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1
Little, Elizabeth, and Lea Simpson. "Counts Count." Art Documentation: Journal of the Art Libraries Society of North America 42, no. 1 (2023): 24–35. http://dx.doi.org/10.1086/728258.
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Billard, Lynne. "The Census Count: Who Counts? How Do We Count? When Do We Count?" PS: Political Science & Politics 33, no. 04 (2000): 767–74. http://dx.doi.org/10.1017/s1049096500061977.
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Billard, Lynne. "The Census Count: Who Counts? How Do We Count? When Do We Count?" PS: Political Science and Politics 33, no. 4 (2000): 767. http://dx.doi.org/10.2307/420913.
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Wagner, Gregory R. "Work Counts So Count It." Respiration 84, no. 3 (2012): 191–92. http://dx.doi.org/10.1159/000339419.
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Lo, Selina, and Richard Horton. "Everyone counts—so count everyone." Lancet 386, no. 10001 (2015): 1313–14. http://dx.doi.org/10.1016/s0140-6736(15)60305-1.
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Gorman, G. E. "How do we count our chickens? Or do citation counts count?" Online Information Review 29, no. 6 (2005): 581–84. http://dx.doi.org/10.1108/14684520510638043.
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Ho, D. D. "Viral Counts Count in HIV Infection." Science 272, no. 5265 (1996): 1124–25. http://dx.doi.org/10.1126/science.272.5265.1124.
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Kuo, Yu-Hsuan, Cho-Chun Chiu, Daniel Kifer, Michael Hay, and Ashwin Machanavajjhala. "Differentially private hierarchical count-of-counts histograms." Proceedings of the VLDB Endowment 11, no. 11 (2018): 1509–21. http://dx.doi.org/10.14778/3236187.3236202.
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Kordower, Jeffrey H. "Making the counts count: the stereology revolution." Journal of Chemical Neuroanatomy 20, no. 1 (2000): 1–2. http://dx.doi.org/10.1016/s0891-0618(00)00079-x.
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Tullus, Kjell. "Low urinary bacterial counts: do they count?" Pediatric Nephrology 31, no. 2 (2015): 171–74. http://dx.doi.org/10.1007/s00467-015-3227-y.
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Townsend, Christine, and Nancy Skinner. "When Counts Count: Improving Practice and Documentation." Journal of Obstetric, Gynecologic & Neonatal Nursing 39 (September 2010): S82. http://dx.doi.org/10.1111/j.1552-6909.2010.01121_47.x.
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Grayson, Lesley. "Making Research Count – where it really counts." Evidence & Policy: A Journal of Research, Debate and Practice 3, no. 1 (2007): 135–38. http://dx.doi.org/10.1332/174426407779702157.
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Holmes, John A., George M. W. Cronkite, Hermann J. Enzenhofer, and Timothy J. Mulligan. "Accuracy and precision of fish-count data from a “dual-frequency identification sonar” (DIDSON) imaging system." ICES Journal of Marine Science 63, no. 3 (2006): 543–55. http://dx.doi.org/10.1016/j.icesjms.2005.08.015.
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Abstract The reliability of sockeye-salmon (Oncorhynchus nerka) count data collected by a dual-frequency, identification sonar (DIDSON) system is evaluated on the basis of comparisons with visual counts of unconstrained migrating salmon and visual counts of salmon constrained to passing through an enumeration fence. Regressions fitted to the DIDSON count data and the visual count data from the enumeration fence were statistically indistinguishable from a line with slope = 1.0 passing through the origin, which we interpret as agreement in both counts. In contrast, the regressions fitted to the DIDSON count data and the unconstrained visual count data had slopes that were significantly <1.0 (p < 0.001) and are consistent with an interpretation of systematic bias in these data. When counts of both unconstrained and constrained fish from the DIDSON system were ≥50 fish event−1, repeated counts of the DIDSON files were observed to produce the same counts 98–99% of the time, respectively, and based on the coefficient of variation, counts of individual passage events varied <3% on average. Therefore, the DIDSON count data exhibit high precision among different observers. As an enumeration fence provides a complete census of all fish passing through it, we conclude that fish-count data produced by the DIDSON imaging system are as accurate as visual counts of fish passing through an enumeration fence when counts range up to 932 fish event−1, the maximum count recorded during our study, regardless of the observer conducting the count. These conclusions should be applicable to typical riverine applications of the DIDSON system in which the bottom and surface boundaries are suitable for acoustic imaging, the migrating fish are adult salmon, and the transducer is carefully aimed so that the beams ensonify the area through which the salmon are migrating.
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Powell, A. Michael, Shirley A. Powell, and Chris Jackson. "Documented chromosome numbers 2017:1. Miscellaneous counts mostly from western Texas (U.S.A.), one each from New Mexico (U.S.A.) and Mexico." Journal of the Botanical Research Institute of Texas 11, no. 1 (2017): 143–46. http://dx.doi.org/10.17348/jbrit.v11.i1.1145.
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Thirty meiotic chromosome counts are reported for 18 species in six families of plants from western Texas, mostly the Trans-Pecos region, and one count each from New Mexico and Mexico. The counts for Perityle microcephala, Echinocereus coccineus var. paucispinus from Bandera County (= subsp. roemeri), Dayia havardii, and the tetraploid counts for Solanum tenuipes var. tenuipes are first reports. The chromosome numbers listed here for other species are consistent with previous reports.
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Bonaccio, Marialaura. "Does platelet count count?" Thrombosis Research 148 (December 2016): 143–44. http://dx.doi.org/10.1016/j.thromres.2016.11.001.
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ADKINSON, ROBERT W., RONALD H. GOUGH, and JEFFREY J. RYAN. "Use of Individual, Premoistened, Disposable Wipes in Preparing Cow Teats for Milking and Resultant Raw Milk Quality and Production1." Journal of Food Protection 54, no. 12 (1991): 957–59. http://dx.doi.org/10.4315/0362-028x-54.12.957.
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Two methods of preparing cows for milking were compared. One preparation consisted of wiping each teat clean with individual, premoistened, disposable wipes. This method was compared with washing teats with a hand-held water nozzle and drying with individual paper towels. Two groups of eight Holstein cows each were randomly assigned to the two treatments. Aseptically collected weigh jar milk samples from individual cow milkings were analyzed for standard plate count, preliminary incubation count, laboratory pasteurization count, and coliform count. Pretrial bacterial counts were monitored for 2 d and were used as covariates in statistical analyses. Cows were sampled for 7 d followed by a 2-d rest after which treatments were switched and cows sampled for another week. Method of udder preparation did not affect daily milk production, fat or protein percent. Standard plate counts and preliminary incubation counts were significantly lower for wipe treatment (363 vs 933 CFU/ml and 263 vs 661 CFU/ml). There was no treatment difference for laboratory pasteurization count or coliform count. Raw milk quality as determined by standard plate count and preliminary incubation count was improved by the wipe treatment.
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Segal, Jodi B., and Alison R. Molterno. "Platelet Counts Vary by Ethnicity, Sex, and Age: Analysis of NHANES III Data." Blood 104, no. 11 (2004): 3937. http://dx.doi.org/10.1182/blood.v104.11.3937.3937.
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Abstract Background: The possibility of variation in platelet count by age and genetic background has not been examined. Identification of subpopulations with elevated platelet counts, within what is traditionally considered a normal range, may identify a group with excessive morbidity or mortality. Furthermore, platelet count differences may suggest populations in which genetic polymorphisms in regulatory proteins such as the thrombopoietin receptor influence platelet production. We hypothesized that there were differences in platelet count by ethnicity, sex and age not explained by environmental factors. Objective: To demonstrate differences in mean platelet counts by ethnicity, sex, and age while controlling for variables known to influence platelet count. Methods and Design: We used data from the National Health, Nutrition and Examination Survey III (NHANES III), which is a multistage probability sample of the United States population with data collected between 1988 and 1994. Using appropriate weighting for the complex sampling design, the geometric mean platelet count was calculated for the total population and the population stratified by ethnicity, sex, and age, while controlling for C-reactive protein, white blood cell count, iron-deficiency, serum folate, markers of alcohol intake, presence of hepatitis B or C antibodies, and diabetes mellitus. Other potential influences, such as medications, were found not to affect the predicted counts and not included in the models. Results: The lowest mean platelet counts were among whites (259 K/ml [95% C.I. 255–264 K/ml]) and the highest were in non-Hispanic blacks (275 K/ml [95% C.I. 270–280 K/ml]) with Mexican-Americans having intermediate values (266 K/ml [95% C.I. 261–272 K/ml]), when controlled for age and sex. Older men and women of each ethnicity consistently had lower mean platelet counts, with 60–69 years olds having mean counts approximately 7 K/ml lower than young adults (p=0.015) and 70–90 year olds having mean counts 19 K/ml lower than young adults (p<0.001). Even with controlling for iron deficiency, women had significantly higher platelet counts than men (273 K/ml [95% C.I. 269 – 278]) versus 251 K/ml [95% C.I. 245 – 256]) Conclusion: Mean platelet counts differ by ethnicity, sex, and age and these differences are not explained by covariates known to influence platelet count. This suggests that genetic influences on the platelet count are operative. These data also suggest that there may be a hormonal regulation of platelet count. The decline with age may reflect decreased stem cell function with age; alternatively, there may be a survival advantage to having a lower platelet count. Longitudinal studies of platelet count with aging are indicated.
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Homburg, Annika, Christian H. Weiß, Gabriel Frahm, Layth C. Alwan, and Rainer Göb. "Analysis and Forecasting of Risk in Count Processes." Journal of Risk and Financial Management 14, no. 4 (2021): 182. http://dx.doi.org/10.3390/jrfm14040182.
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Risk measures are commonly used to prepare for a prospective occurrence of an adverse event. If we are concerned with discrete risk phenomena such as counts of natural disasters, counts of infections by a serious disease, or counts of certain economic events, then the required risk forecasts are to be computed for an underlying count process. In practice, however, the discrete nature of count data is sometimes ignored and risk forecasts are calculated based on Gaussian time series models. But even if methods from count time series analysis are used in an adequate manner, the performance of risk forecasting is affected by estimation uncertainty as well as certain discreteness phenomena. To get a thorough overview of the aforementioned issues in risk forecasting of count processes, a comprehensive simulation study was done considering a broad variety of risk measures and count time series models. It becomes clear that Gaussian approximate risk forecasts substantially distort risk assessment and, thus, should be avoided. In order to account for the apparent estimation uncertainty in risk forecasting, we use bootstrap approaches for count time series. The relevance and the application of the proposed approaches are illustrated by real data examples about counts of storm surges and counts of financial transactions.
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Toth, Christopher, Wonho Suh, Vetri Elango, et al. "Tablet-Based Traffic Counting Application Designed to Minimize Human Error." Transportation Research Record: Journal of the Transportation Research Board 2339, no. 1 (2013): 39–46. http://dx.doi.org/10.3141/2339-05.
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Basic traffic counts are among the key elements in transportation planning and forecasting. As emerging data collection technologies proliferate, the availability of traffic count data will expand by orders of magnitude. However, availability of data does not always guarantee data accuracy, and it is essential that observed data are compared with ground truth data. Little research or guidance is available that ensures the quality of ground truth data with which the count results of automated technologies can be compared. To address the issue of ground truth data based on manual counts, a manual traffic counting application was developed for an Android tablet. Unlike other manual count applications, this application allows data collectors to replay and toggle through the video in supervisory mode to review and correct counts made in the first pass. For system verification, the review function of the application was used to count and recount freeway traffic in videos from the Atlanta, Georgia, metropolitan area. Initial counts and reviewed counts were compared, and improvements in count accuracy were assessed. The results indicated the benefit of the review process and suggested that this application could minimize human error and provide more accurate ground truth traffic count data for use in transportation planning applications and for model verification.
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Saberi, Parya, Nikolai H. Caswell, Cristina I. Gruta, Jason N. Tokumoto, and Betty J. Dong. "Immunologic Benefits of Enfuvirtide in Patients Enrolled in a Drug Assistance Program." Annals of Pharmacotherapy 42, no. 5 (2008): 621–26. http://dx.doi.org/10.1345/aph.1k572.
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Background: Randomized clinical trials have demonstrated that enfuvirtide plus an optimized background regimen can cause a significant increase in CD4+ cell counts and a reduction in HIV RNA levels. Objective: To describe and anaiyze CD4+ cell count and HIV RNA changes in HIV-infected patients receiving enfuvirtide and a prescribed background regimen (PBR) in a primarily clinical setting. Methods: A retrospective review from September 1998 through August 2005 of CD4+ cell counts and HIV RNA changes from baseline was conducted in patients receiving enfuvirtide. Data were stratified and analyzed according to baseline CD4+ cell count and HIV RNA. Results: A mean CD4+ cell count increase of approximately 102 cells/mm3 was observed, regardless of baseline CD4+ cell count, in 187 patients receiving enfuvirtide during a mean of 19.4 months of follow-up. During 3 years of follow-up, patients initiating enfuvirtide at CD4+ cell counts less than 100 cells/mm3 never achieved absolute CD4+ cell counts comparable to the counts in patients starting enfuvirtide at CD4+ cell counts of 100 cells/mm3 or more. In 38.3% of patients achieving an undetectable HIV RNA level, a mean CD4+ cell count increase of 185 cells/mm3 was observed. An unexpected finding was that a mean CD4+ cell count increase of 76 cells/mm3 occurred in 61.7% of patients not achieving complete viral suppression. Conclusions: Immunologic benefits were observed in subjects continuing enfuvirtide plus a PBR irrespective of baseline CD4+ cell count, complete viral suppression, or antiretroviral susceptibility data. Dala suggest that initiation of enfuvirtide at CD4+ cell counts greater than 100 celis/mm3 may be immunologically advantageous and independent of complete virologic response.
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Akevwighome, Solomon, Bruno Chinko, Sunday Ojeka, Kinikanwo Green, and Datonye Dapper. "Assessment of CD4, CD8 and White Cell Parameters Amongst HIV Seronegative Pregnant Subjects in Port Harcourt, Nigeria." Science Frontiers 5, no. 2 (2024): 74–80. http://dx.doi.org/10.11648/j.sf.20240502.11.
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Pregnancy involves maternal immunological adjustments to accommodate the fetus and maintain a strong immune defense against potential pathogens. The present study evaluated the changes in CD4, CD8, white blood cell (WBC) and total lymphocyte count (TLC) amongst HIV seronegative pregnant subjects in Port Harcourt, Nigeria. A total of 302 female subjects (18-39 years) were recruited for the study. They consisted of 205 pregnant subjects and 97 non-pregnant subjects which served as the control. All subjects were screened for HIV type 1 and type 2 using standard test kits. Total and differential white blood cell counts were determined using a haematology auto analyzer while the total lymphocyte count (TLC) was obtained by multiplying total white blood cell count (TWC) with percentage lymphocyte count. The CD4 and CD8 cell counts were analyzed using the automated flow cytometry analyzer while the CD4:CD8 cell count ratio was obtained by dividing the CD4 cell count value by that of CD8. The result of the study shows a statistically significant decrease in CD4 and CD8 cell counts, lymphocyte and total lymphocyte counts and an increase in neutrophil count in all the trimesters of pregnancy when compared to the non-pregnant control (p&lt;0.05). Also, there was a significant increase in WBC during the third trimester and a similar decrease in monocyte count in the first and third trimesters of pregnancy. The evidence from the present study concludes that pregnancy modifies the maternal immune response to ensure fetal survival and the protection of the mother from invading pathogens as reported in the increase in total WBC, neutrophil and monocyte counts and a reduction in TLC, CD4 and CD8 counts. The study recommends routine assessments of these crucial cellular immune markers for pregnant women during antenatal visits.
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Hebbar, Shripad, Mehak Misha, and Lavanya Rai. "Significance of Maternal and Cord Blood Nucleated Red Blood Cell Count in Pregnancies Complicated by Preeclampsia." Journal of Pregnancy 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/496416.
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Objectives.To evaluate the effect of preeclampsia on the cord blood and maternal NRBC count and to correlate NRBC count and neonatal outcome in preeclampsia and control groups.Study Design.This is a prospective case control observational study.Patients and Methods.Maternal and cord blood NRBC counts were studied in 50 preeclamptic women and 50 healthy pregnant women. Using automated cell counter total leucocyte count was obtained and peripheral smear was prepared to obtain NRBC count. Corrected WBC count and NRBC count/100 leucocytes in maternal venous blood and in cord blood were compared between the 2 groups.Results.No significant differences were found in corrected WBC count in maternal and cord blood in cases and controls. Significant differences were found in mean cord blood NRBC count in preeclampsia and control groups (40.0±85.1and5.9±6.3,P=0.006). The mean maternal NRBC count in two groups was2.4±9.0and0.8±1.5, respectively (P=0.214). Cord blood NRBC count cut off value ≤13 could rule out adverse neonatal outcome with a sensitivity of 63% and specificity of 89%.Conclusion.Cord blood NRBC are significantly raised in preeclampsia. Neonates with elevated cord blood NRBC counts are more likely to have IUGR, low birth weight, neonatal ICU admission, respiratory distress syndrome, and assisted ventilation. Below the count of 13/100 leucocytes, adverse neonatal outcome is quite less likely.
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Campbell, Peter J., Cathy MacLean, Philip A. Beer, et al. "Correlation of blood counts with vascular complications in essential thrombocythemia: analysis of the prospective PT1 cohort." Blood 120, no. 7 (2012): 1409–11. http://dx.doi.org/10.1182/blood-2012-04-424911.
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Abstract Essential thrombocythemia, a myeloproliferative neoplasm, is associated with increased platelet count and risk of thrombosis or hemorrhage. Cytoreductive therapy aims to normalize platelet counts despite there being only a minimal association between platelet count and complication rates. Evidence is increasing for a correlation between WBC count and thrombosis, but prospective data are lacking. In the present study, we investigated the relationship between vascular complications and 21 887 longitudinal blood counts in a prospective, multicenter cohort of 776 essential thrombocythemia patients. After correction for confounding variables, no association was seen between blood counts at diagnosis and future complications. However, platelet count outside of the normal range during follow-up was associated with an immediate risk of major hemorrhage (P = .0005) but not thrombosis (P = .7). Elevated WBC count during follow-up was correlated with thrombosis (P = .05) and major hemorrhage (P = .01). These data imply that the aim of cytoreduction in essential thrombocythemia should be to keep the platelet count, and arguably the WBC count, within the normal range. This study is registered at the International Standard Randomized Controlled Trials Number Registry (www.isrctn.org) as number 72251782.
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Myers, Regina M., and Michael A. Pulsipher. "Low counts count after CAR-T for ALL." Blood 145, no. 11 (2025): 1100–1102. https://doi.org/10.1182/blood.2024027489.
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Homburg, Annika, Christian H. Weiß, Layth C. Alwan, Gabriel Frahm, and Rainer Göb. "Evaluating Approximate Point Forecasting of Count Processes." Econometrics 7, no. 3 (2019): 30. http://dx.doi.org/10.3390/econometrics7030030.
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In forecasting count processes, practitioners often ignore the discreteness of counts and compute forecasts based on Gaussian approximations instead. For both central and non-central point forecasts, and for various types of count processes, the performance of such approximate point forecasts is analyzed. The considered data-generating processes include different autoregressive schemes with varying model orders, count models with overdispersion or zero inflation, counts with a bounded range, and counts exhibiting trend or seasonality. We conclude that Gaussian forecast approximations should be avoided.
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Beck, E. J., E. J. Kupek, M. M. Gompels, and A. J. Pinching. "Correlation between total and CD4 lymphocyte counts in HIV infection: not making the good an enemy of the not so perfect." International Journal of STD & AIDS 7, no. 6 (1996): 422–28. http://dx.doi.org/10.1258/0956462961918392.
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The aim of this study was to assess the correlation and average cost of total lymphocyte count compared with CD4 count as a broad estimate of immunosuppression in HIV-1 infected individuals. Spearman's partial rank correlation were calculated between total lymphocyte count, absolute CD4 count and CD4 per cent stratified by stage of HIV-1 infection for routinely collected samples. Data were collected prospectively from a T cell-subset register combined with clinical data obtained retrospectively from case notes of HIV-infected patients managed at St Mary's Hospital, London 1982-1991. Costing data were obtained through a survey of the departments of haematology and immunology 1989 90 prices . The correlation between 1534 paired absolute lymphocyte count and CD4 lymphocyte count was found to be high R 0.76 . When analysed by stage of HIV infection, the correlation increased from R 0.64 for asymptomatic patients, to R 0.72 for patients with symptomatic non-AIDS HIV infection and R 0.73 for AIDS patients. Correlations between absolute lymphocyte count and CD4 per cent were considerably weaker: R 0.41 all paired counts; R 0.32 for asymptomatic patients; R 0.25 for symptomatic non-AIDS patients; R 0.32 for AIDS patients. Average cost was 8 per full blood count compared with 38 per T-cell subset analysis. The high correlation between total and CD4 lymphocyte counts, especially for patients with symptomatic HIV disease, demonstrates the suitability of the use of total lymphocyte count in the absence of CD4 counts. Given the considerably lower prices of total lymphocyte counts compared with T-cell subset analysis, this is particularly relevant for developing countries.
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Muhammad Iqbal Javaid, Masuma Ghazanfar, and Fatima Rehman. "TOTAL LYMPHOCYTE COUNT AS AN ALTERNATIVE TO CD4 COUNT IN MANAGMENT OF HIV/AIDS PATIENTS." Pakistan Postgraduate Medical Journal 35, no. 02 (2024): 73–76. https://doi.org/10.51642/ppmj.v35i02.602.
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Background: Initiation and monitoring of ART are based on CD4+ count which is however, costly and often inaccessible in resource restricted communities. TLC (total lymphocyte count) has been advocated over the years as a marker for progression of HIV. The aim of the study was to find relationship between CD4 count and TLC and to determine whether TLC can be used as a surrogate marker for CD4 counts. Methods: Descriptive/Cross-sectional study was conducted at department of Pathology Allama Iqbal Medical College Lahore. A total of 106 HIV subjects were included. Blood samples were analyzed for TLC and CD4 counts. Pearson’s correlation between TLC and CD4 count was evaluated. Receiving Operating Characteristic (ROC) was used to calculate sensitivity, specificity, positive and negative predictive values for various cut-off points of TLC to predict CD4 count ≥500/µl, 200–499/µl, <350/µl and < 200/µl. Results: A TLC of ≤1400/µl had a maximum sensitivity of 83.3% and specificity 71.1% for predicting CD4 cell count of < 200/µl. The best TLC cut-off for predicting CD4 count <350/µl with a maximum sensitivity of 81.5% and specificity 76.4% was ≤2200 /µl. A CD4 count ≥500/µl was predicted with maximal sensitivity of 88% and specificity of 73.2% at TLC cut-off >2200 /µl. A positive Pearson’s correlation coefficient (r) of 0.6623 (p < 0.0001) was noted when TLC and CD4 count were analysed. Area Under Curve of different groups was high (close to 1) that makes TLC an ideal alternate to CD4 count. Conclusion: We suggest cut-off TLC ≤1400/μl for anticipating CD4 counts < 200/μl to initiate ART in resource-poor settings. Key Words: CD4 count, Total lymphocyte count, HIV
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Nassif, Hani, Kaan Ozbay, and Sami Demiroluk. "Mapping of truck traffic in New Jersey using weigh-in-motion data." IET Intelligent Transport Systems 12, no. 9 (2018): 1053–61. https://doi.org/10.1049/iet-its.2018.0055.
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This study presents an innovative hierarchical Bayesian model for mapping of county level truck traffic in New Jersey. First, the model is estimated using truck counts. Then, using overweight truck counts from weigh-in-motion data as the response variable, the model is re-estimated. The goal in using the overweight trucks in the spatial model is to demonstrate the importance of representing their spatial variation due to their impact on the life of the roadway network elements. Finally, truck count maps are developed based on modelling results to visualise the effects of spatial covariates. The results of the study indicate that the most influential covariate for the truck traffic is the length of interstate roadways, followed by employment and population. The developed truck count maps can help transportation professionals on identifying and ranking the locations at an aggregate level, which requires closer attention.
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Chen, Yen-Chun, Te-Sheng Chang, Chien-Hung Chen, et al. "Factors Associated with Significant Platelet Count Improvement in Thrombocytopenic Chronic Hepatitis C Patients Receiving Direct-Acting Antivirals." Viruses 14, no. 2 (2022): 333. http://dx.doi.org/10.3390/v14020333.
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To clarify the predictive factors of significant platelet count improvement in thrombocytopenic chronic hepatitis C (CHC) patients. CHC patients with baseline platelet counts of <150 × 103/μL receiving direct-acting antiviral (DAA) therapy with at least 12-weeks post-treatment follow-up (PTW12) were enrolled. Significant platelet count improvement was defined as a ≥10% increase in platelet counts at PTW12 from baseline. Platelet count evolution at treatment week 4, end-of-treatment, PTW12, and PTW48 was evaluated. This study included 4922 patients. Sustained virologic response after 12 weeks post-treatment was achieved in 98.7% of patients. Platelet counts from baseline, treatment week 4, and end-of-treatment to PTW12 were 108.8 ± 30.2, 121.9 ± 41.1, 123.1 ± 43.0, and 121.1 ± 40.8 × 103/μL, respectively. Overall, 2230 patients (45.3%) showed significant platelet count improvement. Multivariable analysis revealed that age (odds ratio (OR) = 0.99, 95% confidence interval (CI): 0.99–1.00, p = 0.01), diabetes mellitus (DM) (OR = 1.20, 95% CI: 1.06–1.38, p = 0.007), cirrhosis (OR = 0.66, 95% CI: 0.58–0.75, p < 0.0001), baseline platelet counts (OR = 0.99, 95% CI: 0.98–0.99, p < 0.0001), and baseline total bilirubin level (OR = 0.80, 95% CI: 0.71–0.91, p = 0.0003) were independent predictive factors of significant platelet count improvement. Subgroup analyses showed that patients with significant platelet count improvement and sustained virologic responses, regardless of advanced fibrosis, had a significant increase in platelet counts from baseline to treatment week 4, end-of-treatment, PTW12, and PTW48. Young age, presence of DM, absence of cirrhosis, reduced baseline platelet counts, and reduced baseline total bilirubin levels were associated with significant platelet count improvement after DAA therapy in thrombocytopenic CHC patients.
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Balak, Dashika A., Karen Bissell, Christine Roseveare, Sharan Ram, Rachel R. Devi, and Stephen M. Graham. "Absolute Lymphocyte Count Is Not a Suitable Alternative to CD4 Count for Determining Initiation of Antiretroviral Therapy in Fiji." Journal of Tropical Medicine 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/715363.
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Introduction. An absolute lymphocyte count is commonly used as an alternative to a CD4 count to determine initiation of antiretroviral therapy for HIV-infected individuals in Fiji when a CD4 count is unavailable.Methods. We conducted a retrospective analysis of laboratory results of HIV-infected individuals registered at all HIV clinics in Fiji.Results. Paired absolute lymphocyte and CD4 counts were available for 101 HIV-infected individuals, and 96% had a CD4 count of ≤500 cells/mm3. Correlation between the counts in individuals was poor (Spearman rank correlationr=0.5). No absolute lymphocyte count could be determined in this population as a suitable surrogate for a CD4 count of either 350 cells/mm3 or 500 cells/mm3. The currently used absolute lymphocyte count of ≤2300 cells/μL had a positive predictive value of 87% but a negative predictive value of only 17% for a CD4 of ≤350 cells/mm3and if used as a surrogate for a CD4 of ≤500 cells/mm3it would result in all HIV-infected individuals receiving ART including those not yet eligible. Weight, CD4 count, and absolute lymphocyte count increased significantly at 3 months following ART initiation.Conclusions. Our findings do not support the use of absolute lymphocyte count to determine antiretroviral therapy initiation in Fiji.
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Tuydes-Yaman, Hediye, Oruc Altintasi, and Nuri Sendil. "Better estimation of origin–destination matrix using automated intersection movement count data." Canadian Journal of Civil Engineering 42, no. 7 (2015): 490–502. http://dx.doi.org/10.1139/cjce-2014-0555.
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Intersection movements carry more disaggregate information about origin–destination (O–D) flows than link counts in a traffic network. In this paper, a mathematical formulation is presented for O–D matrix estimation using intersection counts, which is based on an existing linear programming model employing link counts. The proposed model estimates static O–D flows for uncongested networks assuming no a priori information on the O–D matrix. Both models were tested in two hypothetical networks previously used in O–D matrix studies to monitor their performances assuming various numbers of count location and measurement errors. Two new measures were proposed to evaluate the model characteristics of O–D flow estimation using traffic counts. While both link count based and intersection count based models performed with the same success under complete data collection assumption, intersection count based formulation estimated the O–D flows more successfully under decreasing number of observation locations. Also, the results of the 30 measurement error scenarios revealed that it performs more robustly than the link count based one; thus, it better estimates the O–D flows.
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Westcott, David, and Adam McKeown. "Observer error in exit counts of flying-foxes (Pteropus spp.)." Wildlife Research 31, no. 5 (2004): 551. http://dx.doi.org/10.1071/wr03091.
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Population estimation and monitoring is a fundamental component in the conservation management of any species. For species such as flying-foxes (Pteropus spp.) population estimation is complicated by the large number of animals involved, their mobility and the conditions under which counts are conducted. Because count results are used in the determination of management requirements, they are the focus of much critical attention. Despite this, while measures of the precision of fly-out counts of Pteropus spp. have been published, measures of their accuracy have not. In this paper we present an assessment of the accuracy and precision of observer counts of dusk fly-outs by comparing recordings of observers’ counts with a video of the same fly-out. Observer’s counts were significantly related to the video-count (rs = 0.69, P < 0.0001), with the average observer’s count underestimating the video-count by 14.7% (± 25, s.d.) of the video-count. Observers’ errors increased with the rate at which flying-foxes left the camp and with the width of the fly-out stream. These results suggest that while observers’ errors are inherent in dusk fly-out counts, these errors are manageable and relatively predictable. Other sources of error are likely to have a greater impact on the final population estimate at both camp and regional scales.
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Yang, Jing, Xiaojun Lu, Tokuhiro Okada, et al. "Effects of biological variations on platelet count in healthy subjects in China." Thrombosis and Haemostasis 91, no. 02 (2004): 367–72. http://dx.doi.org/10.1160/th03-05-0276.
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SummaryThe effects of biological variations on platelet counts were investigated in 694 healthy subjects aged 18 to 60 years living in three cities including Chengdu (Sichuan Province), Suzhou (Jiangsu Province) and Harbin (Heilongjang Province) in China. Platelet counts in healthy subjects were significantly lower in Chengdu (52∼202 X 109/L) and Suzhou (60∼259 X 109/L) than in Harbin (154∼348 X 109/L)(p <0.0001), but the mean platelet volume (MPV) determined concurrently was negatively correlated with platelet count, the MPV values were significantly higher in Chengdu (11.8∼15.6 fl) and Suzhou (10.9∼15.8 fl) than in Harbin (9.5∼12.9 fl) (p < 0.0001). Platelet counts were significantly higher in summer (73∼289 X 109/L) than in winter (52∼202 X 109/L) (p <0.0001), but the MPV values were lower in summer (11.2∼14.7 fl) than in winter (11.8∼15.6 fl) (p <0.05) in Chengdu. Platelet associated immunoglobulin (PA-IgG) in Chengdu was revealed to be significantly higher in the low platelet count group (<150 X 109/L, 13.5 ± 7.1 ng/107 PLT) than in the normal platelet count group (≥150 X 109/L, 8.3 ± 2.7 ng/107 PLT)(p <0.0001). Similar results were observed in Suzhou for the reticulated platelet ratio, which was significantly higher in the low platelet count group (19.5 ± 7.1%) than in the normal platelet count group (11.6 ± 2.7%)(p <0.01). The bleeding time in Chengdu showed a significantly longer time in the low platelet count group (8.6 ± 2.3 min) than in the normal platelet count group (6.0 ± 1.2 min)(p <0.01). With regard to the effects of lipids on platelet counts, the HDL values were significantly higher in the normal platelet count group (1.60 ± 0.76 mmol/L) than the low platelet count group (1.23 ± 0.31 mmol/L) (p <0.01); but no significant differences in cholesterol and triglycerides values between the normal and low platelet count groups (p >0.05) were recorded. These findings suggest that the platelet counts could be greatly influenced in healthy subjects by biological variations such as geographical, seasonal, and lipid variations.
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BAZSO, ANNA, ALESSANDRO CONSOLARO, NICOLINO RUPERTO, et al. "Development and Testing of Reduced Joint Counts in Juvenile Idiopathic Arthritis." Journal of Rheumatology 36, no. 1 (2009): 183–90. http://dx.doi.org/10.3899/jrheum.080432.
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ObjectiveTo develop and test reduced joint counts in children with juvenile idiopathic arthritis (JIA).MethodsFour reduced joint counts including 45, 35, 27, and 10 joints were devised by a panel of experienced pediatric rheumatologists, who selected the joints to be included based on the ease of technical assessment, functional relevance, and frequency of involvement. Three large samples of patients with JIA (total n = 4353) who had a detailed joint assessment available were used to develop and test reduced joint counts. Performance of reduced counts was examined by comparing their Spearman correlation with the standard (i.e., complete) joint count. Construct validity was evaluated by calculating Spearman correlation with other JIA outcome measures. Responsiveness to clinical change was determined through the standardized response mean (SRM).ResultsSpearman correlations of reduced joint counts with the whole joint count and with the other JIA outcome measures were comparable, revealing that they had similar ability to serve as surrogate for the whole joint count and construct validity. Responsiveness to clinical change was also comparable across reduced counts (SRM 0.83–1.09 for active joint counts and 0.63–0.81 for restricted joint counts). Based on these results and considering the relative feasibility of the different counts, the 27-joint reduced count is proposed for use in JIA. This joint count includes the cervical spine and the elbow, wrist, metacarpophalangeal (from first to third), proximal interphalangeal, hip, knee, and ankle joints.ConclusionReduced joint counts appear to be as reliable as standard joint counts in assessment of the severity of joint disease and its change over time in children with JIA.
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RIVAS, TERESA, JUAN A. VIZCAÍNO, and FRANCISCO J. HERRERA. "Microbial Contamination of Carcasses and Equipment from an Iberian Pig Slaughterhouse." Journal of Food Protection 63, no. 12 (2000): 1670–75. http://dx.doi.org/10.4315/0362-028x-63.12.1670.
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The microbial contamination of carcasses and equipment has been studied in an industrial slaughterhouse of Iberian pigs. Samples of the surface of carcasses were taken at different stages of the process and aerobic plate count at 37°C (APC), Enterobacteriaceae-count (E-count) and Escherichia coli-count (EC-count) were determined. It was demonstrated that in scalding and singeing the APC decreased (P &lt; 0.01), while in the dehairing it increased (P &lt; 0.01). The E-count and EC-count decreased in the scalding but increased in the evisceration (P &lt; 0.001). The implementation of good manufacturing practices (GMP) in the stages of closure of the anus and evisceration significantly decreased the EC-count. It changed from 61.1% in carcasses without GMP that had counts higher than 1 log CFU/cm2 to only 7.4% in GMP carcasses. A final wash of the carcasses with potable water at high pressure (the only decontaminating treatment permitted in the European Union) was tested and failed to decrease the counts. It was also demonstrated that cleaning and disinfection of the dehairing and scraping machines is not effective.
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Gitau, George, Daniel Muasya, Willy Mwangi, et al. "Risk factors associated with camel milk total coliform and total viable bacterial count along the camel milk value chain in Isiolo County, Kenya." Journal of Research in Veterinary Sciences 5, no. 1 (2025): 29. https://doi.org/10.5455/jrvs.20241215111750.
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Abstract Background and Aim: The camel is an important livestock in the semi-arid, arid and desert regions. The study was carried out to determine the level of bacterial contamination and factors associated with total bacterial count and coliform contamination along the camel milk chain in Isiolo County, Kenya. Materials and Methods: A cross-sectional study was carried out between February and March 2024 and milk samples were collected along the milk value chain. Milk samples were collected from farmers, transporters, milk bulkers, and retailers. The samples were assessed for total viable bacterial counts (TVBC) and total coliform counts (TCC), on the plate count agar and violet lactose bile agar. Results: A total of 191 samples were collected, 42.93% from producers, 24.08% from traders, 19.9% from bulkers, and 13.09% from transporters. Total Viable Count (TVC) showed that 34.55% of samples had moderate contamination (between 10³ CFU/ml and 10⁵ CFU/ml), while 23.04% exhibited severe contamination levels (above 10⁶ CFU/ml). For Violet Red Bile Agar (VRBA) testing, 46.60% of the samples exceeded the threshold of 1000 CFU/ml of milk, indicating significant bacterial contamination, while 29.84% showed no bacterial growth. Logistic regression identified factors associated with increased contamination as female respondents, urban location, and use of disinfectants. Conclusion: The study showed that there was moderate to heavy bacterial milk contamination on about 50% of the milk samples tested along the camel milk value chain. Key words: Camel, milk, total viable bacterial counts, total coliform counts, value chain, hygiene practices, contamination risk factors, Kenya
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Badejo, Oluwatosin A., Chung-Chou Chang, Kaku A. So-Armah, et al. "CD8+T-Cells Count in Acute Myocardial Infarction in HIV Disease in a Predominantly Male Cohort." BioMed Research International 2015 (2015): 1–5. http://dx.doi.org/10.1155/2015/246870.
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Human Immunodeficiency Virus- (HIV-) infected persons have a higher risk for acute myocardial infarction (AMI) than HIV-uninfected persons. Earlier studies suggest that HIV viral load, CD4+T-cell count, and antiretroviral therapy are associated with cardiovascular disease (CVD) risk. Whether CD8+T-cell count is associated with CVD risk is not clear. We investigated the association between CD8+T-cell count and incident AMI in a cohort of 73,398 people (of which 97.3% were men) enrolled in the U.S. Veterans Aging Cohort Study-Virtual Cohort (VACS-VC). Compared to uninfected people, HIV-infected people with high baseline CD8+T-cell counts (>1065 cells/mm3) had increased AMI risk (adjustedHR=1.82, P<0.001, 95% CI: 1.46 to 2.28). There was evidence that the effect of CD8+T-cell tertiles on AMI risk differed by CD4+T-cell level: compared to uninfected people, HIV-infected people with CD4+T-cell counts ≥200 cells/mm3had increased AMI risk with high CD8+T-cell count, while those with CD4+T-cell counts <200 cells/mm3had increased AMI risk with low CD8+T-cell count. CD8+T-cell counts may add additional AMI risk stratification information beyond that provided by CD4+T-cell counts alone.
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Aygün, Demet, and Hüseyin Doğu. "Evaluation of hematologic inflammation parameters and cranial magnetic resonance imaging findings in patients with trigeminal neuralgia." Journal of Health Sciences and Medicine 8, no. 2 (2025): 197–203. https://doi.org/10.32322/jhsm.1556900.
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Aims: This study aimed to evaluate the relationship between trigeminal neuralgia (TN) and hematological parameters, including leukocyte-based inflammatory indices, and to explore their association with cranial magnetic resonance imaging (MRI) findings. Methods: A retrospective analysis was conducted on 114 patients with newly diagnosed TN and 114 healthy control groups with comparable demographic characteristics. Clinical, laboratory, and cranial MRI data were collected from hospital records. White matter abnormalities were identified via cranial MRI, and inflammatory indices were calculated as follows: neutrophil-to-lymphocyte ratio (NLR)=Neutrophil count/lymphocyte count, platelet-to-lymphocyte ratio (PLR)=Platelet count/lymphocyte count, Systemic Immune-Inflammation Index (SII)=Platelet count×neutrophil count/lymphocyte count, and Systemic Inflammatory Response Index (SIRI)=Neutrophil count×monocyte count/lymphocyte count. Results: TN patients showed significantly higher leukocyte counts (7.4±1.8 vs. 6.0±1.9 ×10³/μl, p
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Day, N. B., B. J. Skura, and W. D. Powrie. "Comparison of three media used for the enumeration of heat-injured Botrytis cinerea." Canadian Journal of Microbiology 34, no. 2 (1988): 194–96. http://dx.doi.org/10.1139/m88-036.
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The efficacy of three media (antibiotic-supplemented plate count agar (3 days, 21 °C); antibiotic–pyruvate–supplemented plate count agar (3 days, 21 °C); and trypticase soy agar (16 h, followed by 2.5 days on antibiotic-supplemented plate count agar, 21 °C)) for recovery of heat-injured Botrytis cinerea spores was compared using hydrophobic grid membrane filters. The filters restrict spreading of fungal colonies and facilitate the transfer of fungal spores from pre-enrichment trypticase soy agar to antibiotic-supplemented plate count agar. Counts obtained from pre-enrichment on trypticase soy agar were significantly larger than counts obtained from the other media (α = 0.05). Addition of sodium pyruvate to antibiotic-supplemented plate count agar did not increase spore recovery (α = 0.05). The use of trypticase soy agar as a pre-enrichment medium should be considered for use when antibiotic-supplemented plate count agar is employed in the enumeration of heat-stressed fungi.
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Hanprathet, Nitt, Somrat Lertmaharit, Vitool Lohsoonthorn, Thanapoom Rattananupong, Palanee Ammaranond, and Wiroj Jiamjarasrangsi. "Shift Work and Leukocyte Count Changes among Workers in Bangkok." Annals of Work Exposures and Health 63, no. 6 (2019): 689–700. http://dx.doi.org/10.1093/annweh/wxz039.
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Abstract Objectives Previous epidemiological evidence for the association of shift work exposure and increased leukocyte count is cross-sectional in nature, thus limiting cause-effect inference. We therefore used a longitudinal design to: (i) compare leukocyte counts at baseline between shift and day workers and (ii) examine the time trend of leukocyte counts over the follow-up period for these workers. Methods A retrospective cohort study was conducted among 6737 workers aged <60 years at two large organizations (a humanitarian organization and a university) in Bangkok, Thailand who had participated in at least two annual health check-ups during the period 2005–2016. Shift work exposure history was assessed by a self-administered questionnaire and categorized into day, former, and current shift workers. Data on leukocyte count were collected annually as part of worksite health screening during the observation period. Association of shift work exposure and increased leukocyte count was then examined cross-sectionally and longitudinally by using multiple linear regression and multilevel analysis of repeated measures data, respectively. In addition, trends for leukocyte count over the follow-up period and work years were examined using LOWESS smooth curves. Results Compared to day work, the current shift work was associated with increased leukocyte counts. The magnitude of percentage increase was the highest for basophil counts, followed by eosinophil and lymphocyte counts. Both cross-sectional and longitudinal evidence revealed this association, although it was less pronounced longitudinally. For total leukocyte count, the magnitude of difference was constant across the 11-year follow-up period. However, for lymphocyte and basophil counts, these discrepancies tapered over the work years until they no longer differed (for lymphocyte count) or even differed in the opposite direction (for basophil count) in later work years. Conclusion This study confirmed previous cross-sectional evidence that shift work exposure-increased leukocyte counts and that this was reversible. Whether this increase in immune cell count also results in an increased immune cell activity and serves as the intermediary in the association between shift work exposure and subsequent chronic disease development needs further investigation.
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Kaupke, C. J., G. C. Butler, and N. D. Vaziri. "Effect of recombinant human erythropoietin on platelet production in dialysis patients." Journal of the American Society of Nephrology 3, no. 10 (1993): 1672–79. http://dx.doi.org/10.1681/asn.v3101672.
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Two hundred forty-four anemic hemodialysis patients were randomized into recombinant erythropoietin and placebo-treated groups during a 12-wk double-blind phase, followed by a 24-wk open-label period. Mean platelet count rose from the baseline value of 242 x 10(9)/L to 264 x 10(9)/L on day 5 of epoetin therapy (P < 0.001, paired t test). Mean platelet count peaked at 290 x 10(9)/L on day 40 and remained at a significantly elevated level below the peak thereafter. The peak platelet count did not exceed the normal range in a majority of cases. Platelet count was unaffected by placebo. Patients without an erythropoietic response during the first few weeks of therapy exhibited a rise in platelet count comparable to that in patients with a satisfactory erythropoiesis. Patients with low initial serum ferritin concentrations had baseline platelet counts comparable to those with normal or high ferritin values and showed a similar rise in platelet count during therapy. As a group, patients with baseline platelet counts above 400 x 10(9)/L showed no rise in platelet count, whereas those with normal or reduced platelet counts showed a marked thrombopoietic response to epoetin. Erythropoietin therapy did not significantly alter the incidence of blood access thrombosis when compared with placebo treatment.
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Ahluwalia, Pal, and Toby Miller. "To count or not to count?" Social Identities 21, no. 5 (2015): 423–24. http://dx.doi.org/10.1080/13504630.2015.1100055.
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Friedman, Lee. "Why vote-count reviews don’t count." Biological Psychiatry 49, no. 2 (2001): 161–62. http://dx.doi.org/10.1016/s0006-3223(00)01075-1.
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Vagelas, Ioannis. "Analysis of Over-Dispersed Count Data: Application to Obligate Parasite Pasteuria Penetrans." WSEAS TRANSACTIONS ON ENVIRONMENT AND DEVELOPMENT 18 (March 1, 2022): 333–39. http://dx.doi.org/10.37394/232015.2022.18.33.
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In this article we present with STATA regression models suitable for analyzing over-dispersed count outcomes. Specifically, the Negative Binomial regression can be an appropriate choice for modeling count variables, usually for over-dispersed count outcome variables. The common problem with count data with zeroes is that the empirical data often show more zeroes than would be expected under either Poisson or the Negative Binomial model. We concluded, this publications showcases that Zero-inflated models can be used to model count data that has excessive zero counts.
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Azarabadi, Javid Mohammadzadeh, and Neveen Shalalfa. "Association between leukocyte-based inflammatory indices and bone mineral density in hemodialysis patients." Journal of Medicine and Palliative Care 6, no. 2 (2025): 131–37. https://doi.org/10.47582/jompac.1642972.
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Aims: Osteoporosis and osteopenia are common among hemodialysis (HD) patients, yet current methods for risk stratification remain limited. This study aimed to investigate the relationship between leukocyte-based inflammatory indices and osteoporosis and osteopenia in HD patients and to assess their diagnostic performance in differentiating these conditions. Methods: A retrospective analysis was conducted on 168 HD patients classified into normal bone mineral density (BMD) (n=43), osteopenia (n=70), and osteoporosis (n=55) based on T-scores by dual-energy X-ray absorptiometry measurements. The leukocyte-based inflammatory indices were calculated as follows: Platelet to lymphocyte ratio (PLR)=platelet count/ lymphocyte count ratio; neutrophil o lymphocyte ratio (NLR)=neutrophil count/ lymphocyte count ratio; systemic immune inflammation index (SII)=platelet count×neutrophil count / lymphocyte count ratio, and systemic inflammation response index (SIRI)=neutrophil count×monocyte count/ lymphocyte count ratio. Results: Osteopenia and osteoporosis were identified in 41.7% and 32.7% of patients, respectively. Patients with osteoporosis exhibited higher neutrophil and monocyte counts and lower lymphocyte count (p
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Arlt, Nicole, Remo Rothe, and Rainer Moog. "Validation of blood counters for quality control of platelet concentrates with high platelet counts." Journal of Laboratory Medicine 42, no. 5 (2018): 201–4. https://doi.org/10.1515/labmed-2018-0306.
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Abstract Background Blood counters are primarily used to measure peripheral blood cells including platelets (PLTs). In routine quality control of platelet concentrates (PCs), counters are also used to analyze very high PLT counts. To meet the requirements of national and European guidelines for quality assurance, the accuracy of counting very high PLT counts has to be validated. The aim of the present study was to validate four blood counters (one of which has two detection methods) focusing on the PLT count. Methods The comparison was performed with PCs using the blood counter devices CELL-DYN Ruby (optical count) and CELL-DYN Emerald (impedance count), Sysmex K-4500 (impedance count), Sysmex XN-550 (impedance count) and Sysmex XN-550 (optical count). For precision performances, samples were measured serially 5 times and the coefficients of variation were calculated and compared with manufacturers’ requirements. Additionally, 50 peripheral blood samples were analyzed and standard hemogram parameters (red blood cells [RBC], white blood cells [WBC], hemoglobin [HGB], hematocrit [HCT], PLTs) were compared. Results The comparison showed significant differences between the studied blood counter devices in measuring high PLT counts. The CELL-DYN-Emerald, the Sysmex K-4500 and Sysmex XN-500 with the optical counting method measured significantly higher PLT counts compared to the CELL-DYN-Ruby and the Sysmex XN-500 with the impedance counting technology (p<0.0001) independent of their principle of measurement. The manufacturers provide comparable coefficients of variation. We achieved similar results for all counters. All results of the peripheral blood count parameters were comparable. Conclusions Our study showed the importance of blood counter validations focusing on PCs with high PLT counts before routine use. Not only the generally fundamental method, but also the manufacturers’ peculiarities seem to play an important role.
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Zhang, Wenhui, Mani Sotoodeh, Joyce C. Ho, Roy L. Simpson, and Vicki S. Hertzberg. "Examining the Concordance in the Documented Pressure Injury Site, Stage, and Count in Medical Information Mart for Intensive Care-III." Applied Clinical Informatics 12, no. 04 (2021): 897–909. http://dx.doi.org/10.1055/s-0041-1735179.
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Abstract Objectives This study aimed to compare the concordance of pressure injury (PI) site, stage, and count documented in electronic health records (EHRs); explore if PI count during each patient hospitalization is consistent based on PI site or stage count in the diagnosis or chart event records; and examine if discrepancies in PI count were associated with patient characteristics. Methods Hospitalization records with the International Classification of Diseases ninth edition (ICD-9) codes, chart events from two systems (CareVue, MetaVision), and clinical notes on PI were extracted from the Medical Information Mart for Intensive Care (MIMIC)-III database. PI site and stage counts from individual hospitalization were computed. Hospitalizations with the same or different counts of site and stage according to ICD-9 codes (site and stage), CareVue (site and stage), or MetaVision (stage) charts were defined as consistent or discrepant reporting. Chi-squared, independent t-, and Kruskal–Wallis tests were examined if the count discrepancy was associated with patient characteristics. ICD-9 codes and charts were also compared for people with one site or stage. Results A total of 31,918 hospitalizations had PI data. Within hospitalizations with ICD-9-coded sites and stages, 55.9% reported different counts. Within hospitalizations with CareVue charts on PI, 99.3% reported the same count. For hospitalizations with stages based on ICD-9 codes or MetaVision chart data, only 42.9% reported the same count. Discrepancies in counts were consistently and significantly associated with variables including PI recording in clinical notes, dead/hospice at discharge, more caregivers, longer hospitalization or intensive care unit stays, and more days to first transfer. Discrepancies between ICD-9 code and chart values on the site and stage were also reported. Conclusion Patient characteristics associated with PI count discrepancies identified patients at risk of having discrepant PI counts or worse outcomes. PI documentation quality could be improved with better communication, care continuity, and integrity. Clinical research using EHRs should adopt systematic data quality analysis to inform limitations.
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Mongirdienė, Aušra, Jolanta Laukaitienė, Vilius Skipskis, Lolita Kuršvietienė, and Julius Liobikas. "The Difference of Cholesterol, Platelet and Cortisol Levels in Patients Diagnosed with Chronic Heart Failure with Reduced Ejection Fraction Groups According to Neutrophil Count." Medicina 57, no. 6 (2021): 557. http://dx.doi.org/10.3390/medicina57060557.
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Background and Objectives: It is known that neutrophils are involved in the pro-inflammatory processes and thus, can have a great impact on the pathophysiology of heart failure (HF). Moreover, hypercholesterolemia heightens neutrophil production, thereby accelerating cardiovascular inflammation. However, there is a lack of information about the relation of low inflammation to the state of stress, hypercholesterolemia, and pro-thrombotic statement in patients with chronic HF. Therefore, we aimed to determine whether platelet, cholesterol and cortisol levels differ in a different inflammatory condition groups according to the neutrophil count in patients diagnosed with CHF with reduced ejection fraction (CHFrEF), and whether there is a correlation between those readings. Materials and Methods: The average of neutrophil count was 4.37 × 109 L; therefore, 180 patients were separated into two groups: one with relatively a higher inflammatory environment (neutrophil count ≥ 4.37 × 109 L (n = 97)) and one with a relatively lower inflammatory environment (neutrophil count < 4.38 × 109 L (n = 83)). We also determined the levels of lymphocytes, monocytes, platelet count (PLT), mean platelet volume (MPV), platelet aggregation, the levels of cortisol and cholesterol and the concentrations of C reactive protein (CRP) and fibrinogen. Results: We found that CRP, fibrinogen and cortisol concentrations were statistically significantly higher in the group with higher neutrophil counts. However, there were no differences among cholesterol concentration and other markers of platelet function between the groups. We also showed that PLT, leukocyte and monocyte counts were higher in the group with a higher neutrophil count, and the PLT correlated with other cell type count and CRP. In addition, the neutrophil count correlated with concentrations of fibrinogen, evening cortisol and CRP. Conclusions: Cortisol, fibrinogen and CRP levels, PLT and monocyte counts were higher in the CHFrEF patient group with higher neutrophil counts. The cholesterol levels and platelet function readings did not differ between the groups. The neutrophil count correlated with evening cortisol concentration.
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Roth, Jonathan N. "Temperature-Independent Pectin Gel Method for Aerobic Plate Count in Dairy and Nondairy Food Products: Collaborative Study." Journal of AOAC INTERNATIONAL 71, no. 2 (1988): 343–49. http://dx.doi.org/10.1093/jaoac/71.2.343.
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Abstract Ten laboratories participated in a collaborative study to compare the pectin-based plate count (PC) Redigel method with the aerobic plate count and standard plate count agar-based standard methods for the estimation of total bacterial counts in 9 different nondairy food and dairy food products. The foods were cream, homogenized milk, raw milk, cheese, raw chicken, raw oysters, frozen broccoli, flour, and spices. Each laboratory analyzed 6 samples (3 sample pairs) of each food group. Counts obtained by the pectin-based plate count and agarbased plate count methods differed significantly (P 0.05) only for homogenized milk, where the pectin gel method resulted in higher counts. The actual counts were higher in the pectin gel method in 8 of the 9 food groups. The log means for pectin gel and agar-based media, respectively, for the 9 food groups were: cream 8.106 and 7.844; homogenized milk 8.642 and 8.231; raw milk 8.711 and 8.423; chicken 7.654 and 7.645; oysters 7.201 and 7.180; broccoli 7.102 and 6.798; cheese 8.045 and 8.055; flour 4.112 and 3.988; spice 5.379 and 5.314. The repeatability standard deviations favored the pectin gel method in 6 of the 9 foods tested. The reproducibility standard deviations favored the pectin gel method in 7 of the 9 foods tested. These results strongly support the suitability of the pectin gel method as an alternative to agar-based plate count and other methods for total bacterial counts in nondairy and dairy food products. The pectin gel method has been adopted official first action.
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Codding, Brian F., and Simon C. Brewer. "Regression with Archaeological Count Data." Advances in Archaeological Practice 12, no. 2 (2024): 163–72. http://dx.doi.org/10.1017/aap.2024.7.
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AbstractArchaeological data often come in the form of counts. Understanding why counts of artifacts, subsistence remains, or features vary across time and space is central to archaeological inquiry. A central statistical method to model such variation is through regression, yet despite sophisticated advances in computational approaches to archaeology, practitioners do not have a standard approach for building, validating, or interpreting the results of count regression. Drawing on advances in ecology, we outline a framework for evaluating regressions with archaeological count data that includes suggestions for model fitting, diagnostics, and interpreting results. We hope these suggestions provide a foundation for advancing regression with archaeological count data to further our understanding of the past.