Clustering of health risk behaviors among school-going adolescents in Mymensingh district, Bangladesh.

BACKGROUND: Adolescents frequently engage in risky behaviors that negatively influence their health and pose a serious public health concern. This study aimed to examine the clustering pattern of health risk behaviors among school-going adolescents in Bangladesh. METHODS: A cross-sectional study was conducted from 15 April to 27 June 2022 among 412 school-going adolescents in Mymensingh district of Bangladesh through a convenience sampling technique. Data were collected via face-to-face interviews using a modified Global School-Based Student Health Survey (GSHS) 2021 questionnaire. Cluster membership was identified using the k-means clustering algorithm. The chi-square test was adopted to explore the association between sociodemographic variables and each cluster membership. The ordinal logistic regression model was employed to examine the predictors associated with cluster membership. RESULTS: Most of the respondents were female (55.3%) and belonged to the 16-19 years (74.5%) age group. Three behavioral clusters were identified, including Cluster 1: Low-risk taker (50.2%), Cluster 2: Moderate risk taker (39.6%), and Cluster 3: High-risk taker (10.2%). Influential factors of high-risk behavior among adolescents were significantly associated with their age (p = 0.03), father's education who were illiterate (p = 0.02), monthly family income >30000 BDT (p = 0.04), parent's those were understanding their child's problems in most of the time (p = 0.001). CONCLUSIONS: The study found that high-risk behaviors are significantly higher among late adolescents, those whose fathers are illiterate, whose monthly income is higher, those whose parents or guardians never realize their child's complications and worries, and those whose parents or guardians never recognize what they did in their leisure time. These findings will help to develop intervention programs, policies, strategies, and curricula in school by the experts following the necessity to adopt the adolescent toward healthy behavior and help to reduce the prevalence of health risk behavior.

Deep learning neural network derivation and testing to distinguish acute poisonings.

INTRODUCTION: Acute poisoning is a significant global health burden, and the causative agent is often unclear. The primary aim of this pilot study was to develop a deep learning algorithm that predicts the most probable agent a poisoned patient was exposed to from a pre-specified list of drugs. RESEARCH DESIGN & METHODS: Data were queried from the National Poison Data System (NPDS) from 2014 through 2018 for eight single-agent poisonings (acetaminophen, diphenhydramine, aspirin, calcium channel blockers, sulfonylureas, benzodiazepines, bupropion, and lithium). Two Deep Neural Networks (PyTorch and Keras) designed for multi-class classification tasks were applied. RESULTS: There were 201,031 single-agent poisonings included in the analysis. For distinguishing among selected poisonings, PyTorch model had specificity of 97%, accuracy of 83%, precision of 83%, recall of 83%, and a F1-score of 82%. Keras had specificity of 98%, accuracy of 83%, precision of 84%, recall of 83%, and a F1-score of 83%. The best performance was achieved in the diagnosis of single-agent poisoning in diagnosing poisoning by lithium, sulfonylureas, diphenhydramine, calcium channel blockers, then acetaminophen, in PyTorch (F1-score = 99%, 94%, 85%, 83%, and 82%, respectively) and Keras (F1-score = 99%, 94%, 86%, 82%, and 82%, respectively). CONCLUSION: Deep neural networks can potentially help in distinguishing the causative agent of acute poisoning. This study used a small list of drugs, with polysubstance ingestions excluded.Reproducible source code and results can be obtained at https://github.com/ashiskb/npds-workspace.git.

Aducanumab for the treatment of Alzheimer's disease: a systematic review.

Aducanumab is a novel disease-modifying anti-amyloid-beta (Aß) human monoclonal antibody specifically targeted to the pathophysiology of Alzheimer's disease (AD). It was granted for treating AD in June 2021 by the United States Food and Drug Administration. We systematically analyzed available trials to evaluate the efficacy and safety of aducanumab treating AD. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. We conducted an extensive literature search using the electronic databases MEDLINE through PubMed, EMBASE, Cochrane, Web of Science, and Scopus for suitable studies on aducanumab. We considered human clinical trials of aducanumab, assessing its efficacy and adverse effects in treating AD, excluding any experimental animal studies. We included three randomised controlled trials. Studies reported that aducanumab reduced brain amyloid-beta plaques in a time- and dose-dependent manner (dose-response, P < 0.05) and a slowed decline in cognition (22% reduction) in the high-dose treated group, difference of -0.39 versus placebo in Clinical Dementia Rating Scale Sum Boxes (95% CI, -0.69 to -0.09; P = 0.012) along with a reduced amyloid positron emission tomography standard uptake value ratio score (P < 0.001) and plasma p181-tau (phosphorylated tau) level. Amyloid-related imaging abnormality was reported as a serious adverse event and was profound in high-dose treated group (425/1029 in 10 mg/kg). Aducanumab has been reported to affect two main pathophysiologic hallmarks (Aß and tau) of AD. We suggest future studies addressing aducanumab's efficacy and safety to confirm that the benefit of this drug outweighs the risk.

Evaluating Treatment Efficacy by Combining Multiple Measures in Clinical Trial Applications.

A variety of clinical and laboratory measures can be used in clinical trials to assess the benefit of a new treatment over the standard of care. Data from clinical studies are often analyzed by combining individual outcomes into one primary outcome. That primary outcome is then referred to as a composite endpoint or a combined endpoint. We propose an analysis on the composite endpoint with Gehan's (1965) ranking approach where each subject in the treatment group is compared with each subject in the control group in a pair-wise manner. Our approach reduces computational time and complexity to construct a subject-level pairwise composite score. We develop a statistical testing procedure for the analysis of composite endpoints when using the hierarchical scores. In this article, we propose two tests (a parametric test and a non-parametric bootstrap procedure) for evaluating the effect of treatment. The proposed parametric test has an asymptotic F-distribution based on standard statistical assumptions. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods and to compare them with an existing method. We illustrate the methods using publicly available data from two clinical studies.

Classification of acute poisoning exposures with machine learning models derived from the National Poison Data System.

The primary aim of this pilot study was to develop a machine learning algorithm to predict and distinguish eight poisoning agents based on clinical symptoms. Data were used from the National Poison Data System from 2014 to 2018, for patients 0-89 years old with single-agent exposure to eight drugs or drug classes (acetaminophen, aspirin, benzodiazepines, bupropion, calcium channel blockers, diphenhydramine, lithium and sulfonylureas). Four classifier prediction models were applied to the data: logistic regression, LightGBM, XGBoost, and CatBoost. There were 201 031 cases used to develop and test the algorithms. Among the four models, accuracy ranged 77%-80%, with precision and F1 scores of 76%-80% and recall of 77%-78%. Overall specificity was 92% for all models. Accuracy was highest for identifying sulfonylureas, acetaminophen, benzodiazepines and diphenhydramine poisoning. F1 scores were highest for correctly classifying sulfonylureas, acetaminophen and benzodiazepine poisonings. Recall was highest for sulfonylureas, acetaminophen, and benzodiazepines, and lowest for bupropion. Specificity was >99% for models of sulfonylureas, calcium channel blockers, lithium and aspirin. For single-agent poisoning cases among the eight possible exposures, machine learning models based on clinical signs and symptoms moderately predicted the causal agent. CatBoost and LightGBM classifier models had the highest performance of those tested.

Evaluation of a menstrual hygiene intervention in urban and rural schools in Bangladesh: a pilot study.

Girls' menstrual experiences impact their social and educational participation, physical and psychological health. We conducted a pilot study to assess the acceptability and feasibility of a multi-component intervention intended to support menstruating girls; improve menstrual care knowledge, practices, and comfort; and increase school attendance.We conducted a pre/post evaluation of a 6-month pilot intervention in four schools (2 urban, 2 rural) in Dhaka, Bangladesh. We selected 527 schoolgirls (grades 5 to 10; aged 10 to 17 years) for a baseline survey and 528 girls at endline. The intervention included: 1) Menstrual Hygiene Management (MHM) packs- reusable cloth pads, underwear, carry bags and menstrual cycle tracking calendars, 2) education curriculum- pictorial flipcharts, puberty related-booklets, and teachers' training to deliver puberty and MHM sessions, 3) maintenance- improvements to school sanitation, provision of disposable pads in the school office, provision of chute disposal systems for disposable pads, and gender committees to promote a gender-friendly school environment and maintenance of intervention facilities. We estimated intervention uptake and intervention effect by calculating prevalence differences and 95% confidence intervals using fixed-effects logistic regression.The intervention uptake was more than 85% for most indicators; 100% reported receiving puberty education, 85% received MHM packs, and 92% received booklets. Reusable cloth pads uptake was 34% by endline compared with 0% at baseline. Knowledge about menstrual physiology and knowledge of recommended menstrual management practices significantly improved from baseline to endline. Reported improvements included more frequent changing of menstrual materials (4.2 times/day at endline vs. 3.4 times/day at baseline), increased use of recommended disposal methods (prevalence difference (PD): 8%; 95% Confidence Interval: 1, 14), and fewer staining incidents (PD: - 12%; 95% CI: - 22, - 1). More girls reported being satisfied with their menstrual materials (59% at endline vs. 46% at baseline, p < 0.005) and thought school facilities were adequate for menstrual management at endline compared to baseline (54% vs. 8%, p < 0.001). At endline, 64% girls disagreed/strongly disagreed that they felt anxious at school due to menstruation, compared to 33% at baseline (p < 0.001). Sixty-five percent girls disagreed/strongly disagreed about feeling distracted or trouble concentrating in class at endline, compared to 41% at baseline (p < 0.001). Self-reported absences decreased slightly (PD: - 8%; 95% CI: - 14, - 2).Uptake of cloth pads, improved maintenance and disposal of menstrual materials, and reduced anxiety at school suggest acceptability and feasibility of the intervention aiming to create a supportive school environment.

Livelihood challenges and healthcare-seeking behavior of fishermen amidst the COVID-19 pandemic in the Sundarbans mangrove forest of Bangladesh.

The outbreak of coronavirus disease (COVID-19) has posed significant challenges to human wellbeing and survival, particularly among groups of people such as the Sundarbans mangrove forest resource-dependent communities (SMFRDCs), and especially the fishermen in these communities, in developing countries like Bangladesh. It is therefore essential to explore the livelihood conditions, health status and care-seeking behavior of the fishermen in these communities during the ongoing pandemic. This study was carried out by applying mixed methods, including interviews and focus group discussion (FGD), in the three sub-districts of Khulna, Satkhira, and Bagerhat, which are in the southwestern region adjacent to the Sundarbans mangrove forest (SMF) of Bangladesh. Quantitative data were collected from 76 fishermen through telephone interviews, while 24 fishermen participated in three distinct focus group discussions. The findings suggest that the fishermen have experienced a reduction of income, as they have been barred from entering the SMF during the pandemic, which has gradually affected their number of trips to and stays at the forest as well as their catch of fisheries resources. The decline in demand in both regional and international markets has left the fishermen with only a handful of alternative ways to adjust to these unprecedented circumstances, such as borrowing money, selling household assets, and in some extreme cases marrying off young children to reduce the financial burden, as many are now jobless. Their financial hardship during the pandemic has affected their households' capacity to afford basic household necessities, including food, fuel, education, and health expenses. Subsequently, when these fishermen suffer ailments such as fever, cough, headache, and cold - the general symptoms of COVID-19 - they cannot seek medical assistance from trained doctors. Their financial constraints have compelled them to rely on indigenous knowledge, in particular village quack doctors, or in some cases to seek help from local pharmacies for modern medicine. Thus, the government should provide financial support and strengthen the local market value chain so that disadvantaged fishermen in SMFRDCs can adopt alternative livelihood opportunities. Furthermore, longitudinal research on the impacts of COVID-19 on livelihood, local adaptation strategies, health status, and care-seeking behavior is also strongly recommended.

Phase I Study of Venetoclax Plus Daratumumab and Dexamethasone, With or Without Bortezomib, in Patients With Relapsed or Refractory Multiple Myeloma With and Without t(11;14).

PURPOSE: Venetoclax is an oral BCL-2 inhibitor with single-agent activity in patients with relapsed or refractory multiple myeloma (RRMM) with t(11;14) translocation. Venetoclax efficacy in RRMM may be potentiated through combination with agents including bortezomib, dexamethasone, and daratumumab. METHODS: This phase I study (NCT03314181) evaluated venetoclax with daratumumab and dexamethasone (VenDd) in patients with t(11;14) RRMM and VenDd with bortezomib (VenDVd) in cytogenetically unselected patients with RRMM. Primary objectives included expansion-phase dosing, safety, and overall response rate. Secondary objectives included further safety analysis, progression-free survival, duration of response, time to progression, and minimal residual disease negativity. RESULTS: Forty-eight patients were enrolled, 24 each in parts 1 (VenDd) and 2 (VenDVd). There was one dose-limiting toxicity in part 1 (grade 3 febrile neutropenia, 800 mg VenDd). Common adverse events with VenDd and VenDVd included diarrhea (63% and 54%) and nausea (50% and 50%); grade ≥ 3 adverse events were observed in 88% in the VenDd group and 71% in the VenDVd group. One treatment-emergent death occurred in part 2 (sepsis) in the context of progressive disease, with no other infection-related deaths on study with medians of 20.9 and 20.4 months of follow-up in parts 1 and 2, respectively. The overall response rate was 96% with VenDd (all very good partial response or better [≥ VGPR]) and 92% with VenDVd (79% ≥ VGPR). The 18-month progression-free survival rate was 90.5% (95% CI, 67.0 to 97.5) with VenDd and 66.7% (95% CI, 42.5 to 82.5) with VenDVd. CONCLUSION: VenDd and VenDVd produced a high rate of deep and durable responses in patients with RRMM. These results support continued evaluation of venetoclax with daratumumab regimens to treat RRMM, particularly in those with t(11;14).

Efficacy of venetoclax plus rituximab for relapsed CLL: 5-year follow-up of continuous or limited- duration therapy.

We report long-term follow-up of the phase 1b study of venetoclax and rituximab (VenR) in patients with relapsed chronic lymphocytic leukemia (CLL), including outcomes with continuous or limited-duration therapy. Patients received venetoclax daily (200-600 mg) and rituximab over 6 months and then received venetoclax monotherapy. Patients achieving complete response (CR), CR with incomplete marrow recovery (CRi), or undetectable minimal residual disease (uMRD) assessed by flow cytometry (<10-4 cutoff) were allowed, but not required, to discontinue therapy, while remaining in the study and could be retreated with VenR upon progression. Median follow-up for all patients (N = 49) was 5.3 years. Five-year rates (95% CI) for overall survival, progression-free survival, and duration of response were 86% (72-94), 56% (40-70), and 58% (40-73), respectively. Of the 33 deep responders (CR/CRi or uMRD), 14 remained on venetoclax monotherapy (continuous therapy), and 19 stopped venetoclax therapy (limited-duration therapy) after a median of 1.4 years. Five-year estimates of ongoing response were similar between continuous (71%; 95% CI, 39-88) or limited-duration therapy (79% [49-93]). Six of 19 patients in the latter group had subsequent disease progression, all >2 years off venetoclax (range, 2.1-6.4). Four patients were retreated with VenR, with partial responses observed in the 3 evaluable to date. VenR induced deep responses that were highly durable with either continuous or limited-duration therapy. Retreatment with VenR induced responses in patients with CLL progression after discontinuing therapy. Continuous exposure to venetoclax in deep responders does not appear to provide incremental benefit.

Rumor surveillance in support of minimally invasive tissue sampling for diagnosing the cause of child death in low-income countries: A qualitative study.

In low-and middle-income countries, determining the cause of death of any given individual is impaired by poor access to healthcare systems, resource-poor diagnostic facilities, and limited acceptance of complete diagnostic autopsies. Minimally invasive tissue sampling (MITS), an innovative post-mortem procedure based on obtaining tissue specimens using fine needle biopsies suitable for laboratory analysis, is an acceptable proxy of the complete diagnostic autopsy, and thus could reduce the uncertainty of cause of death. This study describes rumor surveillance activities developed and implemented in Bangladesh, Mali, and Mozambique to identify, track and understand rumors about the MITS procedure. Our surveillance activities included observations and interviews with stakeholders to understand how rumors are developed and spread and to anticipate rumors in the program areas. We also engaged young volunteers, local stakeholders, community leaders, and study staff to report rumors being spread in the community after MITS launch. Through community meetings, we also managed and responded to rumors. When a rumor was reported, the field team purposively conducted interviews and group discussions to track, verify and understand the rumor. From July 2016 through April 2018, the surveillance identified several rumors including suspicions of organs being harvested or transplanted; MITS having been performed on a living child, and concerns related to disrespecting the body and mistrust related to the study purpose. These rumors, concerns, and cues of mistrust were passed by word of mouth. We managed the rumors by modifying the consent protocol and giving additional information and support to the bereaved family and to the community members. Rumor surveillance was critical for anticipating and readily identifying rumors and managing them. Setting up rumor surveillance by engaging community residents, stakeholders, and volunteers could be an essential part of any public health program where there is a need to identify and react in real-time to public concern.

Mixed metal zero-mode guides (ZMWs) for tunable fluorescence enhancement.

Zero-mode waveguides (ZMWs) are capable of modifying fluorescence emission through interactions with surface plasmon modes leading to either plasmon-enhanced fluorescence or quenching. Enhancement requires spectral overlap of the plasmon modes with the absorption or emission of the fluorophore. Thus, enhancement is limited to fluorophores in resonance with metals (e.g. Al, Au, Ag) used for ZMWs. The ability to tune interactions to match a wider range of fluorophores across the visible spectra would significantly extend the utility of ZMWs. We fabricated ZMWs composed of aluminum and gold individually and also in mixtures of three different ratios, (Al : Au; 75 : 25, 50 : 50, 25 : 75). We characterized the effect of mixed-metal ZMWs on single-molecule emission for a range fluorophores across the visible spectrum. Mixed metal ZMWs exhibited a shift in the spectral range where they exhibited the maximum fluorescence enhancement allowing us to match the emission of fluorophores that were nonresonant with single metal ZMWs. We also compared the effect of mixed-metal ZMWs on the photophysical properties of fluorescent molecules due to metal-molecule interactions. We quantified changes in fluorescence lifetimes and photostability that were dependent on the ratio of Au and Al. Tuning the enhancement properties of ZMWs by changing the ratio of Au and Al allowed us to match the fluorescence of fluorophores that emit in different regions of the visible spectrum.

If I do not have enough water, then how could I bring additional water for toilet cleaning?! Addressing water scarcity to promote hygienic use of shared toilets in Dhaka, Bangladesh.

OBJECTIVES: Provision of toilets is necessary but not sufficient to impact health as poor maintenance may impair toilet function and discourage their consistent use. Water in urban slums is both scarce and a prerequisite for toilet maintenance behaviours. We describe the development of behaviour change communications and selection of low-cost water storage hardware to facilitate adequate flushing among users of shared toilets. METHODS: We conducted nine focus group discussions and six ranking exercises with adult users of shared toilets (50 females, 35 males), then designed and implemented three pilot interventions to facilitate regular flushing and improve hygienic conditions of shared toilets. We conducted follow-up assessments 1 and 2 months post-pilot including nine in-depth interviews and three focus group discussions with adult residents (23 females, 15 males) and three landlords in the pilot communities. RESULTS: Periodic water scarcity was common in the study communities. Residents felt embarrassed to carry water for flushing. Reserving water adjacent to the shared toilet enabled slum residents to flush regularly. Signs depicting rules for toilet use empowered residents and landlords to communicate these expectations for flushing to transient tenants. Residents in the pilot reported improvements in cleanliness and reduced odour inside toilet cubicles. CONCLUSIONS: Our pilot demonstrates the potential efficacy of low-cost water storage and behaviour change communications to improve maintenance of and user satisfaction with shared toilets in urban slum settings.

A comparison of multiple testing adjustment methods with block-correlation positively-dependent tests.

In high dimensional data analysis (such as gene expression, spatial epidemiology, or brain imaging studies), we often test thousands or more hypotheses simultaneously. As the number of tests increases, the chance of observing some statistically significant tests is very high even when all null hypotheses are true. Consequently, we could reach incorrect conclusions regarding the hypotheses. Researchers frequently use multiplicity adjustment methods to control type I error rates-primarily the family-wise error rate (FWER) or the false discovery rate (FDR)-while still desiring high statistical power. In practice, such studies may have dependent test statistics (or p-values) as tests can be dependent on each other. However, some commonly-used multiplicity adjustment methods assume independent tests. We perform a simulation study comparing several of the most common adjustment methods involved in multiple hypothesis testing, under varying degrees of block-correlation positive dependence among tests.