Exon 1 1.000/.000 .932/.068 a/g 182226 Intron 2 .955/.045 .689/.311 t/c 182521 Intron 2 .850/.150 .905/.095 c/t 187524 3′ Exon 5 .417/.583 .865/.135 c/g * 187652 3′ Exon 5 .625/.375 .851/.149 c/g * 187753 3′ Exon 5 .587/.417 .838/.162 In addition to the well-described UGT1A1 (TA)n promoter polymorphism, a total of 16 SNPs were identified in these regions, including 10 that have not been previously reported. Four novel promoter SNPs were identified, along with three new UGT1A6 exon 1 coding SNPs and three non-coding SNPs within the common exon 2–5 region. The alellic frequencies for these SNPs can only be estimated from this small sample size, but indicate substantial differences between Thai and African-American patients. A larger sample size will be used to determine a more accurate allelic frequency for each SNP, and to identify haplotype associations. These novel SNPs within the UGT1A gene complex may have important effects on drug metabolism and may explain some of the phenotypic variability observed in these patient populations.
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Dörner, T., Y. Tanaka, M. Mosca, et al. "POS0714 POOLED SAFETY ANALYSIS OF BARICITINIB IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS: RESULTS FROM THREE RANDOMISED, DOUBLE-BLIND, PLACEBO-CONTROLLED, CLINICAL TRIALS." Annals of the Rheumatic Diseases 81, Suppl 1 (2022): 639.1–639. http://dx.doi.org/10.1136/annrheumdis-2022-eular.2375.
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BackgroundBaricitinib (BARI), an oral selective inhibitor of Janus kinase 1 and 2 approved for the treatment of rheumatoid arthritis and atopic dermatitis, has been evaluated in clinical studies in patients with systemic lupus erythematosus (SLE).ObjectivesTo assess the safety profile of BARI in patients with SLE.MethodsPatients with SLE receiving stable background therapy were randomised 1:1:1 to BARI 2-mg, 4-mg, or placebo (PBO) once daily in one 24-week, phase 2 (NCT02708095) and two 52-week, phase 3, PBO controlled studies (NCT03616912 and NCT03616964).ResultsA total of 1,849 patients were included in this pooled analysis, representing 1,463.5 patient years of exposure (PYE). The incidence rates per 100 PYR at risk (IR/100 PYR) for serious adverse events (SAEs) were 9.5, 14.7, and 14.1 respectively for PBO, BARI 2-mg, and BARI 4-mg. There were no clinically meaningful differences between treatment groups for discontinuations due to AEs or death (Table 1).Table 1.Overview of safety measures of baricitinib in patients with SLESafety measurePBOBARI 2-mgBARI 4-mgPooled-BARIN=614N=621N=614N=1235PYE=488.1PYE=494.0PYE=481.4PYE=975.4n(%)n(%)n(%)n(%)PYRPYRPYRPYR[IR; 95%CI][IR; 95%CI][IR; 95%CI][IR; 95%CI]SAEs45 (7.3)70 (11.3)*65 (10.6)*135 (10.9)*473.2476.6461.9938.5[9.5; 6.9, 12.7][14.7; 11.5, 18.6][14.1; 10.9, 17.9][14.4; 12.1, 17.0]Discontinuation of study drug due to AE48 (7.8)58 (9.3)57 (9.3)115 (9.3)485.3492.3480.6973.0[9.9; 7.3, 13.1][11.8; 8.9, 15.2][11.9; 9.0, 15.4][11.8; 9.8, 14.2]Death4 (0.7)1 (0.2)4 (0.7)5 (0.4)488.2494.0481.5975.5[0.8; 0.2, 2.1][0.2; 0.0, 1.1][0.8; 0.2, 2.1][0.5; 0.2, 1.2]Serious infections12 (2.0)22 (3.5)28 (4.6)*50 (4.0)*484.3487.2472.5959.7[2.5; 1.3, 4.3][4.5; 2.8, 6.8][5.9; 3.9, 8.6][5.2; 3.9, 6.9]Herpes Zoster18 (2.9)17 (2.7)29 (4.7)46 (3.7)481.1486.5468.6955.1[3.7; 2.2, 5.9][3.5; 2.0, 5.6][6.2; 4.1, 8.9][4.8; 3.5, 6.4]VTEs#6 (1.2)3 (0.6)1 (0.2)4 (0.4)444.0450.2438.1888.3[1.4; 0.5, 2.9][0.7; 0.1, 1.9][0.2; 0.0, 1.3][0.5; 0.1, 1.2]MACE#01 (0.2)3 (0.6)4 (0.4)443.9450.1438.1888.3[0.0; NA, 0.8][0.2; 0.0, 1.2][0.7; 0.1, 2.0][0.5; 0.1, 1.2]Malignancy excluding NMSC2 (0.3)3 (0.5)2 (0.3)5 (0.4)488.0494.1481.4975.5[0.4; 0.0, 1.5][0.6; 0.1, 1.8][0.4; 0.1, 1.5][0.5; 0.2, 1.2]NMSC2 (0.3)000*486.7494.0481.4975.4[0.4; 0.0, 1.5][0.0; NA, 0.7][0.0; NA, 0.8][0.0; NA, 0.4]Data are n (%) patients PYR [IR; 95% CI]. #Phase 2 study data not included. AE=adverse event; CI=confidence interval; MACE=major adverse cardiac event; NMSC=non-melanoma skin cancers; VTE=venous thrombotic event (includes deep vein thrombosis and pulmonary embolism); IR=incidence rate (100 times the number of patients reporting an adverse event divided by the event-specific exposure to treatment); N=number of patients in the analysis population; n=number of patients in the specified category; PYE=patient-year of exposure; PYR=patient years at risk; SAE=serious adverse event. *p≤0.05 vs placebo.The IR/100 PYR for serious infections were 2.5, 4.5, and 5.9 respectively for PBO, BARI 2-mg, and BARI 4-mg. The risk of Herpes Zoster was higher in BARI 4-mg (4.7%) vs PBO (2.9%) (Table 1).The IR/100 PYR for positively adjudicated venous thrombotic events (VTEs) were 1.4, 0.7, and 0.2 respectively for PBO, BARI 2-mg, and BARI 4-mg. The IR/100 PYR for positively adjudicated major adverse cardiac event (MACE) was numerically higher in BARI 2-mg (0.2) and BARI 4-mg (0.7) vs PBO (0.0), however the pooled-BARI IR/PYR (0.5) was within the range of background disease (1). No increased risk for malignancies was observed.ConclusionThe safety profile of BARI in SLE patients was consistent with the known BARI safety profile. There was no increased risk of VTE in BARI treatment groups.References[1]Barbhaiya M, Feldman CH, et al. Arthritis Rheumatol. 2017;69(9):1823-31.Disclosure of InterestsThomas Dörner Speakers bureau: Eli Lilly and Company and Roche, Consultant of: AbbVie, Celgene, Eli Lilly and Company, Janssen, Novartis, Roche, Samsung and UCB, Grant/research support from: Chugai, Janssen, Novartis and Sanofi, Yoshiya Tanaka Speakers bureau: Gilead, Abbvie, Behringer-Ingelheim, Eli Lilly, Mitsubishi-Tanabe, Chugai, Amgen, YL Biologics, Eisai, Astellas, Bristol-Myers, Astra-Zeneca, Consultant of: Eli Lilly, Daiichi-Sankyo, Taisho, Ayumi, Sanofi, GSK, Abbvie, Grant/research support from: Asahi-Kasei, Abbvie, Chugai, Mitsubishi-Tanabe, Eisai, Takeda, Corrona, Daiichi-Sankyo, Kowa, Behringer-Ingelheim, Marta Mosca Speakers bureau: Eli Lilly, GSK, Astra Zeneca, Consultant of: Eli Lilly, GSK, Astra Zeneca, Ian N. Bruce Speakers bureau: GSK, Astra Zeneca, UCB, Consultant of: Eli Lilly, GSK, UCB, BMS, Merck Serono, Astra Zeneca, IL-TOO, Aurinia, Grant/research support from: GSK, Janssen, Mario Cardiel Speakers bureau: Eli Lilly, Pfizer, Abbvie, Consultant of: Eli Lilly, Pfizer, Grant/research support from: Pfizer, Gilead, Roche, Janssen, Eric F. Morand Speakers bureau: AstraZeneca, Eli Lilly, Novartis, Consultant of: Amgen, AstraZeneca, Asahi Kasei, Biogen, BristolMyersSquibb, Capella, Eli Lilly, EMD Serono, Genentech, GlaxoSmithKline, Janssen, Neovacs, Sanofi, Servier, UCB, Wolf, Grant/research support from: Janssen, AstraZeneca, BristolMyersSquibb, Eli Lilly, EMD Serono, GlaxoSmithKline, Michelle A Petri Consultant of: Eli Lilly, Grant/research support from: Eli Lilly, Maria Silk Shareholder of: Eli Lilly, Employee of: Eli Lilly, christina dickson Shareholder of: Eli Lilly, Employee of: Eli Lilly, Gabriella Meszaros Shareholder of: Eli Lilly, Employee of: Eli Lilly, Maher Issa Shareholder of: Eli Lilly, Employee of: Eli Lilly, Lu Zhang Shareholder of: Eli Lilly, Employee of: Eli Lilly, Daniel J. Wallace Consultant of: Amgen, Eli Lilly and Company, EMD Merck Serono and Pfizer
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Taylor, P. C., C. Charles-Schoeman, M. Alani, et al. "POS0660 CONCOMITANT USE OF STATINS IN FILGOTINIB-TREATED PATIENTS WITH RHEUMATOID ARTHRITIS." Annals of the Rheumatic Diseases 80, Suppl 1 (2021): 572–73. http://dx.doi.org/10.1136/annrheumdis-2021-eular.933.
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Background:The Janus kinase-1 preferential inhibitor filgotinib (FIL) improved rheumatoid arthritis (RA) signs and symptoms in phase (P)3 trials.1–3 RA elevates cardiovascular disease risk; statins are used to reduce risk.Objectives:To assess safety of statin and filgotinib coadministration across the clinical program.Methods:Patients (pts) meeting 2010 ACR/EULAR RA criteria in P2 DARWIN 1–2 (D1–2; NCT01888874, NCT01894516), P3 FINCH 1–3 (F1–3; NCT02889796, NCT02873936, NCT02886728), and long-term extensions DARWIN 3 and FINCH 4 (D3, F4; NCT02065700, NCT03025308) receiving FIL 100 mg (FIL100) QD, FIL 200 mg QD (FIL200), adalimumab (ADA), methotrexate (MTX), or placebo (PBO) were included. Events related to statin use were analysed as exposed by treatment received. N and % were provided.Week (W)12 PBO-controlled safety analysis included pts receiving FIL100, FIL200, or PBO for ≤12W (D1–2, F1–2); as-treated safety analysis included pts receiving long-term FIL100 QD (n=1647), FIL200 QD (n=2267), ADA (n=325), MTX (n=416), or PBO (n=781) (D1–3, F1–4); P3 as-randomised analysis included data up to W52 (F1–3) per assigned treatment.Results:In each arm, similar proportions of pts took statins at baseline (9.4%–11.9%); initiation during study was low (1.2%–6.8%). Through W12 in PBO-controlled analysis, mean creatine phosphokinase (CPK; Figure 1), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) levels were similar regardless of statin use and remained within normal levels across all arms.Mean baseline ALT and AST levels were 20–23 and 20–22 U/L, respectively; at W12, ALT and AST ranged from 22–24 and 20–25 U/L, respectively. Graded CPK, ALT, and AST elevations are in Table 1.Table 1.Graded laboratory abnormalities at week 12 by baseline statin use in PBO-controlled analysisConcomitantNoneFIL200(n=68)FIL100(n=95)PBO(n=93)FIL200 (n=709)FIL100(n=693)PBO(n=688)CPK increased*598281562549537G1 (≤2.5×ULN)10 (16.9)13 (15.9)6 (7.4)71 (12.6)47 (8.6)18 (3.4)G2 (>2.5 to 5×ULN)3 (5.1)006 (1.1)2 (0.4)3 (0.6)G3 (>5 to 10×ULN)0001 (0.2)03 (0.6)G4 (>10×ULN)0001 (0.2)2 (0.4)0AST increased**689492708692684G1 (≤3.0×ULN)9 (13.2)11 (11.7)7 (7.6)97 (13.7)79 (11.4)60 (8.8)G2 (>3.0 to 5.0×ULN)0003 (0.4)2 (0.3)3 (0.4)G3 (>5.0 to 20.0×ULN)01 (1.1)02 (0.3)00G4 (>20.0×ULN)000000ALT increased**689492708692684G1 (≤3.0×ULN)13 (19.1)14 (14.9)13 (14.1)98 (13.8)92 (13.3)72 (10.5)G2 (>3.0 to 5.0×ULN)02 (2.1)010 (1.4)5 (0.7)6 (0.9)G3 (>5.0 to 20.0×ULN)0001 (0.1)01 (0.1)G4 (>20.0×ULN)000000Data are n (%). Grading per Common Terminology Criteria for Adverse Events v4.03*FINCH 1–2**DARWIN 1–2, FINCH 1–2ALT, alanine aminotransferase; AST, aspartate aminotransferase; CPK, creatine phosphokinase; csDMARD, conventional synthetic disease-modifying antirheumatic drug; FIL200/100, filgotinib 200/100 mg + csDMARDs; Grade, G; PBO, placebo; ULN, upper limit of normal.In the long-term as-treated analysis, 1 (0.5%)/6 (3.2%)/0/0/0 treatment-emergent adverse events (AE) of myalgia occurred in pts on statins at baseline receiving FIL200/FIL100/ADA/MTX/PBO and in 12 (0.6%)/8 (0.5%)/3 (1.0%)/2 (0.5%)/1 (0.1%) pts not on statins. Muscle spasms occurred in 2 (0.9%)/3 (1.6%)/1 (3.2%)/0/1 (1.1%) pts on statins at baseline receiving FIL200/FIL100/ADA/MTX/PBO and 21 (1.0%)/8 (0.5%)/0/3 (0.8%)/1 (0.1%) pts not on statins at baseline. One patient not on statins receiving FIL200 reported rhabdomyolysis. For all treatment arms in P3 as-randomised analysis, mean LDL and HDL increased similarly from baseline (108–110 and 56–59 mg/dL, respectively) to W52 (119–130 and 59–71 mg/dL, respectively).Conclusion:No increases in statin-induced AEs such as muscle or liver toxicities occurred with statins and filgotinib coadministration; results are supported by a drug-drug interaction study.4 Mean LDL and HDL increased at W52 in all treatment arms.References:[1]Genovese et al. JAMA. 2019;322:315–25.[2]Westhovens et al. Ann Rheum Dis. 2021; online first.[3]Combe et al. Ann Rheum Dis. 2021; online first.[4]Anderson et al. EULAR 2021 abstract.Disclosure of Interests:Peter C. Taylor Consultant of: AbbVie, Biogen, Eli Lilly, Fresenius, Galapagos, Gilead, GlaxoSmithKline, Janssen, Nordic Pharma, Pfizer, Roche, BMS, Sanofi, Celltrion, and UCB, Grant/research support from: Celgene, Eli Lilly, Galapagos, and Gilead, Christina Charles-Schoeman Consultant of: Gilead, Pfizer, and Regeneron-Sanofi, Grant/research support from: AbbVie, Bristol-Myers Squibb and Pfizer Inc, Muhsen Alani Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Mona Trivedi Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Vanessa Castellano Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Iyabode Tiamiyu Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Deyuan Jiang Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Lei Ye Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Sander Strengholt Shareholder of: Galapagos BV, Employee of: Galapagos BV, Michael Nurmohamed Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, Roche, and Sanofi, Consultant of: AbbVie, Celgene, Celltrion, Eli Lilly, Janssen, and Sanofi, Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, MSD, Mundipharma, Novartis, Pfizer, Roche, and Sanofi, Gerd Rüdiger Burmester Speakers bureau: AbbVie, Eli Lilly, Pfizer, and Gilead Sciences, Inc., Consultant of: AbbVie, Eli Lilly, Pfizer, and Gilead Sciences, Inc.
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Bauman, Glenn, Mohammed Rashid, Deanna L. Langer, et al. "A prospective provincial registry of PSMA PET CT for recurrent prostate cancer (PREP): Results for 4135 men." Journal of Clinical Oncology 43, no. 5_suppl (2025): 35. https://doi.org/10.1200/jco.2025.43.5_suppl.35.
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35 Background: PREP was initiated in Ontario to provide access and characterize performance of PSMA PET CT among men with recurrent prostate cancer after primary definitive treatment (RP or RT). Methods: Between 03/18 and 09/22, 4135 men were accrued. Men were enrolled and imaged with 18F-DCFPyL at 1 of 6 participating sites within 1 of 6 clinical cohorts. Standardized reports delineated sites of recurrence and post PET management changes. Linkage to provincial databases allowed estimation of overall survival and utilization of salvage radiotherapy after PET. Results: Median follow-up was 1.8 years; key findings are in Table 1. Significant predictors of a positive PET scan on multi-variable analysis included: higher PSA at time of PET and clinical cohort (highest for cohort 4). Significant predictors of change in management were type of recurrence (highest for loco-regional) and higher PSA. Significant predictors of worse overall survival included clinical cohort (worst for cohort 4), extent and type of metastases (worst for mixed bone/lymph/visceral or extensive metastases). A change in management post PET was a significant predictor of improved survival. Conclusions: The PREP registry facilitated access to PSMA PET/CT with high rates of disease detection and impact on management. Significant factors associated with survival were extent and sites of disease detected and management change after PET. Clinical trial information: NCT03718260 . PREP registry: Key findings. Total (n=4135) Cohort 1 (n=255): BF within 3 months from RP and pN+ or PSA >0.1 Cohort 2 (n=1500): BF following RP Cohort 3 (n=1040): BF post RPand adjuvant or salvage RT Cohort 4 (n=263): BF while on salvage hormone therapy Cohort 5 (n=176): BF following Therapy for Oligo-metastases on prior PET Cohort 6 (n=901): BF following primary RT Median Age at scan (IQR) 71.0 (66.0–76.0) 66.0 (61.0–70.0) 70.0 (65.0–74.0) 72.0 (67.0–76.0) 74.0 (69.0–79.0) 73.0 (66.0–77.0) 75.0 (70.0–79.0) Median PSA (IQR) at scan (ng/mL) 1.3 (0.3–4.0) 0.7 (0.2–2.5) 0.3 (0.2–1.0) 1.1 (0.5–2.7) 3.5 (1.6–7.2) 2.4 (1.0–5.3) 4.4 (3.1–7.4) PET: Negative Findings 1216 (29.4) 84 - 88 (32.9 - 34.5)* 749 (49.9) 258 (24.8) 19 (7.2) 18 - 22 (10.2 - 12.5)* 84 (9.3) PET: Locoregional Recurrence 1377 (33.3) 95 (37.3) 471 (31.4) 295 (28.4) 63 (24.0) 34 (19.3) 419 (46.5) PET: Oligo-Metastatic (≤5 metastases) 1021 (24.7) 45 (17.6) 224 (14.9) 354 (34.0) 111 (42.2) 70 (39.8) 217 (24.1) PET: Extensive Metastases 521 (12.6) 29 (11.4) 56 (3.7) 133 (12.8) 70 (26.6) 52 (29.5) 181 (20.1) Change in management post PET 2070 (50.1) 135 (52.9) 585 (39.0) 552 (53.1) 152 (57.8) 99 (56.3) 547 (60.7) Radiotherapy within 6 months 1729 (41.8) 165 (64.7) 866 (57.7) 346 (33.3) 88 (33.5) 49 (27.8) 215 (23.9) Died during follow-up period 138 (3.3) 1 - 5 (0.4 - 2.0)* 18 (1.2) 30 (2.9) 35 (13.3) 8 -12 (4.5 - 6.8)* 44 (4.9) BF: Biochemical Failure; RP: Radical Prostatectomy; RT: Radiotherapy; IQR: Interquartile Range. *Small cell size.
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Hanzis, Christina, Zachary Hunter, Robert Manning, et al. "Associated Malignancies Among Patients and Kin with Waldenstrom's Macroglobulinemia." Blood 116, no. 21 (2010): 4159. http://dx.doi.org/10.1182/blood.v116.21.4159.4159.
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Abstract Abstract 4159 Waldenstrom's macroglobulinemia (WM) is a B-cell malignancy characterized as an IgM secreting lymphoplasmacytic lymphoma. Familial predisposition is common in WM. Studies to date by us and others have revealed three identifiable clinical subtypes for WM predisposition: * Sporadic; proband has WM, but there is an absence of WM or other B-cell disorders in other family members; * Familial, Mixed B-cell Disorders Subtype; proband has WM, and various B-cell disorders are manifested by other family members. * Familial, WM Only Subtype; proband has WM, and only WM is present in other family members; While these studies suggest a separate genetic predisposition for WM, the correlation of additional cancer risk among all patients with WM and their kin, and well as those sub typed by familial WM predisposition may herald important information for common genetic risks to cancer. We therefore examined the incidence of additional malignancies in 923 consecutive WM patients seen at our Institution, and characterized the frequencies of additional malignancies based on familial subtype and against SEER data. In addition, we also characterized the incidence of solid cancers in kin of WM patients, and sub typed these cancers based on familial WM presentation. Of the 923 patients, 221 (23.9%) patients had at least one additional malignancy to WM. Among these patients, 32 had 2, and 4 (0.43%) had 3 additional malignancies. For 167/221 (75.5%), the associated cancers were diagnosed before WM. The associated malignancies for all patients were as follows: Prostate (n=53; 9.2% of all males); Breast (n=27; 7.7% of all females); Skin (Basal and Squamous; n=61; 6.6%); Skin (Melanoma; n=16; 1.7%); Lung (n=12; 1.3%); Thyroid (n=10; 1.1%); Colorectal (n=7; 0.8%); Bladder (n=8; 0.9%) Other B-cell Malignancies (n=18; 2.0%); Renal (n=6; 0.7%); MDS (n=6; 0.65%); Other (n=11; 1.2%). The incidence of Lung (p=0.002) and Prostate (p=0.07) were higher among WM patients with Familial, Mixed B-cell Disorders Subtype. To avoid potential treatment related impact on additional cancer development, we next adjusted the observed versus expected frequencies based on SEER-17 data. The age adjusted incidence for development of any malignancy among WM patients was 7.6 fold higher when the development of another cancer antedated the diagnosis of WM. Among all WM patients, the incidence of solid cancers among first degree kin were as follows: Prostate (n=98; 10.6%); Breast (n=133; 14.4%); Skin (Basal and Squamous; n=21; 2.3%); Skin (Melanoma; n=21; 2.3%); Lung (n=116; 12.5%); Thyroid (n=9; 1.0%), Colorectal (n=79; 8.6%); Renal (n=8; 0.9%); and Gastric (n=20; 2.2%). The incidence of Breast (p=0.0098), and Skin (Melanoma) (p=0.037) cancers were higher among first degree kin of patients with the Sporadic versus Familial, Mixed B-cell Disorders Subtype. In summary, the above data suggest an increased risk for additional cancers among all WM patients, as well as specific risks for lung and prostate cancer among patients with Familial, Mixed B-cell Disorders Subtype. Moreover, these data also show the association of specific types of solid cancers in first degree kin of WM patients, particularly for WM patients with the Sporadic Subtype. n= Age (Yrs) Gender % Treated Additional Cancers Sporadic 666 60 (29–91) 64% M; 36% F 515 (77%) 163 (24.4%) Familial, Mixed B–cell Disorders 212 58 (36–85) 57% M; 43% F 156 (73%) 50 (23.5%) Familial, WM Only 45 61 (35–89) 56% M; 44% F 35 (77%) 8 (17.7%) Total 923 59 (29–91) 62% M; 38% F 706 (76.4%) 221 (23.9%) Disclosures: No relevant conflicts of interest to declare.
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Kolarek Karakaš, Mirjana. "Djece je sve manje ali su potrebe sve veće." Paediatria Croatica 69, Suppl 1 (2025): 41–43. https://doi.org/10.13112/pc.1007.
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Evidentno je da je demografski trend Republike Hrvatske u silaznoj putanji kao i u većini Europskih zemalja. Jedan od razloga je smanjenje broja žena u fertilnoj dobi jer žene sve kasnije rađaju zbog svojevrsnih životnih planova i osobnih prioriteta. Prosječna dob rađanja u Republici Hrvatskoj je u dobi od 31-34 godina. Jedna žena u prosjeku rodi 1,5 djece. Da bi se stanovništvo obnavljalo taj broj bi trebao biti 2,1 djeteta. Iseljavanje mladih obitelji u prosječnoj dobi od 20-40 godina dodatno doprinosi sveukupno manjem broju djece. Svake godine sve se manje djece rađa, pa je od 2013. godine kada je rođeno 39 935 djece, broj rođenih pao na 33 883 djece u 2022. godini. Logično bi bilo zaključiti da manji broj djece rezultira potrebom manjeg broja zdravstvenih usluga, a samim time i manjeg broja pedijatara. No, praksa pokazuje da to jednostavno nije tako. Broj zdravstvenih usluga se ne smanjuje usprkos manjem broju djece. Gledajući s pozicije ordinacija primarnih pedijatara čini se da su djeca sve bolesnija. U porastu su nove bolesti modernog doba, primjerice povećana je incidencija prekomjerne tjelesne težine uslijed loše izbalansirane prehrane i sjedilačkog načina života. Sve češći su poremećaji mentalnog zdravlja, odstupanja u razvoju, ADHD, autizam, astma, alergijske bolesti, autoimune bolesti, razne vrste ovisnosti. Uzroci 1. Prehrana Prirodna prehrana dojenjem jedan je od preduvjeta zdravlja. Sve se poremetilo kad se 60-ih godina prošlog stoljeća zamjensko mlijeko počelo promovirati kao jednako vrijedno majčinom mlijeku uz pružanja većeg komoditeta majkama. Priroda zna najbolje izbalansirati što je dojenčetu potrebno, ali u ljudskom je umu povodljivost i linija manjeg otpora. Sve to ima svoju cijenu. Potrebno je vrijeme i veliki angažman pedijatara u edukaciji roditelja što je nabolje za dijete u zaštiti njegova zdravlja. Brza prehrana dodatno doprinosi narušavanju zdravlja djeteta. 2. Perinatalni rizici Sve više djece rođeno je s neurorizikom, oko 10 posto novorođenih. Oni predstavljaju dodatni izazov za primarne pedijatre. Broj preventivnih pregleda premašuje brojku od 5 sistematskih pregleda određenu Planom i programom mjera. Takvo dijete iziskuje više pažnje i dodatnih posjeta i ciljanih pregleda, upućivanje drugim subspecijalistima i dodatnim dijagnostičkim pretragama. Ispitivanje provedeno u Specijalističkoj pedijatrijskoj ordinaciji Mirjana Kolarek Karakaš obuhvatilo je 111 djece rođene 2022. godine (neobjavljeni podatci). Rezultat prikazuje 38 djece (36,5%) s rizikom (Tablica 1). Svako treće dijete ima mogućnost smetnje u razvoju. U razdoblju od 20 godina broj djece s teškoćama je utrostručeni. Najčešće je riječ o jezično-govornim teškoćama. Napredak znanja i tehnologije u medicini smanjio je mortalitet novorođenčadi, ali je rezultirao povećanim brojem djece s neurorazvojnim teškoćama. Djeca rođena s neurorizikom i posljedično tome djeca s odstupanjem u razvoju doprinose povećanju broja usluga primarnog pedijatra, kako preventivnih tako kurativnih. 3. Boravak djece u dječjem kolektivu Sve veći broj djece upisuje se u predškolske ustanove, dječje vrtiće, igraonice i radionice što rezultira dodatnim mogućnostima obolijevanja. Roditelji danas vode i bolesnu djecu u dječji vrtić jer si ne mogu dozvoliti izostanak s radnog mjesta. To predstavlja dodatni rizik za širenje bolesti i povećani broj dolazaka u naše ordinacije. Iz priloženih brojki vidimo kako se broj djece polaznika dječjih vrtića povećava usprkos sve manjem broju novorođene djece. Tako je u pedagoškoj godini 2023/2024 upisano 153 212 djece u odnosu na 128 046 djece upisanih u pedagoškoj godini 2012/2013 (1, 2). 4. Prekomjerna administracija U odnosu na period prije 20-ak godina, administrativni poslovi, uključujući izdavanje preporuka za bolovanje roditeljima, ispričnica po izostanku iz dječjeg vrtića i škole, te potvrda za upis u dječji vrtić su u značajnom porastu. 5. Vanjski uzroci Pretjerana upotreba mobilne tehnologije doprinosi broju razvojnih teškoća. Uz nju treba naglasiti i okolišne čimbenike kao što su zagađenosti zraka, i štetne kemikalije u hrani, odjevnim predmetima i kozmetici.Emocionalni odnos roditelja i djece od velikog je značaja. Roditelji su danas preopterećeni, zaposleni od jutra do mraka. Nemaju dovoljno vremena niti energije nakon napornog posla baviti se djecom koju preuzima digitalna tehnologija. Najčešća posljedica su govorno jezični poremećaji, poremećaji ponašanja, te otklon u socijalizaciji sve do digitalnog autizma. Brojke pruženih usluga govore same za sebe. A. Hrvatski zdravstveno-statistički ljetopis ZZJZ 2013 Zaštita se provodila na 404 339 djece, od kojih 275 464 djece predškolske dobi (68,1%). Zaštitu su provodila 272 tima pedijatara. 92,4% djece predškolske dobi bilo je u skrbi pedijatra, 7,6% kod obiteljskih liječnika. U prosjeku 1 pedijatrijski tim skrbi za 1487 djece. Posjeta 2 566 745, pregledi 1 565 000 (64,2%). Preventivni pregledi 387 258, na dojenčad se odnosi 152 007 usluga (3). B. Hrvatski zdravstveno-statistički ljetopis ZZJZ 2022 Zaštita se provodi na 353 063 djece, 235 170 predškolske dobi. Registrirana su 242 pedijatra, 1 tim skrbi o 1252 djece. Broj kontakata 3 867 832, (20% više nego 2021) pregledi 1 600 771 (15,5% više nego 2021). Obavljeno je 283 063 preventivnih pregleda, od toga 162 347 usluga se odnosi na dojenčad (4). Vidljivo je iz prikazanih podataka kako se smanjuje ukupni broj preventivnih pregleda što je logično zbog manjeg broja djece, budući da su preventivni pregledi uvjetovani Planom i programom mjera koje određuje Ministarstvo zdravstva. Očigledno je da se broj pregleda bolesne djece i broj kontakata i uz manji broj korisnika povećava. Nije nevažno naglasiti iz iskustva da je broj usluga i veći, ali smo mi kao pružatelji usluga zakinuti određenim ograničenjima u prikazivanju. Naime, bez obzira koliko recepata izdali možemo prikazati samo jedan, a nevezano koliko smo uputnica morali napisati prikazuje se samo jedna. U slučaju da s roditeljem razgovaramo telefonski, a nakon toga obavimo i pregled, možemo prikazati samo jednu uslugu. Svi znamo da kad su u pitanju djeca, roditelji dolaze s više zahtjeva istovremeno. Samo jedan pregled se evidentira. Na sistematske preglede i na cijepljenje dovode se i bolesna djeca. Obavimo sistematski pregled, pregledamo bolesno dijete, ali ne možemo prikazati istovremeno i preventivni i kurativni pregled.Brojke su realan pokazatelj. Djece je sve manje, pedijatara je sve manje, ali broj usluga i potreba bolesnog djeteta uslijed modernog načina života neprestano raste. Na kraju se postavlja pitanje kako činiti više na zdravstvenoj edukaciji stanovništva u cilju preuzimanja veće osobne odgovornosti za zdravlje djeteta, preduvjeta za zdravlje naroda. Kako osvijestiti sustav zdravstva da potražnja za zdravstvenim uslugama raste, unatoč manjem broju korisnika, te da je neophodno brojem zdravstvenog kadra pratiti postojeće rastuće potrebe.
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Du, Mengxi, and Fang Fang Zhang. "Dietary Supplement Use Among Adult Cancer Survivors in the United States." FASEB Journal 31, S1 (2017). http://dx.doi.org/10.1096/fasebj.31.1_supplement.168.6.
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BackgroundMany cancer patients initiated supplement use after cancer diagnosis and yet the effect of supplement use on survival has not been established. The trend of and factors associated with dietary supplement use in cancer survivors warrant further investigation.MethodsWe examined the trend of dietary supplemental use in 1,902 adult cancer survivors who participated in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2012, and compared the frequency of supplement use in cancer survivors to that of 3,804 individuals with no history of cancer who were matched to the cancer survivors by age, sex, and race/ethnicity. The use of any supplements and individual supplements in the past 30 days was assessed based on self‐report. We further evaluated factors associated with supplement use in cancer survivors.ResultsAdult cancer survivors reported a significantly higher frequency of using any supplements (58% vs. 54%, p=0.0009) and individual supplements such as folic acid (26% vs. 23%, p=0.01), vitamin D (21% vs. 17%, p=0.0002), vitamin C (19% vs. 16%, p=0.01), and magnesium (12% vs. 10%, p=0.03) than non‐cancer individuals. Cancer survivors also reported an increasing trend of using vitamin D (11% in 1999–2000 vs. 41% in 2011–2012, p for trend<0.0001) and fish oil (1% in 1999–2000 vs. 15% in 2011–2012, p for trend<0.0001) but a decreasing trend of using calcium (18% in 1999–2000 vs. 10% in 2011–2012, p for trend=0.002). Compared to survivors who reported no supplement use, those who reported any supplement use were older (60 vs. 56 years of age, p<0.0001) and more likely to be non‐Hispanic Whites (86% vs. 76%, p<0.0001), college graduates (62% vs. 46%, p<0.0001), nonsmokers (42% vs. 38%, p<0.0001), and moderate alcohol drinkers defined as <=1 drink/d for women and <=2 drinks/d for men (41% vs. 31%, p=0.004), having a diagnosis of breast cancer (22% vs.14%, p=0.004), and being diagnosed with cancer at an older (49 vs. 45 years of age, p<0.0001). Gender, weight status, and years since diagnosis were not associated with supplement use in cancer survivors.ConclusionsIn a national sample of US adults, cancer survivors reported a higher frequency of supplement use than non‐cancer individuals. Supplement use in cancer survivors has been increasing for vitamin D and fish oil but decreasing for calcium.Support or Funding InformationNIH/NCI 1R03CA199516 Supplement Use in Adult Cancer Survivors and Individuals without Cancer in NHANES 1999–2012 Supplement Use Cancer Survivors (n=1,902) Individuals without Cancer (n=3,804) P value N (%) N (%) Any supplement use1 1,111 (58.4) 2046 (53.8) 0.0009 Multivitamin and mineral (MVM) supplement use2 Multivitamin with mineral 182 (9.6) 336 (8.8) 0.36 Multivitamin without mineral 75 (3.9) 111(2.9) 0.04 Single supplement use 444 (23.3) 877 (23.1) 0.81 Vitamins Folic Acid 492 (25.9) 862 (22.7) 0.01 Vitamin D 393 (20.7) 631 (16.6) 0.0002 Vitamin C 362 (19.0) 622 (16.4) 0.01 Vitamin E 331 (17.4) 609 (16.0) 0.18 Vitamin B12 212 (11.2} 385 (10.1) 0.23 Vitamin B6 181 (9.5) 327 (8.6) 0.25 Vitamin A 177 (9.3) 364 (9.6) 0.75 Vitamin B3 161 (8.5) 303 (8.0) 0.52 Vitamin K 54 (2.8) 118 (3.1) 0.58 Minerals Calcium 274 (14.4) 551 (14.5) 0.94 Magnesium 225 (11.8) 377 (9.9) 0.03 Zinc 153 (8.0) 311 (8.2) 0.86 Iron 130 (6.8) 242 (6.4) 0.49 Selenium 118 (6.2) 214 (5.6) 0.38 Potassium 114 (6.0) 212 (5.6) 0.52 Copper 93 (4.9) 201 (5.3) 0.53 Phosphorus 56 (2.9) 109 (2.9) 0.87 Others Fish Oil 116 (6.1) 218 (5.7) 0.58 Glucosamine 43 (2.3) 88 (2.3) 0.90 Garlic 40 (2.1) 82 (2.2) 0.90 Fiber 27 (1.4) 60 (1.6) 0.65 Glutamine 4 (0.2) 7 (0.2) 0.83 Echinacea 8 (0.4) 22 (0.6) 0.44 Any supplement use was defined as the use of the selected vitamins, minerals, non‐vitamin non‐mineral supplements. Multivitamin/mineral (MVM) supplemental use was defined as containing 3 or more vitamins with or without minerals. B‐complex vitamin is considered as a multivitamin supplement. Factors Associated with Supplemental Use in Adult Cancer Survivors1 Characteristics Survivors who reported supplemental use (N=1,111) Survivors who did not report supplemental use (N=791) P value OR (95% CI) Age, years, mean (SEM) 59.8 (0.5) 55.6 (0.6) <.000l Gender, N (%) Men 450 (34.9) 348 (37.0) 0.50 1.0 (ref.) Women 661 (65.1) 443 (63.0) 1.1 (0.8–1.4) Race/ethnicity, N (%) Non‐Hispanic White 747 (86.4) 410 (76.1) < 0001 1.0 (ref.) Non‐Hispanic Black 179 (6.0) 209 (12.2) 0.4 (0.3–0.6) Other 185 (7.6) 172 (11.7) 0.6 (0.4–0.8) Education, N (%) Grades 0–12 242 (14.3) 289 (25.1) <.000l 1.0 (ref.) Some post high school 265 (23.3) 206 (29.2) 1.4 (1.0–1.9) College graduate 602 (62.4) 296 (45.7) 2.4 (1.8–3.2) Smoking, N (%) Nonsmokers 481 (42.2) 308 (38.0) <.0001 1.0 (ref.) Former smokers 472 (42.7) 272 (31.9) 1.2 (0.9–1.6) Current smokers 157 (15.1) 210 (30.1) 0.5 (0.3–0.6) Alcohol, drink/week, N (%) Nondrinkers 414 (33.3) 345 (40.6) 0.004 1.0 (ref.) Moderate drinkers 421 (41.4) 215 (30.8) 1.6 (1.2–2.2) Heavy Drinkers 219 (25.4) 164 (28.6) 1.1 (0.8–1.5) Body mass index (BMI), kg/m2, mean (SEM) 28.9 (0.2) 29.4 (0.3) 0.13 Weight status, N (%) Normal weight (BMI=18.5–24.9) 308 (31.1) 186 (28.1) 0.60 1.0 (ref.) Overweight (BMI=25–29.9) 374 (31.8) 276 (33.2) 0.9 (0.6–1.2) Obese (BMI≥30) 429 (37.1) 329 (38.7) 0.9 (0.6–1.2) Primary diagnosis, N (%) Breast cancer 233 (22.0) 114 (14.3) 0.004 1.7 (1.2–2.4) Prostate cancer 184 (11.6) 162 (12.9) 0.45 0.9 (0.7–1.2) Colon cancer 94 (6.7) 77 (7.5) 0.54 0.9 (0.6–1.3) Lung cancer 33 (3.0) 20 (2.4) 0.40 1.3 (0.7–2.1) Other 500 (50.0) 381 (57.0) 0.02 0.8 (0.6–0.9) Multiple 67 (6.7) 37 (5.8) 0.60 1.2 (0.7–2.1) Age at diagnosis, years, mean (SEM) 49.0 (0.6) 44.6 (0.7) <.0001 Time from diagnosis, years, mean (SEM) 10.8 (0.5) 11.0 (0.4) 0.76 Time from diagnosis, N (%) >10 453 (42.0) 324 (43.0) 0.98 1.0 (ref) 5–9 279 (24.4) 196 (24.4) 1.1 (0.6–1.9) 1–4 331 (28.6) 230 (27.9) 1.1 (0.8–1.4) <1 48 (5.0) 41 (4.7) 1.0 (0.8–1.3) Frequencies, odds ratio, and 95% confidence intervals presented were weighted. Trend of Supplemental Use in Adult Cancer Survivors and Individuals without Cancer1 Supplement Use Cancer Survivors (n=1,902) p trend Individuals Without Cancer (n=3,804) p trend 99–00 01–02 03–04 05–06 07–08 09–10 11–12 99–00 01–02 03–04 05–06 07–08 09–10 11–12 Any supplement use2 125 (62.1) 133 (62.9) 156 (64.2) 131 (63.3) 192 (60.0) 197 (62.6) 177 (67.3) 0.95 239 (55.0) 286 (56.9) 313 (61.0) 260 (59.8) 352 (59.1) 332 (54.7) 264 (57.2) 0.44 Folic Acid 39 (20.7) 69 (31.5) 78 (33.0) 66 (31.3) 95 (30.4) 75 (27.9) 70 (24.5) 0.26 85 (19.3) 124 (23.9) 129 (25.3) 130 (28.2) 155 (26.7) 139 (24.6) 100 (22.0) 0.49 Vitamin D 21 (11.3) 30 (15.3) 44 (18.7) 38 (19.9) 68 (21.7) 96 (33.7) 96 (41.3) <.0001 38 (10.2) 53 (11.1) 78 (15.8) 71 (16.1) 125 (21.8) 134 (24.9) 132 (27.4) <.0001 Vitamin C 45 (22.2) 43 (26.3) 68 (29.9) 43 (21.8) 59 (18.0) 58 (19.3) 46 (16.5) 0.08 71 (17.4) 103 (22.1) 92 (16.9) 86 (20.6) 105 (19.0) 85 (15.9) 80 (19.0) 0.48 Calcium 34 (17.6) 41 (22.4) 46 (20.3) 37 (19.1) 40 (12.6) 43 (14.5) 33 (10.3) 0.002 65 (16.4) 79 (15.5) 86 (16.3) 89 (21.2) 87 (15.0) 70 (12.8) 75 (17.9) 0.02 Magnesium 28 (14.0) 23 (12.1) 36 (13.1) 26 (13.9) 36 (12.0) 41 (14.0) 35 (16.5) 0.89 45 (13.3) 55 (10.2) 50 (9.8) 53 (13.7) 67 (11.4) 59 (10.7) 48 (14.1) 0.45 Zinc 13 (6.5) 15 (7.9) 18 (7.0) 23 (12.7) 28 (7.8) 30 (11.8) 26 (11.8) 0.34 25 (6.6) 54 (10.6) 42 (7.9) 48 (9.8) 57 (9.9) 42 (8.0) 43 (10.8) 0.54 Fish Oil 1 (0.7) 4 (1.6) 6 (2.8) 13 (7.6) 26 (6.6) 32 (8.8) 34 (15.8) <.0001 3 (1.4) 10 (2.7) 19 (4.3) 59 (9.7) 66 (13.1) 66 (13.1) 44 (6.6) <.0001 Frequencies presented were weighted frequencies. Any supplement use was defined as the use of the selected vitamins, minerals, non‐vitamin non‐mineral supplements.
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Lee, Ju-Hao, Ni-Chung Lee, and Yi-Ching Tung. "SUN-033 A Rare Case: Bone Pain and Continued Linear Growth in a Young Adult Male Due to Aromatase Deficiency." Journal of the Endocrine Society 4, Supplement_1 (2020). http://dx.doi.org/10.1210/jendso/bvaa046.212.
Full textAbstract:
Abstract Introduction: Aromatase, the product of CYP19A1, catalyzes the conversion of androgens to estrogens. 46, XX infants with aromatase deficiency, due to androgen excess, present with ambiguous genitalia at birth. In 46, XY individuals, however, the subtle phenotypic features make the diagnosis even more difficult. Less than 15 male cases were reported in the literature and we present the first case of aromatase deficiency diagnosed in Taiwan. Clinical Case: A 23-year-old man, Burman overseas student of Chinese descent, presented to an orthopedist with a two-year history of left ankle pain, which was diagnosed as gout by his previous physician. Unexpectedly, unfused growth plates were discovered so he was referred to our pediatric endocrine clinic for evaluation. Reviewing his past history, we learned he is the third child of consanguineous parents. His mother experienced deepening of voice during this pregnancy which resolved following parturition. He was 177 cm tall at the age of 19. At the time he presented to our clinic, he weighed 95.3 kg and was 183 cm tall. Physical exam showed the ratio of U/L segment to be 0.82, stretched penile length 6.5 cm, bilateral testes &gt; 25 mL, pubic hair at Tanner stage V, and presence of genu valgum. The skeletal age was 14 years and 6 months. Labs showed FSH 19.7 IU/L (0.7–11.1), LH 8.18 IU/L (0.8–7.6), total testosterone 1335 ng/dL (240–871), estradiol &lt;20 pg/mL, DHEA-S 13.41 μmol/L (6.5–14.6), androstenedione 5.73 nmol/L (3.5–9.8) and 17-OH progesterone 6.55 nmol/L (2–10). GnRH (100 μg i.v) stimulation test showed a supranormal basal FSH level and a normal to higher LH response (FSH at baseline/peak were 23.0/38.6 IU/L; LH at baseline/peak were 8.81/47.7 IU/L). Under the clinical suspicion of aromatase deficiency, we performed genetic sequencing of CYP19A1 (NM_031226) and found a homozygous missense variant c.1108G&gt;A (V370M), a previously reported pathogenic mutation. A diagnosis of aromatase deficiency was made. He also had hypertension (156/87 mmHg), dyslipidemia (T-cholesterol 236 mg/dL, LDL-C 175 mg/dL) and insulin resistance (AC glucose 87 mg/dL, insulin 23.5 μU/mL, HOMA-IR 5.0, Hb1Ac 5.6%). Bone mineral density of lumbar spine (DXA) showed a T-score of -2.8, consistent with the diagnosis of osteoporosis. Conclusion: Estrogen is pivotal for epiphyseal closure in both sexes. As demonstrated in this case, estrogen deficiency in men results in tall stature and eunuchoid habitus, while it is also associated with low bone density and metabolic syndrome. The gonadotropin response in this report suggests the inhibitory role of estrogen in the male HPG axis. Clinicians may consider this rare diagnosis for men in their late teens or early twenties, who have spontaneous initiation of puberty, presenting with bone pain and continued linear growth.
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Gazi, Md. Shakhawat Hossain, Shahinur Rahman Md., and Das amir. "A Structural Equation Modeling (SEM) Approach to Explore the Association between Corporate Social Responsibility and Financial Performance: A Single Mediating Mechanism." August 27, 2019. https://doi.org/10.5281/zenodo.3378207.
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<strong><em>Abstrac</em></strong><em>t</em>: <em>The past couple of decades have seen a growing interest in Corporate Social Responsibility (CSR) research in both business and academia. It has been observed that a substantial number of studies on CSR and Financial Performance (FINP) have focused almost entirely on large firms. As pointed out earlier, the bulk number of studies on the link between CSR-firm performances is from developed countries. Thus, a limited number of studies have been conducted in developing countries and more especially in Bangladesh. We cannot generalize the findings from developed countries to developing countries without further research, therefore, requiring more research on the association between CSR and firm performance in manufacturing companies. <strong>Objective: </strong>This paper aims to exploring how CSR dimensions influence the financial performance and whether the mediating effect of selected organizational factors determine the relationship between CSR and financial performance.</em> <strong><em>Methods: </em></strong><em>A </em><em>self-administered questionnaire was used along with the simple random sampling method to collect 371 respondents’ views from medium and small scale manufacturing firms in Bangladesh. The results were analyzed by using SEM. Confirmatory Factor Analysis (CFA) was performed followed by structural model to examine the proposed model.<strong> Findings: </strong>The findings demonstrated that CSR positively affects financial performance and organizational factors fully mediate the CSR-FINP. Furthermore, this study indicates the important order of CSR dimensions which are as follows; environmental protection, social, legal and economic dimension. In addition, it was found that small and medium scale of manufacturing firms carry out moderate level of </em> <em>CSR activities. <strong>Implications: </strong>The mediation of organizational factors in CSR linkage to financial performance is a major contribution to the literature which may help to explore the relationship between CSR and firm performance.</em> <strong><em>Originality /Values: </em></strong><em>Results of the model would be practical and useful for business managers who seek a competitive solution for succeeding in a business crises and work in the settings of domestic as well as international business. <strong>Limitations and Further Research Direction: </strong>Methodologically, we used simple random sampling for data collection. Therefore, the employees may not be representative of the wider population. Thus the findings of this study cannot be generalized to other industrial sectors in Bangladesh. However, future research could be carried out on large samples. </em> <strong>1. Introduction</strong> The concept of CSR has gained a wide consideration in the academic field as well as in the business world in recent years. As a result, CSR has grown to be an issue of much concern in the 21st century for international business (Reverte, Gómez-Melero & Cegarra-Navarro, 2016; Kolk, A. & Tulder, 2010). Hence, CSR has been increasingly getting more attention in the international business studies (Park & Ghauri, 2015). Today’s organizations are using CSR to develop competitive advantage and establish congenial relations with their stakeholders. Furthermore, Multinational Corporations (MNCs) and investors in international businesses are increasingly interested in the issue of socially responsible business around the globe (Besieux <em>et al.</em>, 2015; Boehe & Cruz, 2010).Although CSR is a subjective concept, it has been a subject of extensive research over the last few decades (Jamali, 2008). Manufacturing industry is responsible for environmental pollution and social cost. Thus, CSRis used as a way to improve corporate image and increase long-term organizational performance. This study attempts to fill the gap in literature as there is lack of research on CSR in developing countries (Ralston & Egri, 2008). CSR is reflected as a western phenomenon due to the presence of social systems as compared to developing countries (Chapple & Moon, 2005). CSR has broader implications for the nation as a whole while it reduces dependency on the government for social change. The manufacturing company is selected for examining the association between CSR and financial performance. The manufacturing companies are chosen for this study due to their rapid expansion Therefore, the aim of this study is to build and test a theoretical model to identify the mediating effect of innovationtowards the relationship between CSR and financial performance in the context of developing country like Bangladesh. As per above literature review, another objectives of this study was to fill the above identified gaps by examining and evaluate the viability of the proposed model and to offer a number of recommendations for decision makers to implements CSRs program in Bangladesh, the following specific research question was formulated as “How does innovation influence the financial performance as a mediator?” The rest of the paper is organized as follows. In the next section, a theoretical framework is used to develop the model of CSR and financial performance with mediation of innovation. Likewise,later section describes the methodology of the study. It is followed by the summary of the data analysis. Then, concluded with findings together with theoretical contributions and implications for the managers, and policy makers. Finally, the limitations of the study with avenues for future research are listed. <strong>2. Theoretical Background and Hypotheses Development</strong> Using a review of prior studies on CSR and Financial Performance (FINP) from the context of manufacturing firms, we adopted the most commonly used constructs in those studies. The conceptual research model (Figure-1) developed in this study postulates the constructs in different dimensions: Environment (ENV), Economic (ECO), Social (SOC), Legal (LEG), and Innovation (INV). In the subsequent section explains the relationship among variables and the theoretical support for the hypotheses which are adopted for investigating the research question. <strong><em>2.1 CSR and Financial Performance</em></strong> Some studies have been done to investigate the relationship between CSR and Corporate Financial Performance (CFP) and between Corporate Environmental Performance (CEP) and FINP, some decades ago producing found conflicting results, although the number of the research findings indicated the positive link (see for examples Preston & O’Bannon, 1997; Orlitzky, Schmidt &Rynes, 2003; Simpson & Kohers, 2002). According to some previous researchers (Orlitzky, Schmidt and Rynes, 2003; Husted and Allen, 2001), the conflicting results had been caused by two main factors: theoretical ground and methodological aspect. To resolve the theoretical ground,Husted and Allen, (2001) andOrlitzky and Benjamin (2001)proposed the theory of corporate social performance. The effect of CSR on the firm performance has attracted quite an interesting number of researchers recently. Although, most of the studies have found positive association between CSR and FINP(Cegarra-Navarro <em>et al.</em>, 2016; Orlitzky, Schmidt &Rynes, 2003; Surroca, Tribó & Waddock, 2010), yet few other studiesfound a negative relationship(Wright & Ferris, 1997). While, some others still found no relation between the two variables(Aupperle, Carroll, & Hatfield, 1985), therefore the question still remain unsettled (Aguinis & Glavas, 2012). Such contradictory evidence has created ground to investigate this issue further and therefore, CSR effect on FINP and included factor may mediate their relationship(Aguinis & Glavas, 2012). Aupperle, Carroll and Hatfield (1985);Cochran and Wood (1984) and Ullmann (1985)found a mixed of results concerning the concurrent relationships between social responsibility and firm performance. In another study, Bhattacharya and Sen (2004) suggested that the costs of resources used in CSR activities vary among firms across industries. In environmentally sensitive industries, firms invest huge amount of money and resources in CSR activities, such as investment in Research and Development (R &D) to produce green products or building production facility and waste processing systems to improve and increase the environmental performance of products and services. These CSR activities are necessary and will help firms to create differentiated products and services which boost their sales and FINP. The above discussion led this study to posit the following hypothesis: <strong><em>H<sub>1</sub>:</em></strong><em> There is a significant positive relationship between the </em><em>CSRand the FINP.</em> According to Bitektine and Haack (2015), the growth and success of an organization depend on its relationship with several stakeholders (e.g., employees, shareholders, consumers, suppliers, government agencies, etc.) within organization and external society. As CSR issues become increasingly important in the current business environment, organizations should invest considerable efforts and resources in CSR activities to satisfy stakeholder requirements and to obtain legitimacy. <strong><em>2.2 CSR, Innovation, and Financial Performance</em></strong> Innovation related to technological advancements which are environmentally friendly is socially acceptable towards environmental sustainability and can improve firm performance (Boonkanit & Kengpol, 2010). In literature, innovation is frequently enlisted as the intensity of firm’s investments in R&D (Orlitzky & Benjamin, 2001). However, CSR literature has distinguished the verity that the linkage between CSR and firms’ FINP cannot be well comprehended without taking the role of innovation into consideration(McWilliams, Siegel, & Wright, 2006; McWilliams & Siegel, 2001).McWilliams and Siegel(2000) pointed out that if the innovation in firms is statistically controlled, the positive relationship among CSR and firms’ financial performance will disappear. There exists positive relationship between innovation and firm’s financial performance (Geroski, 1995; Geroski, Van Reenen, & Walters, 1997).Hence, it was hypothesized that: <em>H<sub>2</sub>: There is a significant positive relationship between </em><em>CSR and the INV.</em> Certain studies have found the association between CSR and innovation (Waddock, Bodwell, & Graves, 2002). Furthermore, from the literature, it may be concluded that innovation has a tendency to heave the zero-order correlation between CSR and FINP which provide relationship between innovation and CSR is statistically significant (Schwab et al., 2000). Therefore, CSR acts as a means or vehicle for the innovation (Husted & Allen, 2006, 2007) particularly in the cases where CSR is directed towards innovation (Maxfield, 2008). Indeed, innovation helps proving the business case for CSR (Maxfield, 2008). Therefore, this study postulates innovation as mediator between CSR and firm’s financial performance as per following hypotheses: <em>H<sub>3</sub>: Innovation moderates the relationship between CSR and FINP.</em> Environment Economic Social Legal CSR Innovation Financial Performance <strong>H<sub>1</sub></strong> <strong>H<sub>2</sub></strong> <strong>H<sub>3</sub></strong> <em>Figure-1: Model and the related hypothesis of the research</em> To understand the relationship between CSR and FINP, we proposed a model that integrates innovation as a mediator into the relationship between CSR and FINP. In this model, we argued that CSR is significantly associated with INV (<em>H<sub>1</sub></em>), and CSR can also enhance FINP (<em>H<sub>2</sub></em>), in other words, INV will mediate the relationship between CSR and FINP (<em>H<sub>3</sub></em>). <strong>3. Methodology</strong> <strong><em>3.1 Measurement Instruments</em></strong> In order to conduct this empirical research, the variables in theoretical model were employed using previously validated research instruments. The study adopted the instrument of Maignan and Ferrell (2001) to measure CSR in hypothesized model. Moreover, CSR measurement items are adopted from Mishra and Suar (2010). Likewise, this study used the inductive approach to determine the dimension of CSR. The variables include: environmental dimension, economic dimension, social dimension, and legal dimension. <em>Table-1: Item Source of the Construct</em> <strong>Construct</strong> <strong>Items</strong> <strong>Source</strong> Environment ENV-1 Practices recycling pollutants and wastes. Schiebel and Pöchtrager (2003) ENV-2 Manufactures eco-friendly products. ENV-3 Purchases environmentally friendly products. ENV-4 Voluntarily does recycling and re-use. Economic ECO-1 Has a strong competitive position. Balabanis, Phillips, and Lyall, (1998) ECO-2 This firm seeks a profitable business. ECO-3 Closely monitor employees' productivity. ECO-4 Maximizing our profits. Social SOC-1 Supports culture and art activities Austin (2000);Grudinschi <em>et al.</em> (2013); Davenport (2000);Hopkins (2003); Spiller (2000) SOC-2 Participate in charitable activities SOC-3 Supports educational institutions. SOC-4 Assists to enhance quality of life Legal LGL-1 Obeys state, and local regulations. Maignan and Ferrell (2001); Spiller (2000) LGL-2 This firm fulfills its legal obligation. LGL-3 Meets minimal legal requirements LGL-4 Our products meet legal standards. Innovation INV-1 Frequently tries out new ideas. Calantone, Dröge and Vickery (2002); Moore (2001); Moore (2001) INV-2 Seeks out new ways to do things. INV-3 Our company is creative INV-4 Our new product introduction has increased Financial Performance FINP-1 We had larger market share. Mishra and Suar (2010) FINP-2 Our sales growth has been substantially better. FINP-3 Return on assets has been substantially better. FINP-4 Return on investment has been substantially. <strong><em>3.2 Population and Sample </em></strong> We focused on employees of manufacturing companies in Bangladesh. The companies were selected in a stepwise process. The respondents were selected from a population that had already experienced CSR activities in Bangladesh. Therefore, the sample size was calculated with a level of significance of 0.05. Calculation of the defined sample showed that the minimum sample size to be 196. <strong><em>3.3 Sampling Method</em></strong> The sampling method used in the study was purposive sampling. Atotal of 439 manufacturing firms in Bangladesh that meet the criteria: (1) the number of workers is more than 100 people (2) the firm is active in CSR activities at least 3 years, were considered in this study. The survey questionnaire was used in the research in which employees and managers of the firms are the unit of analysis. A self-administered questionnaire was sent to each respondent. <strong><em>3.4Questionnaire Design</em></strong> The questionnaire comprised two sections: section-A was designed to extract the respondents’ demographic characteristics, and section-B measured CSR based on the antecedent variables as follows environmental dimension of CSR, customer dimension, community dimension, legal dimension, ethical dimension, employees dimension, economic dimension. All instruments were designed on a five-point Likert scale ranging from ‘strongly agree (5)’ to ‘strongly disagree (1)’, using multi-item scales. Furthermore, the questionnaires were distributed to 410 respondents, and 383 responses were received, a response rate of 93.41%. After receiving the responses, missing value analysis was performed and dropped the ones with high missing values. The remaining data included total of 371 responses, the response rate for combined sample is 90.49%. It is an acceptable response rate as per the methodological studies (Anderson <em>et al.</em>, 1988; Hair Jr <em>et al.</em> 2010). <strong><em>3.5 Data Analysis </em></strong><strong><em>Methods</em></strong> The data was analyzed through software Statistical Package for Social Sciences (SPSS) and Analysis of Moment Structures (AMOS). Reliability and correlation analysis were performed through SPSS 20 and SEM was conducted through AMOS 23 as SEM was conducted because it has the ability to estimate both direct and indirect effects of a testable model; it also has the ability to ensure the consistency of the model with the data and to estimate the effects among the constructs. In the research, further, AMOS was used for testing confirmatory factor analysis (CFA) and the structural model. Maximum likelihood method was used while testing the measurement model and the structural model. In order to test the model hypothesis, this study administered survey using self-administered instruments. <strong>4. Results</strong> <strong><em>4.1 Demographic Characteristics of Sample</em></strong> The detailed demographic attributes of the respondents are shown in Table 1. Out of 371 respondents, 67.39% were male and 32.61% were female who participated in the study. The distribution of the respondents by age, with 21.56% wasbelow 30 years old, from 31 to 39 were 57.15%, more than 40 years were 21.29%.Approximately,45.82% of respondents have taken under-graduate and post-graduate education and 14.83% of them have taken others degree from different educational background; with 50.67% of them having more than 4 years of job experience. <em>Table-2: Demographic Characteristics of the Informants</em> <strong>Variables</strong> <strong>Description</strong> <strong>Frequency</strong> <strong>Percentage (%)</strong> <strong>Gender</strong> Male 250 67.39 Female 121 32.61 <strong>Age</strong> 20-30 Years 80 21.56 31-39 Years 212 57.15 More than 40 years 79 21.29 <strong>Educational Qualification</strong> Undergraduate 56 15.09 Bachelor 90 24.26 Masters 170 45.82 Others 55 14.83 <strong>Experience</strong> 0-4 Years 183 49.33 5-8 Years 89 23.99 More than 9 Years 99 26.68 <strong><em>4.2 Descriptive Statistics</em></strong> The descriptive statistics of the sample are tabulated as below in Table 3.Table 3reports the descriptive statistics for both dependent and independent variables. It is evident that the sample is well diversified by the tests of normality for preliminary results. There have been responses from managers from different sectors, experience levels. Table 3provides the means, standard deviations, minimum, maximum, skewness, kurtosis among the model variables. <em>Table-3: Descriptive Statistics for the Dependent and Independent Variables</em> <strong>Variables</strong> <strong>Mean</strong> <strong>Std. Deviation</strong> <strong>Minimum</strong> <strong>Maximum</strong> <strong>Skewness</strong> <strong>Kurtosis</strong> Environment 3.8120 .67948 1.25 5.00 -1.504 2.579 Economic 3.7190 .61103 1.25 5.00 -1.181 3.019 Social 3.6759 .66973 1.25 5.00 -.946 1.155 Legal 3.5020 .83210 1.00 5.00 -.450 .139 Innovation 3.6152 .81271 1.25 5.00 -.194 -.197 Financial Performance 3.5539 .70504 1.25 5.00 -.371 .435 The average level of CSR in the sample was high. The differences between several means for total CSR and environmental, customer, community, employees, economic, satisfaction, innovation, reputation, motivation, productivity, financial performancewere not significant. More than two-third (2/3) of companies do not disclose any environmental information in their annual reports (median and minimum are equal to zero). Thedistribution of variables was skewed.On considering total CSR level, we found most of variables to be statistically significant: industry environmental, community and employee. The higher level of total CSR disclosure occurs in companies with higher level of innovation, motivation, productivity, satisfaction of the employees in the organization. <strong><em>4.3 Reliability Measurement</em></strong> The reliability of construct is deemed appropriate if value remains at least 0.7 for exploratory research and 0.8 for basic research (Nunnally, 1978). The Cronbach alpha was calculated for measuring reliability. A reliability analysis was conducted through Cronbach’s alpha coefficient. Therefore, Cronbach’s alpha coefficient was used to measure reliability or consistency between variables. An alpha coefficient that is higher than 0.8 implies a strong consistency, and an alpha coefficient that is higher than 0.6 implies acceptable consistency. In this analysis, all the variables scored higher than 0.8. Therefore, the respondents answered the questions consistently. Table 4summarizes the reliability analysis as follows. <em>Table-4: Reliability of the constructs</em> <strong>Variables</strong> <strong>Code</strong> <strong>Items</strong> <strong>Cronbach’s Alpha (α)</strong> Environment ENV-1, ENV-2, ENV-3, ENV-4 4 .866 Economic ECO-1, ECO-2, ECO-3, ECO-4 4 .814 Social SOC-1, SOC-2, SOC-3, SOC-4 4 .816 Legal LGL-1, LGL-2, LGL-3, LGL-4 4 .975 CSR CSR-1, CSR-2 CSR-3, CSR-4 4 .903 Innovation INV-1, INV-2, INV-3, INV-4 4 .944 Financial Performance FINP-1, FINP-2, FINP-3, FINP-4 4 .941 The seven constructs showed high internal consistency and reliability, with Cronbach alpha values of 0.866 for environmental CSR, 0.814 for economic CSR, 0.816 for social CSR, 0.975 for legal CSR, 0.903 for CSR, and 0.944 for innovation, and 0.941 for FINP. All values are greater than the recommended value of 0.7 (Nunnally, 1978). The result revealed a factor-loading index that was higher than 0.6 for all questions. This score proved the internal and external validity of the questions in this study. <strong><em>4.4 Confirmatory factor analysis summary</em></strong> Table 5 shows the summary of CFA. It shows the corresponding factors and the loading items and their scores. CFA tests the validity and reliability of all constructs that is conceived as a one-dimensional, precise, and consistent indicator in measuring its latent variables (Jöreskog & Sörbom, 1993). The cut of value for the construct reliability is recommended to be > 0.7, while the cut of the value of average variance extracted is recommended to be > 0.5, and the recommended loading factor is 0.6 or moreHair Jr <em>et al.</em> (2010). Table 5 shows the construct reliability value more than 0.7, greater than 0.5. The loadings and AVE for all items exceeded the 0.5 acceptable threshold, thus convergent validity is confirmed (Henseler, Ringle, & Sarstedt, 2015). <em>Table-5: Outcomes of Measurement Model</em> <strong>Variables (Construct)</strong> <strong>Items (Code)</strong> <strong>Estimates (Loadings)</strong> <strong>CR</strong> <strong>AVE</strong> Environment ENV-1 .79 .867 .621 ENV-2 .79 ENV-3 .81 ENV-4 .76 Economic ECO-1 .77 .815 .525 ECO-2 .69 ECO-3 .75 ECO-4 .68 Social SOC-1 .68 .819 .531 SOC-2 .75 SOC-3 .70 SOC-4 .77 Legal LGL-1 .99 .976 .910 LGL-2 .96 LGL-3 .91 LGL-4 .96 CSR CSR-1 .89 .905 .706 CSR-2 .82 CSR-3 .71 CSR-4 .93 Innovation INV-1 .93 .905 .809 INV-2 .92 INV-3 .89 INV-4 .86 Financial Performance FINP-1 .86 .942 .802 FINP-2 .95 FINP-3 .89 FINP-4 .89 <em>Note: Reference value ** p < 0.05; CR = Composite Reliability, AVE = Average Variance Extracted.</em> The loadings, AVE, composite reliability and Cronbach’s alpha (<em>α) </em>are presented in Table 5. It can be seen from the Table 5 that CR values ranged from 0.815 to 0.976, which supports strong internal reliability. Table 5 also shows that the estimated constructs loading ranged from 0.68 to 0.99 and AVE ranged from 0.525 to 0.910 are greater than the recommended levels.Therefore, the conditions for convergent validity are satisfied in this study. It is clear from results that the items on each factor met the requirements of reliability and validity (Nunnally, 1978). <strong><em>4.5 Discriminant Validity Analysis</em></strong> To determine the discriminant validity of the construct’s used in this research, we followed the criteria suggested byFornell and Larker, (1981). They suggested that the value of the square root of the AVE for each construct should exceed that of correlations between constructs. As can be seen in Table 6, the square root values of the AVE for each construct are higher in comparison with the AVEs in Table 5. This outcome confirms that discriminant validity is present. <em>Table-6: Discriminant Validity Analysis</em> <strong>Constructs</strong> <strong>FINP</strong> <strong>ENV</strong> <strong>ECO</strong> <strong>SOC</strong> <strong>LGL</strong> <strong>CSR</strong> <strong>INV</strong> <strong>FINP</strong> 0.895 <strong>ENV</strong> 0.380 0.788 <strong>ECO</strong> 0.365 0.650 0.725 <strong>SOC</strong> 0.320 0.784 0.646 0.729 <strong>LGL</strong> 0.250 0.537 0.414 0.578 0.954 <strong>CSR</strong> 0.345 0.386 0.286 0.306 0.260 0.840 <strong>INV</strong> 0.198 0.299 0.340 0.262 0.184 0.165 0.900 <strong><em>4.6 Model Testing</em></strong> The testing results of the end model of the research (Table 7) are as follow: the value of Chi Square =537.121with df = 329, probability = 0.000, Goodness of Fit Index (GFI) = 0.911, Comparative Fit Index (CFI) = 0.976, Root Mean Square Error of Approximation (RMSEA) = 0.041, Cmin/df = 1.633. The fit of measurement of hypotheses model, was good as indicated by GFI, IFI, TLI, and CFI values are higher than the threshold values suggested by Nunnally (1978). Considering all these outcomes, it was concluded that the model fits the data well given that it exceeds all the basic requirements for goodness of-fit measures. All the values of the index showed good model feasibility criteria. This means that the research data can be used to support the structural models proposed. <em>Table-7: Summary of Model Fitness indices</em> <strong>Modification Indices of Predictor Variables</strong> <strong>Desirability Range</strong> <strong>Estimated Range</strong> <strong>Level of Positions</strong> CMIN/DF 3.00 1.633 3.00>1.633 Satisfactory RMR (Root Mean Squires Residuals) 0.09 0.024 0.09>0.024 Good GFI (Goodness of Fit Index) 0.9 0.911 0.9<0.911 Good IFI (Incremental Fit Index) 0.9 0.976 0.9<0.976 Good TLI (Tucker Lewis Index) 0.9 0.972 0.9<0.972 Good CFI (Comparative Fit Index) 0.9 0.976 0.9<0.976 Good RMSEA (Root Mean Squire Error of Approximation) 0.08 0.041 0.08>0.041 Good The overall values provided evidence of a good model fit. All of the model-fit indices exceeded the respective common acceptable levels suggested in previous research, following the suggested cut-off value, demonstrating that the proposed model provided an adequate fit to the data collected. <strong><em>4.7 Hypotheses Testing Result of Generating Model</em></strong> Table 8 is used as the base in the testing of the five hypotheses proposed in the research.To examine the impact of CSR on FINP, CSR on INV, and INV on FINP over time, a longitudinal analysis was conducted using data collected in 2019. Table 8 shows the hypotheses test, in determining the significance of each path coefficient, estimate of regression weight, standard error of regression weight, and critical ratio for regression weight were used. Table 8 presents each parameter's C.R., estimate and S.E of the generating model. SEM analysis was conducted to determine the relationship of several variables in the research model. Hence, CSR has a significant positive and direct impact on Financial Performance (β =.306; C.R = 6.142; P = ***) or H<sub>1</sub> was supported. And, Corporate Social Responsibility has a significant positive and direct impact on Innovation (β=.235; C.R= 3.132; P= 0.002) or H<sub>2</sub> was supported. Finally, Innovation has a positive significant direct impact on Financial Performance (β=.0.096; C.R= 2.603; P= 0.009) or H<sub>3 </sub>was also supported. <em>Table-8: Path Analysis Summary</em> <strong>Hypothesis</strong> <strong>Relationship of Path</strong> <strong>Estimate</strong> <strong>S.E.</strong> <strong>C.R.</strong> <strong>P-value</strong> <strong>Decision</strong> IV Path DV H<sub>1</sub> CSR ---> FINP .306 .050 6.142 *** Supported H<sub>2</sub> CSR ---> INV .235 .075 3.132 .002 Supported H<sub>3</sub> INV ---> FINP .096 .037 2.603 .009 Supported These results show that innovation mediates the relationship between CSR and Financial Performance. There exists a mediatory relationship between CSR and financial performance. Hence, all the hypotheses including mediation (H<sub>1</sub>, H<sub>2</sub>, and H<sub>3</sub>) were supported. <strong><em>4.8 Mediating Effects</em></strong> The mediation effect of the mediator variables of innovation were evaluated using Baron and Kenny’s approach. To assess the significance of the mediation effect, Sobel’s test for mediation significance was conducted. The result of the Barron-Kenny mediation test (Table 9) showed that there are partial mediation effects of innovation on financial performance. <em>Table-9: Barron-Kenny’s Mediation Effect</em> <strong>IV</strong> <strong>MV</strong> <strong>DV</strong> <strong>IV - > DV</strong> <strong>SE</strong> <strong>IV -> MV</strong> <strong>SE</strong> <strong>IV + MV - > DV</strong> <strong>Mediation</strong> <strong>IV->DV</strong> <strong>SE</strong> <strong>MV->DV</strong> <strong>SE</strong> Partial Mediation CSR INV FINP 0.326 0.048 0.167 0.058 0.0375 .048 0.163 0.043 After assessing the size of the mediation effect, we proceed to evaluate the significance of these effects and based on Sobel’s test (Table 10), we found that mediation effect is significant at 0.001 levels. <em>Table-10: Sobel’s Test for Significance of Mediation Effect</em> <strong>IV</strong> <strong>MV</strong> <strong>DV</strong> <strong><em>Sobel’s Test</em></strong> <strong>t-value</strong> <strong>p-value</strong> <strong>Sig.</strong> CSR INV FINP 3.37142 0.001 Yes Besides evaluating the mediation effects, we also examine the direct, indirect, and total effects of all the exogenous variables. Table 11 shows that there were no indirect effects of CSR on INV; CSR on FINP; and INV on FINP. Other exogenous variables were found to have significant direct, indirect, and total effects on their respective endogenous variables. In terms of indirect effect on FINP, CSR (0.022) has the greatest indirect effect followed by INV (0.000). <em>Table-11: Direct, Indirect, and Total Effect</em> <strong>IV</strong> <strong>DV</strong> <strong><em>Direct Effect</em></strong> <strong><em>Indirect Effect</em></strong> <strong><em>Total Effect</em></strong> CSR INV 0.235 0.000 0.235 CSR FINP 0.306 0.022 0.328 INV FINP 0.096 0.000 0.096 <strong>5. Conclusions and Recommendations</strong> <strong><em>5.1 Conclusions </em></strong> This study was conducted to investigate an examination of the relationship between CSR and financial performance mediating by selected outcomes. This study provides imperative information for corporate decision makers who are interested to develop some competitive advantage and ensure sustainable growth in the market. The most remarkable finding of the study was that CSR has significantas well as positive influence on financial performance with mediating effect of innovation. Also analysis of this study indicated that environment economic, social, and legal dimensions aregood predictors, and play significant role in CSR. Moreover, CSR can help to create a competitive advantage by encouraging the development of a workforce that effectively carries out the firm’s business strategy, leading to improved business performance. <strong><em>5.2</em></strong> <strong><em>Recommendations</em></strong> The study recommends that business organization should engage in doing CSR activities to ensure successful financial performance in rival business environment. Therefore, the business firms need to take social and corporate collaboration initiative with stakeholders, which will lead to solve social, employee, community and environmental problems, as well as improve firm’s financial performance and the efficiency and the effectiveness of business activity. <strong>6.</strong> <strong>Implications</strong> The result of this study adds to the existing body of research literature which founda statistical significance in the relationship between CSR and financial performance. The findings also suggest that different types of CSR actions influence stakeholder’s attitudes differently and this understanding may help managers formulate effective and efficient CSR strategies. Furthermore, this study has implications for entrepreneurs, researchers and policy makers in that they should exercise the outcomes of the CSR activities in business organization. It is clear from different statistical analysis that CSR activities can increase firm performance over a period of time. <strong>7.Limitations and Further Research Direction</strong> <strong><em>7.1 Limitations</em></strong> Despite the implications of the above results, the study had certain limitations; the first limitation was the relatively low of sampled size. Methodologically, we used a convenience sample for data collection purposes. Therefore, the employees may not be representative of the wider population. Thus the findings of this study cannot be generalized to other industrial sectors in Bangladesh. Finally, this study contributes to an overall understanding of CSR level that needs to be practiced in different organizations. <strong><em>7.2Further Research Direction</em></strong> The research findings can be a basis for further research to validate and develop better models to explain firm performance in the large-scale manufacturing firms related to CSR. However, future research could examine more antecedent or factors influencing CSR in Bangladesh. In addition, external stakeholders’ perceptions could also be considered in future research using different methodological tools, such as interviews to specify their opinions on the company’s characteristics and the level of CSR practice.