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Nevin Manimala Statistics

Association between body weight variability and an incidence of Parkinson’s disease: A nationwide, population-based cohort study

Eur J Neurol. 2021 Jul 13. doi: 10.1111/ene.15025. Online ahead of print.

ABSTRACT

BACKGROUND: Although body weight variability has been associated with mortality, cardiovascular disease, and dementia, the relationship between body weight variability and Parkinson’s disease (PD) has been rarely studied. We aimed to investigate the longitudinal association between body weight variability and PD incidence.

METHODS: A nationwide population-based, cohort study was conducted using the database from the Health Insurance Review and Assessment Service of the whole Korean population. We analyzed 2,815,135 participants (≥ 40 years old, mean age 51.7 (8.6) years, 66.8% men) without a previous PD diagnosis. We determined individual body weight variability from baseline weight and follow-up visits. We used Cox proportional hazards regression models.

RESULTS: The highest quartile group was associated with increased PD incidence compared with the lowest quartile group after adjustment for confounding factors (hazard ratio (HR), 1.18; 95% confidence interval (CI): 1.08-1.29). In contrast, baseline body mass index, baseline waist circumference, and waist circumference variability were not associated with increased PD incidence. In the body weight loss group, individuals within the quartile of the highest variation in body weight showed a higher HR of PD risk than those within other quartiles (HR, 1.41; 95% CI: 1.18-1.68).

CONCLUSION: Body weight variability, especially weight loss, was associated with higher PD incidence. This finding has important implications for clinicians and supports the need for preventative measures and surveillance for PD in individuals with fluctuating body weight.

PMID:34255908 | DOI:10.1111/ene.15025

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Nevin Manimala Statistics

Changes in obstetric interventions and preterm birth during COVID-19: A nationwide study from Iceland

Acta Obstet Gynecol Scand. 2021 Jul 13. doi: 10.1111/aogs.14231. Online ahead of print.

ABSTRACT

INTRODUCTION: Previous evidence has been conflicting regarding the effect of Covid-19 pandemic lockdowns on obstetric intervention and preterm birth rates. The literature to date suggests potentially differential underlying mechanisms based on country economic setting. We aimed to study these outcomes in an Icelandic population where uniform lockdown measures were implemented across the country.

MATERIAL AND METHODS: The study included all singleton births (n=20,680) during 2016-2020 identified from the population-based Icelandic Medical Birth Register. We defined two lockdown periods during March-May and October-December in 2020 according to government implemented nationwide lockdown. We compared monthly rates of cesarean section, induction of labor and preterm birth during lockdown with the same time periods in the four years prior (2016-2019) using logit binomial regression adjusted for confounders.

RESULTS: Our results indicated a reduction in the overall cesarean section rate, which was mainly evident for elective cesarean section, both during the first (adjusted odd ratio (AOR) 0.71, 95% CI 0.51-0.99) and second (AOR 0.72, 95% CI 0.52-0.99) lockdown periods, and not for emergency cesarean section. No change during lockdown was observed in induction of labor. Our results also suggested a reduction in the overall preterm birth rate during the first lockdown (AOR 0.69, 95% CI 0.49-0.97) and in the months immediately following the lockdown (June-September) (AOR 0.67, 95% CI 0.49-0.89). The reduction during the first lockdown was mainly evident for medically indicated preterm birth (although not statistically significant) and the reduction during June-September was mainly evident for spontaneous preterm birth.

CONCLUSIONS: This study suggested a reduction in elective cesarean section during Covid-19 lockdown, possibly reflecting changes in prioritization of nonurgent health care during lockdown. We also found a reduction in overall preterm birth during the first lockdown and spontaneous preterm birth following the first lockdown, but further research is needed to shed light on the underlying mechanisms for these findings.

PMID:34255860 | DOI:10.1111/aogs.14231

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Nevin Manimala Statistics

InTACT: An adaptive and powerful framework for joint-tissue transcriptome-wide association studies

Genet Epidemiol. 2021 Jul 13. doi: 10.1002/gepi.22425. Online ahead of print.

ABSTRACT

Transcriptome-wide association studies (TWAS) that integrate transcriptomic reference data and genome-wide association studies (GWAS) have successfully enhanced the discovery of candidate genes for many complex traits. However, existing methods may suffer from substantial power loss because they fail to effectively consider that expression of many genes tends to be consistent across tissues. Here we propose a computationally efficient testing method, referred to as Integrative Test for Associations via Cauchy Transformation (InTACT), that effectively combines information across multiple tissues and thus improves the power of identifying associated genes. Through simulation studies, we show that InTACT maintains high power while properly controls for Type 1 error rates. We applied InTACT to the largest GWAS of Alzheimer’s disease (AD) to date and identified 227 genome-wide significant genes, of which 130 were not identified by benchmark methods, TWAS and MultiXcan. Importantly, InTACT identified five novel loci for AD. We implemented InTACT in publicly available software, “InTACT.”

PMID:34255882 | DOI:10.1002/gepi.22425

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Nevin Manimala Statistics

Impact of COVID-19 outbreak on Italian healthcare workers versus general population: results from an online survey

Clin Psychol Psychother. 2021 Jul 13. doi: 10.1002/cpp.2644. Online ahead of print.

ABSTRACT

OBJECTIVE: COVID-19 pandemic has been a stressful condition. We explored life changes and health-related consequences of COVID-19 outbreak in Italian health care workers in comparison to the general population.

METHODS: A total of 593 subjects participated to the online CoRonavIruS Health Impact Survey. Life events and changes, physical health, and worries were evaluated referring to 2-week prior the survey. Mood states and daily behavior were retrospectively evaluated referring to 3-month before COVID-19 (T1) and 2-week prior the survey (T2). Student t-test, Mann-Whitney test, and multivariate logistic regression analyses were run.

RESULTS: Five hundred and twenty-one subjects were analyzed (healthcare workers: n= 163, 31.84%; general population: n = 349, 68.16%). Healthcare workers were more likely to report fatigue and have spent more time outside home during the 2-week prior the survey than the general population (x2 (df)=266.03(17), p<0.001, R2=0.57). From T1 to T2, healthcare workers had a significant increase in negative mood, worry, restlessness, loneliness, and a decrease in happiness, while subjects from the general population had a statistically significant increase in negative mood, worry, attention, concentration difficulties, and a decrease in happiness, pleasure related to daily activities, time spent outdoors, alcohol use.

CONCLUSION: In the framework of a growing literature on health care workers’ status during the COVID-19 pandemic, the present study allowed to identify fatigue and loneliness as psychosomatic modifiable variables in need of being monitored and, possibly managed, to ameliorate the health status of health care workers.

PMID:34255890 | DOI:10.1002/cpp.2644

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Nevin Manimala Statistics

On the stability of log-rank test under labeling errors

Bioinformatics. 2021 Jul 13:btab495. doi: 10.1093/bioinformatics/btab495. Online ahead of print.

ABSTRACT

MOTIVATION: Log rank test is a widely used test that serves to assess the statistical significance of observed differences in survival, when comparing two or more groups. The log rank test is based on several assumptions that support the validity of the calculations. It is naturally assumed, implicitly, that no errors occur in the labeling of the samples. That is – that the mapping between samples and groups is perfectly correct. In this work we investigate how test results may be affected when considering some errors in the original labeling.

RESULTS: We introduce and define the uncertainty that arises from labeling errors in log rank test. In order to deal with this uncertainty, we develop a novel algorithm for efficiently calculating a stability interval around the original log rank p-value and prove its correctness. We demonstrate our algorithm on several datasets.

AVAILABILITY: We provide a Python implementation, called LoRSI, for calculating the stability interval using our algorithm. https://github.com/YakhiniGroup/LoRSI.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34255820 | DOI:10.1093/bioinformatics/btab495

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Nevin Manimala Statistics

In1-ghrelin splicing variant as a key element in the pathophysiological association between obesity and prostate cancer

J Clin Endocrinol Metab. 2021 Jul 13:dgab516. doi: 10.1210/clinem/dgab516. Online ahead of print.

ABSTRACT

CONTEXT: Recent studies emphasize the importance of considering the metabolic status to develop personalized medicine approaches. This is especially relevant in prostate cancer (PCa), wherein the diagnostic capability of PSA dramatically drops when considering patients with PSA levels ranging 3-10 ng/mL, the so-called “grey-zone”. Hence, additional non-invasive diagnostic and/or prognostic PCa biomarkers are urgently needed, especially in the metabolic-status context.

OBJECTIVE: To assess the potential relation of urine In1-ghrelin (a ghrelin splicing variant) levels with metabolic-related/pathological conditions (e.g. obesity/diabetes/BMI/insulin-glucose levels), and to define its potential clinical value in PCa (diagnostic/prognostic capacity) and relationship with PCa-risk in patients with PSA in the grey-zone.

METHODS: Urine In1-ghrelin levels were measured by radioimmunoassay in a clinically/metabolically/pathologically well-characterized cohort of patients without (n=397) or with (n=213) PCa with PSA in the grey-zone.

RESULTS: Key obesity-related factors associated with PCa-risk (BMI/diabetes/glucose/insulin) were strongly correlated to In1-ghrelin levels. Importantly, In1-ghrelin levels were higher in PCa patients compared to control patients (with suspect of PCa but negative-biopsy). Moreover, high In1-ghrelin levels were associated with increased PCa-risk and linked to PCa-aggressiveness (e.g. tumour-stage/lymphovascular-invasion). In1-ghrelin levels added significant diagnostic value to a clinical model consisting of age, suspicious-DRE, previous-biopsy, and PSA levels. Furthermore, a multivariate model consisting of clinical and metabolic variables, including In1-ghrelin levels, showed high specificity and sensitivity to diagnose PCa (AUC=0.740).

CONCLUSIONS: Urine In1-ghrelin levels are associated with obesity-related factors and PCa risk/aggressiveness, and could represent a novel and valuable non-invasive PCa biomarker, as well as a potential link in the pathophysiological relationship between obesity and PCa.

PMID:34255835 | DOI:10.1210/clinem/dgab516

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Nevin Manimala Statistics

Social sentiment segregation: Evidence from Twitter and Google Trends in Chile during the COVID-19 dynamic quarantine strategy

PLoS One. 2021 Jul 13;16(7):e0254638. doi: 10.1371/journal.pone.0254638. eCollection 2021.

ABSTRACT

The Chilean health authorities have implemented a sanitary strategy known as dynamic quarantine or strategic quarantine to cope with the COVID-19 pandemic. Under this system, lockdowns were established, lifted, or prolonged according to the weekly health authorities’ assessment of municipalities’ epidemiological situation. The public announcements about the confinement situation of municipalities country-wide are made typically on Tuesdays or Wednesdays before noon, have received extensive media coverage, and generated sharp stock market fluctuations. Municipalities are the smallest administrative division in Chile, with each city broken down typically into several municipalities. We analyze social media behavior in response to the confinement situation of the population at the municipal level. The dynamic quarantine scheme offers a unique opportunity for our analysis, given that municipalities display a high degree of heterogeneity, both in size and in the socioeconomic status of their population. We exploit the variability over time in municipalities’ confinement situations, resulting from the dynamic quarantine strategy, and the cross-sectional variability in their socioeconomic characteristics to evaluate the impact of these characteristics on social sentiment. Using event study and panel data methods, we find that proxies for social sentiment based on Twitter queries are negatively related (more pessimistic) to increases in the number of confined people, but with a statistically significant effect concentrated on people from the wealthiest cohorts of the population. For indicators of social sentiment based on Google Trends, we found that search intensity during the periods surrounding government announcements is positively related to increases in the total number of confined people. Still, this effect does not seem to be dependent on the segments of the population affected by the quarantine. Furthermore, we show that the observed heterogeneity in sentiment mirrors heterogeneity in stock market reactions to government announcements. We provide evidence that the observed stock market behavior around quarantine announcements can be explained by the number of people from the wealthiest segments of the population entering or exiting lockdown.

PMID:34255804 | DOI:10.1371/journal.pone.0254638

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Nevin Manimala Statistics

One-year change in plasma volume and mortality in the Japanese general population: An observational cohort study

PLoS One. 2021 Jul 13;16(7):e0254665. doi: 10.1371/journal.pone.0254665. eCollection 2021.

ABSTRACT

BACKGROUND: Changes in plasma volume, a marker of plasma volume expansion and contraction, are gaining attention in the field of cardiovascular disease because of its role in the prevention and management of heart failure. However, it remains unknown whether a 1-year change in plasma volume is a risk factor for all-cause, cardiovascular, and non-cardiovascular mortality in the general population.

METHODS AND RESULTS: We used a nationwide database of 134,291 subjects (age 40-75 years) who participated in the annual “Specific Health Check and Guidance in Japan” check-up for 2 consecutive years between 2008 and 2011. A 1-year change in plasm volume was calculated using the Strauss-Davis-Rosenbaum formula. There were 220 cardiovascular deaths, 1,001 non-cardiovascular deaths including 718 cancer deaths, and 1,221 all-cause deaths during the follow-up period of 3.9 years. All subjects were divided into quintiles based on the 1-year change in plasma volume. Kaplan-Meier analysis demonstrated that the highest 5th quintile had the greatest risk among the five groups. Multivariate Cox proportional hazard regression analysis demonstrated that a 1-year change in plasma volume was an independent risk factor for all-cause, cardiovascular, non-cardiovascular, and cancer deaths. The addition of a 1-year change in plasma volume to cardiovascular risk factors significantly improved the C-statistic, net reclassification, and integrated discrimination indexes.

CONCLUSIONS: Here, we have demonstrated for the first time that a 1-year change in plasma volume could be an additional risk factor for all-cause, cardiovascular, and non-cardiovascular (mainly cancer) mortality in the general population.

PMID:34255808 | DOI:10.1371/journal.pone.0254665

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Nevin Manimala Statistics

Probabilistic Identification of Bacterial Essential Genes via insertion density using TraDIS Data with Tn5 libraries

Bioinformatics. 2021 Jul 13:btab508. doi: 10.1093/bioinformatics/btab508. Online ahead of print.

ABSTRACT

MOTIVATION: Probabilistic Identification of bacterial essential genes using TraDIS data based on Tn5 libraries has received relatively little attention in the literature; most methods are designed for mariner transposon insertions. Analysis of Tn5 transposon-based genomic data is challenging due to the high insertion density and genomic resolution. We present a novel probabilistic Bayesian approach for classifying bacterial essential genes using transposon insertion density derived from transposon insertion sequencing data. We implement a Markov chain Monte Carlo sampling procedure to estimate the posterior probability that any given gene is essential. We implement a Bayesian decision theory approach to selecting essential genes. We assess the effectiveness of our approach via analysis of both simulated data and three previously published Escherichia coli, Salmonella Typhimurium and Staphylococcus aureus datasets. These three bacteria have relatively well characterised essential genes which allows us to test our classification procedure using receiver operating characteristic curves and area under the curves. We compare the classification performance with that of Bio-Tradis, a standard tool for bacterial gene classification.

RESULTS: Our method is able to classify genes in the three datasets with areas under the curves between 0.967 and 0.983. Our simulated synthetic datasets show that both the number of insertions and the extent to which insertions are tolerated in the distal regions of essential genes are both important in determining classification accuracy. Importantly our method gives the user the option of classifying essential genes based on the user-supplied costs of false discovery and false non-discovery.

AVAILABILITY: An R package that implements the method presented in this paper is available for download from https://github.com/Kevin-walters/insdens.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34255819 | DOI:10.1093/bioinformatics/btab508

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Nevin Manimala Statistics

Pulmonary rehabilitation in Lebanon “What do we have”? A national survey among chest physicians

PLoS One. 2021 Jul 13;16(7):e0254419. doi: 10.1371/journal.pone.0254419. eCollection 2021.

ABSTRACT

BACKGROUND: Pulmonary rehabilitation (PR) is not very often used by physicians in Lebanon despite evidence on its positive effects on health-related quality of life.

AIM: This study assesses the knowledge, attitudes and practices of PR among physicians in Lebanon. In addition, the study identifies the main barriers to access to PR according to chest physicians. Insight into these issues will help to increase awareness about the need for PR programs and can contribute to designing such programs in the country.

METHODS: A survey was conducted during the regional conference of the Lebanese Pulmonary Society. One week after the initial survey, the survey questionnaire was sent by email to all chest physicians who were registered with the Lebanese Pulmonary Society but did not attend the conference. A 25-item questionnaire was used to collect information on PR.

RESULTS: Responses were analyzed using descriptive statistics. The response rate was 40%. Results show that only one-third of Lebanese chest physicians have good knowledge about the nature and multidisciplinary content of PR. Physicians generally support the current “Pulmonary Rehabilitation Program” in Beirut. Key barriers found are the lack of referral, lack of motivation by patients due to their health, cost of care and lack of qualified health care specialists in Lebanon.

CONCLUSION: Absence of awareness and education about PR among healthcare providers plays an important role in increasing access to the “Pulmonary Rehabilitation Program”. Awareness campaigns and education for physicians, health care professionals and patients should be considered to increase PR in the country.

PMID:34255790 | DOI:10.1371/journal.pone.0254419