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Nevin Manimala Statistics

An intensive anatomy by whole-body dissection elective: a longitudinal study

Clin Anat. 2022 Apr 3. doi: 10.1002/ca.23861. Online ahead of print.

ABSTRACT

Whole body dissection, once a long-held method of learning and teaching in anatomy medical education, has largely been replaced by cost and time-reduced methods of teaching. This paper reports on a longitudinal study of student knowledge acquisition and retention, following six annual intensive seven-week elective anatomy by whole body dissection (AWBD) courses implemented between 2010 to 2015, utilising a modified Team-based learning (TBL) pedagogy. A total of 160 students completed the intensive full-time courses. During each course, students, in groups of five or six, completed the dissection of a whole cadaver. Students were assessed by a standardised practical test involving the accurate identification of 20 different tagged anatomical structures. All students (n=160) completed pre-course and end-course individual assessments. Seventy students were assessed again one month after the course ended. A further 71 students were assessed seven months later. A marked increase in topographical relational anatomical knowledge was demonstrated. The median pre-course score was 9/20 (interquartile range 5). The median end-course score was 19/20 (IQR 2), a statistically significant increase (p < 0.001). The assessments for the 70 students reassessed one month after the course ended showed no significant statistical change. The assessments for the further 71 students assessed seven months later also showed no significant statistical change. The results of this study demonstrate that AWBD, provides significant acquisition and maintenance of three-dimensional regional relational anatomical knowledge. As an elective, AWBD has a place in the medical curricula, particularly for students interested in a surgical or procedural based specialty career. This article is protected by copyright. All rights reserved.

PMID:35368123 | DOI:10.1002/ca.23861

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Precision and bias of spatial capture-recapture estimates: A multi-site, multi-year Utah black bear case study

Ecol Appl. 2022 Apr 3:e2618. doi: 10.1002/eap.2618. Online ahead of print.

ABSTRACT

Spatial capture-recapture (SCR) models are powerful analytical tools that have become the standard for estimating abundance and density of wild animal populations. When sampling populations to implement SCR, the number of unique individuals detected, total recaptures, and unique spatial relocations can be highly variable. These sample sizes influence precision and accuracy of model parameter estimates. Testing the performance of SCR models with sparse empirical datasets typical of low-density, wide-ranging species can inform the threshold at which a more integrated modeling approach with additional data sources or additional years of monitoring may be required to achieve reliable, precise parameter estimates. Using a multi-site, multi-year Utah black bear (Ursus americanus) capture-recapture dataset, we evaluated factors influencing the uncertainty of SCR structural parameter estimates, specifically density, detection, and the spatial scale parameter, sigma. We also provided some of the first SCR density estimates for Utah black bear populations, which ranged from 3.85 – 74.33 bears/100 km2 . Increasing total detections decreased uncertainty of density estimates, while an increasing number of total recaptures and individuals with recaptures decreased uncertainty of detection and sigma estimates, respectively. In most cases, multiple years of data were required for precise density estimates (<0.2 CV). Across study areas there was an average decline in CV of 0.07 with the addition of another year of data. One sampled population with very high estimated bear density had an atypically low number of spatial recaptures relative to total recaptures, apparently inflating density estimates. A complementary simulation study used to assess estimate bias suggested that when < 30% of recaptured individuals were spatially recaptured, density estimates were unreliable and ranged widely, in some cases to >3 times the simulated density. Additional research could evaluate these requirements for other density scenarios. Large numbers of individuals detected, numbers of spatial recaptures, and precision alone may not be sufficient indicators of parameter estimate reliability. We provide an evaluation of simple summary statistics of capture-recapture datasets that can provide an early signal of a need to alter sampling design or collect auxiliary data before model implementation to improve estimate precision and accuracy.

PMID:35368131 | DOI:10.1002/eap.2618

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Nevin Manimala Statistics

Linear mixed models to handle missing at random data in trial-based economic evaluations

Health Econ. 2022 Apr 2. doi: 10.1002/hec.4510. Online ahead of print.

ABSTRACT

Trial-based cost-effectiveness analyses (CEAs) are an important source of evidence in the assessment of health interventions. In these studies, cost and effectiveness outcomes are commonly measured at multiple time points, but some observations may be missing. Restricting the analysis to the participants with complete data can lead to biased and inefficient estimates. Methods, such as multiple imputation, have been recommended as they make better use of the data available and are valid under less restrictive Missing At Random (MAR) assumption. Linear mixed effects models (LMMs) offer a simple alternative to handle missing data under MAR without requiring imputations, and have not been very well explored in the CEA context. In this manuscript, we aim to familiarize readers with LMMs and demonstrate their implementation in CEA. We illustrate the approach on a randomized trial of antidepressants, and provide the implementation code in R and Stata. We hope that the more familiar statistical framework associated with LMMs, compared to other missing data approaches, will encourage their implementation and move practitioners away from inadequate methods.

PMID:35368119 | DOI:10.1002/hec.4510

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Nevin Manimala Statistics

The effects of interventions to integrate long-acting reversible contraception with treatment for incomplete abortion: Results of a six-year interrupted time series analysis in hospitals in mainland Tanzania and Zanzibar

Int J Gynaecol Obstet. 2022 Apr 3. doi: 10.1002/ijgo.14203. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate an intervention strengthening voluntary access to long-acting reversible contraception (LARC) within postabortion care (PAC) in hospitals in mainland Tanzania and Zanzibar.

METHODS: From 2016 to 2018, we conducted PAC quality improvement interventions, emphasizing family planning (FP) counseling and voluntary access to LARC. Researchers conducted an interrupted time series analysis of service statistics compiled from 2014 to 2020 using segmented linear mixed effects regression models to assess the interventions’ effect on postabortion contraceptive uptake.

RESULTS: The intervention in mainland was associated with an immediate 38% increase in postabortion LARC uptake, a trend that declined from late 2016 to mid-2020 to 34%. In Zanzibar, the intervention was associated with a gradual increase in LARC uptake that peaked in late 2018 at 23% and stabilized at approximately 15% by mid-2020. Whereas the interventions in mainland did not generate significant changes in postabortion FP uptake overall, the launch of interventions in Zanzibar in mid-2016 was associated with a precipitous rise in that outcome over time, which plateaued at approximately 54% by 2019.

CONCLUSION: Increased voluntary uptake of postabortion contraception was associated with the introduction of training in PAC, including FP, and quality improvement interventions and gains were sustained over time.

PMID:35368096 | DOI:10.1002/ijgo.14203

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C-Reactive Protein Trajectories and the Risk of All Cancer Types: A Prospective Cohort Study

Int J Cancer. 2022 Apr 3. doi: 10.1002/ijc.34012. Online ahead of print.

ABSTRACT

A single CRP measurement is insufficient to examine the association of long-term patterns of CRP concentration with cancer risk. We prospectively examined the relationship between CRP trajectory patterns and new-onset cancers among 52 276 participants. Latent mixture modeling was used to identify CRP trajectories. Cox proportional hazards regression models were used to evaluate the association between CRP trajectory patterns and the risk of overall and specific-site cancer. Four CRP trajectories patterns were identified: low-stable pattern (n = 43 258), moderate-increasing pattern (n = 2591), increasing-decreasing pattern (n = 2068), and elevated-decreasing pattern (n = 4359). Relative to the low-stable pattern, the moderate-increasing trajectory pattern was associated with an elevated risk of overall, lung, breast, leukemia, bladder, stomach, colorectal, liver, gallbladder, or extrahepatic bile duct cancer and leukemia. Participants in the increasing-decreasing trajectory pattern were associated with an elevated risk of overall, lung, breast, bladder, pancreatic, and liver cancer. The increasing-decreasing trajectory pattern was also associated with decreased risk of colorectal cancer in the multivariate analyses. Elevated-decreasing trajectory pattern was associated with increased risk of leukemia and decreased risk of esophageal and colorectal cancer. CRP trajectories play an important role in the occurrence of cancers, especially in the lung, breast, bladder, stomach, colorectal, liver, gallbladder and extrahepatic bile duct cancer, and leukemia. This article is protected by copyright. All rights reserved.

PMID:35368093 | DOI:10.1002/ijc.34012

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Nevin Manimala Statistics

Application of individualized differential expression analysis in human cancer proteome

Brief Bioinform. 2022 Apr 2:bbac096. doi: 10.1093/bib/bbac096. Online ahead of print.

ABSTRACT

Liquid chromatography-mass spectrometry-based quantitative proteomics can measure the expression of thousands of proteins from biological samples and has been increasingly applied in cancer research. Identifying differentially expressed proteins (DEPs) between tumors and normal controls is commonly used to investigate carcinogenesis mechanisms. While differential expression analysis (DEA) at an individual level is desired to identify patient-specific molecular defects for better patient stratification, most statistical DEP analysis methods only identify deregulated proteins at the population level. To date, robust individualized DEA algorithms have been proposed for ribonucleic acid data, but their performance on proteomics data is underexplored. Herein, we performed a systematic evaluation on five individualized DEA algorithms for proteins on cancer proteomic datasets from seven cancer types. Results show that the within-sample relative expression orderings (REOs) of protein pairs in normal tissues were highly stable, providing the basis for individualized DEA for proteins using REOs. Moreover, individualized DEA algorithms achieve higher precision in detecting sample-specific deregulated proteins than population-level methods. To facilitate the utilization of individualized DEA algorithms in proteomics for prognostic biomarker discovery and personalized medicine, we provide Individualized DEP Analysis IDEPAXMBD (XMBD: Xiamen Big Data, a biomedical open software initiative in the National Institute for Data Science in Health and Medicine, Xiamen University, China.) (https://github.com/xmuyulab/IDEPA-XMBD), which is a user-friendly and open-source Python toolkit that integrates individualized DEA algorithms for DEP-associated deregulation pattern recognition.

PMID:35368072 | DOI:10.1093/bib/bbac096

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Nevin Manimala Statistics

cSurvival: a web resource for biomarker interactions in cancer outcomes and in cell lines

Brief Bioinform. 2022 Apr 2:bbac090. doi: 10.1093/bib/bbac090. Online ahead of print.

ABSTRACT

Survival analysis is a technique for identifying prognostic biomarkers and genetic vulnerabilities in cancer studies. Large-scale consortium-based projects have profiled >11 000 adult and >4000 pediatric tumor cases with clinical outcomes and multiomics approaches. This provides a resource for investigating molecular-level cancer etiologies using clinical correlations. Although cancers often arise from multiple genetic vulnerabilities and have deregulated gene sets (GSs), existing survival analysis protocols can report only on individual genes. Additionally, there is no systematic method to connect clinical outcomes with experimental (cell line) data. To address these gaps, we developed cSurvival (https://tau.cmmt.ubc.ca/cSurvival). cSurvival provides a user-adjustable analytical pipeline with a curated, integrated database and offers three main advances: (i) joint analysis with two genomic predictors to identify interacting biomarkers, including new algorithms to identify optimal cutoffs for two continuous predictors; (ii) survival analysis not only at the gene, but also the GS level; and (iii) integration of clinical and experimental cell line studies to generate synergistic biological insights. To demonstrate these advances, we report three case studies. We confirmed findings of autophagy-dependent survival in colorectal cancers and of synergistic negative effects between high expression of SLC7A11 and SLC2A1 on outcomes in several cancers. We further used cSurvival to identify high expression of the Nrf2-antioxidant response element pathway as a main indicator for lung cancer prognosis and for cellular resistance to oxidative stress-inducing drugs. Altogether, these analyses demonstrate cSurvival’s ability to support biomarker prognosis and interaction analysis via gene- and GS-level approaches and to integrate clinical and experimental biomedical studies.

PMID:35368077 | DOI:10.1093/bib/bbac090

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Nevin Manimala Statistics

Exposure to negative news stories about vaping, and harm perceptions of vaping, among youth in England, Canada, and the US before and after the outbreak of E-cigarette or Vaping-Associated Lung Injury (EVALI)

Nicotine Tob Res. 2022 Apr 3:ntac088. doi: 10.1093/ntr/ntac088. Online ahead of print.

ABSTRACT

INTRODUCTION: Little is known about the international impact of ‘EVALI’ on youth perceptions of vaping harms.

METHODS: Repeat cross-sectional online surveys of youth aged 16-19 in England, Canada, and the US before (2017, 2018), during (2019Aug/Sept), and after (2020Feb/Mar, 2020Aug) the ‘EVALI’ outbreak (N=63,380). Logistic regressions assessed trends, country differences, and associations between exposure to negative news stories about vaping and vaping harm perceptions.

RESULTS: Exposure to negative news stories increased between 2017 and Feb/Mar 2020 in England (12.6% to 34.2%), Canada (16.7% to 56.9%), and the US (18.0% to 64.6%), accelerating during (2019) and immediately after (Feb/Mar 2020) the outbreak (p<.001) before returning to 2019 levels by Aug 2020. Similarly, accurate perception that vaping is less harmful than smoking declined between 2017 and Feb/Mar 2020 in England (77.3% to 62.2%), Canada (66.3% to 43.3%), and the US (61.3% to 34.0%), again accelerating during and immediately after the outbreak (p<.001). Perception that vaping takes less than a year to harm users’ health and worry that vaping will damage health also doubled over this period (p≤.001). Time trends were most pronounced in the US. Exposure to negative news stories predicted perception that vaping takes less than a year to harm health (AOR=1.55, 1.48-1.61) and worry that vaping will damage health (AOR=1.32, 1.18-1.48).

CONCLUSIONS: Between 2017 and February/March 2020, youth exposure to negative news stories, and perceptions of vaping harms, increased, and increases were exacerbated during and immediately after ‘EVALI’. Effects were seen in all countries but were most pronounced in the US.

IMPLICATIONS: This is the first study to examine changes in exposure to news stories about vaping, and perceptions of vaping harms, among youth in England, Canada, and the US before, during, and after ‘EVALI’. Between 2017 and February/March 2020, youth exposure to negative news stories, and perceptions of vaping harms, increased, and increases were exacerbated during and immediately after ‘EVALI’. By August 2020, exposure to negative news stories returned to 2019 levels, while perceptions of harm were sustained. Exposure to negative news stories also predicted two of three harm perceptions measures. Overall, findings suggest ‘EVALI’ may have exacerbated youth’s perceptions of vaping harms internationally.

PMID:35368062 | DOI:10.1093/ntr/ntac088

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Nevin Manimala Statistics

A community based cross sectional study on the prevalence of dyslipidemias and 10 years cardiovascular risk scores in adults in Asmara, Eritrea

Sci Rep. 2022 Apr 2;12(1):5567. doi: 10.1038/s41598-022-09446-9.

ABSTRACT

Despite the contribution of dyslipidemia to the high and rising burden of arteriosclerotic cardiovascular disease (CVD) in Sub-Saharan Africa; the condition is under-diagnosed, under-treated, and under-described. The objective of this study was to explore the prevalence of dyslipidemias, estimate a 10-year cardiovascular disease risk and associated factors in adults (≥ 35 to ≤ 85 years) living in Asmara, Eritrea. This population-based cross-sectional study was conducted among individuals without overt CVDs in Asmara, Eritrea, from October 2020 to November 2020. After stratified multistage sampling, a total of 386 (144 (37%) males and 242 (63%) females, mean age ± SD, 52.17 ± 13.29 years) respondents were randomly selected. The WHO NCD STEPS instrument version 3.1 questionnaire was used to collect data. Information on socio-demographic variables was collected via interviews by trained data collectors. Measurements/or analyses including anthropometric, lipid panel, fasting plasma glucose, and blood pressure were also undertaken. Finally, data was analyzed by using Statistical Package for Social Sciences version 26.0 for Windows (SPSS Inc., Chicago, IL, USA). All p-values were 2-sided and the level of significance was set at p < 0.05 for all analyses. The frequency of dyslipidemia in this population was disproportionately high (87.4%) with the worst affected subgroup in the 51-60 age band. Further, 98% of the study participants were not aware of their diagnosis. In terms of individual lipid markers, the proportions were as follows: low HDL-C (55.2%); high TC (49.7%); high LDL (44.8%); high TG (38.1%). The mean ± SD, for HDL-C, TC, LDL-C, non-HDL-C, and TG were 45.28 ± 9.60; 205.24 ± 45.77; 130.77 ± 36.15; 160.22 ± 42.09 and 144.5 ± 61.26 mg/dL, respectively. Regarding NCEP ATP III risk criteria, 17.6%, 19.4%, 16.3%, 19.7%, and 54.7% were in high or very high-risk categories for TC, Non-HDL-C, TG, LDL-C, and HDL-C, respectively. Among all respondents, 59.6% had mixed dyslipidemias with TC + TG + LDL-C dominating. In addition, 27.3%, 28.04%, 23.0%, and 8.6% had abnormalities in 1, 2, 3 and 4 lipid abnormalities, respectively. Multivariate logistic regression modeling suggested that dyslipidemia was lower in subjects who were employed (aOR 0.48, 95% CI 0.24-0.97, p = 0.015); self-employed (aOR 0.41, 95% CI 0.17-1.00, p = 0.018); and married (aOR 2.35, 95% CI 1.19-4.66, p = 0.009). A higher likelihood of dyslipidemia was also associated with increasing DBP (aOR 1.04 mmHg (1.00-1.09, p = 0.001) and increasing FPG (aOR 1.02 per 1 mg/dL, 95% CI 1.00-1.05, p = 0.001). Separately, Framingham CVD Risk score estimates suggested that 12.7% and 2.8% were at 10 years CVD high risk or very high-risk strata. High frequency of poor lipid health may be a prominent contributor to the high burden of atherosclerotic CVDs-related mortality and morbidity in Asmara, Eritrea. Consequently, efforts directed at early detection, and evidence-based interventions are warranted. The low awareness rate also points at education within the population as a possible intervention pathway.

PMID:35368036 | DOI:10.1038/s41598-022-09446-9

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Oral conditions and salivary analysis in HIV-uninfected subjects using preexposure prophylaxis

Med Oral Patol Oral Cir Bucal. 2022 Apr 3:25140. doi: 10.4317/medoral.25140. Online ahead of print.

ABSTRACT

BACKGROUND: New prevention strategies have been advocated to control the progression of HIV/AIDS, such as preexposure prophylaxis (PrEP). The aim of this study is to evaluate the potential changes in the oral and salivary conditions of HIV-uninfected subjects using PrEP.

MATERIAL AND METHODS: Subjects were evaluated before beginning the medication (T0), at the first follow-up (T1), and at the second follow-up (T2). Xerostomia, presence of untreated cavitated caries, oral hygiene habits, taste, gingival and plaque index, stimulated salivary flow rate (SSFR), and salivary concentrations of calcium, glucose, urea, and total proteins were evaluated. Data obtained were analyzed using statistical tests (p<0.05).

RESULTS: Forty-seven participants (41 men; 6 women) were evaluated at T0. Thirty (28 men; 2 women) and 17 men were reassessed at T1 and T2, respectively. There was no difference between the SSFR and oral and salivary conditions between T0, T1, and T2 (p>0.05), except for the salivary calcium concentration, that increased at T2 compared to T1 (p=0.02). There was significant difference between taste and xerostomia at T1 (p=0.017), and the need to drink to swallow at T2 (p=0.015). There was significant correlation between the reported amount of saliva and taste (p=0.039, r=-0.378) at T1.

CONCLUSIONS: The prolonged use of PrEP seems to be associated with reports of dry mouth and worsening of taste, possibly associated with increased salivary calcium concentration.

PMID:35368014 | DOI:10.4317/medoral.25140