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Nevin Manimala Statistics

EggLib 3: a Python package for population genetics and genomics

Mol Ecol Resour. 2022 Jun 26. doi: 10.1111/1755-0998.13672. Online ahead of print.

ABSTRACT

Rapid and repeatable polymorphism analyses have become a necessity with the current amount of genomic data that can be collected in many organisms. Traditionally such analyses are conducted using a variety of tools in combination, often requiring numerous format translation and manipulation. Here we present a massively updated version of our previous software package EggLib, intended to alleviate such costly and error-prone tinkering with the data. EggLib has been streamlined into a Python package and thoroughly updated and optimized to accommodate modern-day sized dataset. We show the main characteristics of the package making it a tool of choice to perform population genetics analyses. Once the data are imported (whatever their encoding), they can be filtered, edited, analyzed and compared to coalescent simulations very easily and efficiently. Furthermore the list of diversity and polymorphism statistics that can now be calculated has been greatly expanded. The software and its full documentation are available at https://egglib.org/.

PMID:35753060 | DOI:10.1111/1755-0998.13672

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Nevin Manimala Statistics

A Bayesian hierarchical model for improving measurement of 5mC and 5hmC levels: Toward revealing associations between phenotypes and methylation states

Genet Epidemiol. 2022 Jun 26. doi: 10.1002/gepi.22489. Online ahead of print.

ABSTRACT

5-hydroxymethylcytosine (5hmC) is a methylation state linked with gene regulation, commonly found in cells of the central nervous system. 5hmC is associated with demethylation of cytosines from 5-methylcytosine (5mC) to the unmethylated state. The presence of 5hmC can be inferred by a paired experiment involving bisulfite and oxidation-bisulfite treatments on the same sample, followed by a methylation assay using a platform such as the Illumina Infinium MethylationEPIC BeadChip (EPIC). Existing methods for analysis of the resulting EPIC data are not ideal. Most approaches ignore the correlation between the two experiments and any imprecision associated with DNA damage from the additional treatment. Estimates of 5mC/5hmC levels free from these limitations are desirable to reveal associations between methylation states and phenotypes. We propose a hierarchical Bayesian method called Constrained HYdroxy Methylation Estimation (CHYME) to simultaneously estimate 5mC/5hmC signals as well as any associations between these signals and covariates or phenotypes, while accounting for the potential impact of DNA damage and dependencies induced by the experimental design. Simulations show that CHYME has valid type 1 error and better power than a range of alternative methods, including the popular OxyBS method and linear models on transformed proportions. Other methods we examined suffer from hugely inflated type 1 error for inference on 5hmC proportions. We use CHYME to explore genome-wide associations between 5mC/5hmC levels and cause of death in postmortem prefrontal cortex brain tissue samples. These analyses indicate that CHYME is a useful tool to reveal phenotypic associations with 5mC/5hmC levels.

PMID:35753057 | DOI:10.1002/gepi.22489

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Nevin Manimala Statistics

Semi-supervised approach to event time annotation using longitudinal electronic health records

Lifetime Data Anal. 2022 Jun 26. doi: 10.1007/s10985-022-09557-5. Online ahead of print.

ABSTRACT

Large clinical datasets derived from insurance claims and electronic health record (EHR) systems are valuable sources for precision medicine research. These datasets can be used to develop models for personalized prediction of risk or treatment response. Efficiently deriving prediction models using real world data, however, faces practical and methodological challenges. Precise information on important clinical outcomes such as time to cancer progression are not readily available in these databases. The true clinical event times typically cannot be approximated well based on simple extracts of billing or procedure codes. Whereas, annotating event times manually is time and resource prohibitive. In this paper, we propose a two-step semi-supervised multi-modal automated time annotation (MATA) method leveraging multi-dimensional longitudinal EHR encounter records. In step I, we employ a functional principal component analysis approach to estimate the underlying intensity functions based on observed point processes from the unlabeled patients. In step II, we fit a penalized proportional odds model to the event time outcomes with features derived in step I in the labeled data where the non-parametric baseline function is approximated using B-splines. Under regularity conditions, the resulting estimator of the feature effect vector is shown as root-n consistent. We demonstrate the superiority of our approach relative to existing approaches through simulations and a real data example on annotating lung cancer recurrence in an EHR cohort of lung cancer patients from Veteran Health Administration.

PMID:35753014 | DOI:10.1007/s10985-022-09557-5

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Nevin Manimala Statistics

Estimating Disease Prevalence in Administrative Data

Clin Invest Med. 2022 Jun 26;45(2):E21-27. doi: 10.25011/cim.v45i2.38100.

ABSTRACT

PURPOSE: Disease prevalence estimates from population-based administrative databases are often biased due to measurement (misclassification) errors. The purpose of this article is to review the methodology for estimating disease prevalence in administrative data, with a focus on bias correction.

SOURCE: Several approaches to bias correction in administrative data were reviewed and application of these methods was demonstrated using an example from the literature: physician claims and hospitalization data were employed to estimate diabetes prevalence in Ontario, Canada.

FINDINGS: Misclassification bias in prevalence estimates from administrative data can be reduced by developing and selecting an optimal algorithm for case identification, applying a bias correction formula, or using statistical modelling. An algorithm for which sensitivity equals positive predictive value provides an unbiased estimate of prevalence. Bias reduction methods generally require information about the measurement properties of the algorithm, such as sensitivity, specificity, or predictive value. These properties depend on disease type, prevalence, algorithm definition (including the observation window), and may vary by population and time. Prevalence estimates can be improved by applying multivariable disease prediction models.

CONCLUSION: Frequency of a positive case identification algorithm in administrative data is generally not equivalent to disease prevalence. Although prevalence estimates can be corrected for bias using known measurement properties of the algorithm, these properties may be difficult to estimate accurately; therefore, disease prevalence estimates based on administrative data must be treated with caution.

PMID:35752980 | DOI:10.25011/cim.v45i2.38100

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Nevin Manimala Statistics

Quality of chronic care for patients with type 2 diabetes in practices with and without a Clinical Specialized Medical Assistant (CSMA) – a cross-sectional study from Switzerland

Swiss Med Wkly. 2022 Jun 22;152:w30180. doi: 10.4414/smw.2022.w30180. eCollection 2022 Jun 20.

ABSTRACT

BACKGROUND: Due to Switzerland’s shortage of general practitioners (GPs), task shifting through interprofessional collaboration is needed to relieve GPs’ workload and allow the continued provision of quality care. The profession of specialized medical assistant (SMA) was created in Switzerland several years ago to provide a career advancement opportunity for medical practice assistants (MPAs) and intended to counteract the increasing scarcity of resources in primary care. Clinical specialized medical assistants (CSMAs) are trained to care for a set of chronic conditions, such as diabetes.

OBJECTIVE: We aimed to compare the quality of care for patients with type 2 diabetes in practices with and without CSMAs. Further, we aimed to investigate whether evidence exists that CSMA care models may allow for task shifting and the provision of interprofessional care while maintaining a high quality of care and to assess patient experiences with diabetes care in both care models.

METHODS: The present study was a paper-based cross-sectional survey of patient data. A total of 171 patients with type 2 diabetes who had been under the care of either a GP with CSMA (91 patients) or a GP without CSMA (80 patients) for at least one year were consecutively recruited for the study. Data were collected from mid-September 2020 to mid-June 2021. For the statistical analyses, we used descriptive statistics and t-tests.

RESULTS: Patients from both practice types were comparable in age, gender and diabetes-relevant factors such as Body Mass Index, smoking status and blood pressure. Overall, patients in both models received a high quality of care (Diabetes Treatment Satisfaction Questionnaire, DTSQ >32/36 points, SGED >75 points) and a low treatment burden (Treatment Burden Questionnaire, TBQ <20/150 points). When comparing patients’ DTSQ, SGED and TBQ in both groups, we found no significant differences in diabetes-specific satisfaction (32.1 [SD 3.6] vs. 32.4 [SD 3.8], p = 0.7), SGED score (80.2 [SD 8.5] vs. 75.9 [SD 4.8], p = 0.18) or treatment burden (19.2 [SD 15.6] vs. 18.8 [SD 21.4], p = 0.89).

CONCLUSION: Our comparison of patient-reported outcomes and SGED criteria of patients with type 2 diabetes in practices with and without CSMAs showed an equally high quality of care and a low treatment burden. More research is needed on the long-term effects and benefits of the care provided by CSMAs and which other tasks could be shifted to CSMAs to reduce the burden on GPs in the future. At the same time, an increasing number of patients with type 2 diabetes will require high-quality primary care.

PMID:35752968 | DOI:10.4414/smw.2022.w30180

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Nevin Manimala Statistics

Incidence and outcome of patients with renal cell carcinoma treated with partial or radical nephrectomy in the Cantons St Gallen and Appenzell 2009-2018

Swiss Med Wkly. 2022 Jun 16;152:w30175. doi: 10.4414/smw.2022.w30175. eCollection 2022 Jun 6.

ABSTRACT

BACKGROUND: Over recent years, the incidence of renal cell carcinoma (RCC) has remained unchanged in Switzerland and is low compared with other European countries. Partial or radical nephrectomy is the mainstay of treatment in patients with localised disease.

METHODS: We conducted an analysis of data from the cancer registry of Eastern Switzerland on patients with surgery for RCC from 2009 to 2018, focusing on a comparison of surgical technique and outcome in tertiary and non-tertiary hospitals.

RESULTS: 492 nephrectomies were performed. Out of 441 curative procedures, 226 were radical and 195 partial nephrectomies (20 unknown). At the tertiary hospital, statistically significantly more partial nephrectomies were performed in non-metastatic patients than at non-tertiary hospitals. We demonstrate a trend towards better disease-free survival after partial compared with radical nephrectomy. The 5-year overall survival for patients diagnosed between 2009 and 2013 was 85%, 83%, and 70% in stage I, II, and III, respectively, compared with 96%, 78%, and 72% for patients diagnosed between 2014 and 2018.

CONCLUSION: RCC incidence in Switzerland has been stable during the past decade in contrast to other European countries, and no stage migration occurred. We demonstrated that patients with localised renal cancer at our tertiary centre were more likely to be treated with renal preserving surgery compared with non-tertiary hospitals. This analysis underlines the importance of local cancer registries in the comparison of treatment and outcome over time.

PMID:35752957 | DOI:10.4414/smw.2022.w30175

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Nevin Manimala Statistics

Translation, Cultural Adaptation and Validation of the Hausa version of the Standardised Mini-Mental State Examination in Northeastern Nigeria

West Afr J Med. 2022 Jun 24;39(6):614-622.

ABSTRACT

BACKGROUND: Mini-Mental State Examination (MMSE) is one of the most widely used patient-rated assessment tools but may not be applicable among an overwhelming majority of Nigerians older adults. This is because MMSE was designed and adapted for English speakers, and some of its items are challenging to understand for those with low literacy levels.

OBJECTIVES: This study aimed at translating and adapting MMSE into the Hausa language and also evaluates the psychometric properties of the modified Hausa version of MMSE.

METHODOLOGY: The MMSE was translated and adapted into Hausa language by an Hausa language expert and focus group of experts and the validity of the adapted Hausa MMSE was evaluated against a gold standard (Diagnostic and Statistical Manual of Mental Disorder V criteria for neurocognitive disorders), among older adults participants (N=100). Descriptive statistics and inferential statistics (Receiver Operating Curve analysis and Cronbach alpha coefficient approach) were employed for data analysis and the alpha level was set at 0.05.

RESULTS: The adapted Hausa MMSE has item content validity index of 0.97 and the mean expert proportion relevant rating, across all the experts was 0.99. The adapted Hausa version of MMSE shows 66.7% sensitivity and 84.7% specificity, when the original MMSE cut off point of 24 was used. With ROC analysis, optimal cut-offs derived were 25 and 26 with Area Under Curve of 0.886 (95% CI: 0.816-0.956; Std.Err: 0.036; P=0.000). However, at the optimal cut off of 26, derived using ROC analysis, the modified Hausa MMSE had sensitivity of 93.3% and specificity of 71.8% and the tool internal consistency reliability had alpha value of 0.64.

CONCLUSION: Hausa adapted versions of MMSE is a valid cognitive screening tool for Hausa older adult patients although its use for Screening and for monitoring changes warrant considerations for two separate cut- off points.

PMID:35752953

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Nevin Manimala Statistics

The Prevalence and Outcome of Teenage Pregnancies in a Secondary Health Facility in Delta State, Nigeria: A Four-Year Retrospective Review

West Afr J Med. 2022 Jun 24;39:609-613.

ABSTRACT

INTRODUCTION: This study determined the prevalence, obstetric characteristics and pregnancy outcomes in teenagers who delivered at a secondary health facility in a Southern State in Nigeria.

MATERIALS AND METHODS: A retrospective study was employed to review pregnancies that were managed in Central Hospital Warri, Delta State, Nigeria between 2014-2017. Patients’ notes were retrieved and analyzed with respect to the socio-demographic characteristics, pregnancy, labor and delivery complications and fetal outcome. Chi-square test was used to test the association between the independent variables and the main outcomes of the study with statistical significance set at p<0.05.

RESULTS: Out of the 14,067 pregnancies reviewed, the prevalence of teenage pregnancy was 2.8%. The mean age of the teenagers was 17.5 (±1.4) years, 243 (61.5%) of them had completed secondary school. Majority 286 (72.4%) delivered via spontaneous vaginal delivery, while 73 (18.5%) and 36 (9.1%) delivered via caesarean section and instrumental delivery respectively. The commonest complications encountered among the pregnant teenagers were perineal laceration (23.3%), iron deficiency anemia (17%) and delivery of low birth weight infant (14.9%). The younger teenagers were twice at risk of iron deficiency anaemia {OR (95%CI); p = 2.60 (1.08-5.92); p=0.028}. A similar association was seen between the age of the teenagers and route of delivery {OR (95%CI); p = 3.11 (1.34-6.93); p=0.002}, delivery of low birth weight infant {OR (95%CI); p = 3.12 (1.28-7.15); p=0.003} and perineal laceration {OR (95%CI); p = 2.54 (1.13-5.55); p=0.010}.

CONCLUSION: Teenage pregnancy is associated with high risk of complications, especially among younger teenagers. Increasing public awareness as well as improving educational, socio- economic and reproductive health opportunities for adolescent girls is recommended.

PMID:35752950

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Nevin Manimala Statistics

Effect of Vent Hole and Cement Type on Fracture Resistance of CAD-CAM Monolithic Zirconia Crowns

J Prosthodont. 2022 Jun 25. doi: 10.1111/jopr.13563. Online ahead of print.

ABSTRACT

PURPOSE: To assess the fracture resistance of monolithic zirconia crowns cemented with different types of cement on cement-retained implant abutments.

MATERIALS AND METHODS: Forty implant analogues were positioned in acrylic resin blocks, and cement-retained straight implant abutments were fastened to the analogues. Crowns were designed with/without occlusal vent holes and produced from monolithic zirconia blocks by the CAD-CAM technique. The two crown types were divided into two groups and cemented with resin and zinc-polycarboxylate cement under 5 kg weight. A universal testing machine applied compressive forces to the crowns until fracture. Fracture resistance values were analysed using two-way ANOVA and the independent samples t-test with statistical significance set at p < 0.05.

RESULTS: According to the two-way ANOVA results, although the crown design did not have a significant effect on fracture resistance (1417.65 ±337.39 N, 1565.16 ±517.12 N; crowns with and without vent holes, respectively), the main effect of the cement variable on the fracture resistance was significant. Zinc-polycarboxylate cement (1680.1 ±375.23 N) showed higher fracture resistance than resin cement (1302.71 ±420.64 N) in the crowns designed with vent holes (p< 0.005).

CONCLUSION: The use of cement-retained implant-supported monolithic zirconia crowns with an occlusal vent hole is safe, and zinc-polycarboxylate cement use may be an appropriate choice for cementation of these crowns. This article is protected by copyright. All rights reserved.

PMID:35752941 | DOI:10.1111/jopr.13563

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Nevin Manimala Statistics

Observing pedestrian-vehicle traffic conflicts in school zones to evaluate the effectiveness of road safety interventions and reduce injuries in Ghana, Vietnam, and Mexico, 2019-2021

J Inj Violence Res. 2022 Jun 26;14(3). doi: 10.5249/jivr.v14i3.1710. Online ahead of print.

ABSTRACT

BACKGROUND: Daily more than 3,000 children are injured or killed on the road, often along the school route. Road traffic crashes and resulting injuries are preventable. More can be done to reduce injuries and save lives. Traffic Conflict Techniques (TCTs) are simple methods of collecting observational data to evaluate the effectiveness of road safety interventions through counting and analyzing traffic conflicts. A TCT Toolkit was developed and piloted to analyze pedestrian-vehicle traffic conflicts in school zones in low- and middle-income countries.

METHODS: Three non-governmental organizations in Ghana, Vietnam, and Mexico applied three TCTs from the TCT Toolkit to collect traffic conflict data before (pre-intervention) and after (post-intervention) road safety intervention implementation. As the number of traffic conflicts was often less than 100, confidence intervals (CIs) based on gamma distributions were calculated for the traffic conflict rate. Using the calculated traffic conflict rate, the difference between pre- and post-intervention rates was assessed by determining overlap of the CIs. When CIs did not overlap, the difference was said to be statistically significant at the 0.05 level.

RESULTS: For each method, results indicated a decrease in traffic conflicts between pre- and post-intervention data collection periods. Pre- and post-intervention traffic conflict rates with non-overlapping CIs demonstrated the results were statistically significant, providing evidence that the road safety interventions were effective.

CONCLUSIONS: TCTs are relatively low-cost and simple techniques that provide an opportunity to base road safety improvement decisions on real-world data. TCTs are effective in objectively evaluating road safety interventions and can help decision-makers evaluate strategies for improving road safety, preventing injuries and saving lives.

PMID:35752931 | DOI:10.5249/jivr.v14i3.1710