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Lihua Li,1– 3 Meaghan S Cuerden,4 Bian Liu,1,3,5 Salimah Shariff,6 Arsh K Jain,4,6 Madhu Mazumdar1– 3 1Institute for Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA; 2Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA; 3Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; 4London Health Sciences Centre, London, Ontario, Canada; 5Institute for Translational Epidemiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; 6Institute for Clinical Evaluative Sciences, Toronto, Ontario, CanadaCorrespondence: Madhu MazumdarDepartment of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, Mount Sinai Hospital, 1425 Madison Avenue, New York, NY, USATel +1 212-659-1470Email Madhu.Mazumdar@mountsinai.orgIntroduction: Statistical methods to assess the impact of an intervention are increasingly used in clinical research settings. However, a comprehensive review of the methods geared toward practitioners is not yet available.Methods and Materials: We provide a comprehensive review of three methods to assess the impact of an intervention: difference-in-differences (DID), segmented regression of interrupted time series (ITS), and interventional autoregressive integrated moving average (ARIMA). We also compare the methods, and provide illustration of their use through three important healthcare-related applications.Results: In the first example, the DID estimate of the difference in health insurance coverage rates between expanded states and unexpanded states in the post-Medicaid expansion period compared to the pre-expansion period was 5.93 (95% CI, 3.99 to 7.89) percentage points. In the second example, a comparative segmented regression of ITS analysis showed that the mean imaging order appropriateness score in the emergency department at a tertiary care hospital exceeded that of the inpatient setting with a level change difference of 0.63 (95% CI, 0.53 to 0.73) and a trend change difference of 0.02 (95% CI, 0.01 to 0.03) after the introduction of a clinical decision support tool. In the third example, the results from an interventional ARIMA analysis show that numbers of creatinine clearance tests decreased significantly within months of the start of eGFR reporting, with a magnitude of drop equal to − 0.93 (95% CI, − 1.22 to − 0.64) tests per 100,000 adults and a rate of drop equal to 0.97 (95% CI, 0.95 to 0.99) tests per 100,000 per adults per month.Discussion: When choosing the appropriate method to model the intervention effect, it is necessary to consider the structure of the data, the study design, availability of an appropriate comparison group, sample size requirements, whether other interventions occur during the study window, and patterns in the data.Keywords: difference-in-difference, interrupted time series, segmented regression, autoregressive integrated moving average

The MMR vaccine as we know is a vital vaccine to protect against three disease-causing microbes- measles, mumps, and rubella. To commemorate 75 years of Indian independence, the present study delves into the achievement of Indian research and lists out articles retrieved from the Web of Science Core Collection database on the domain of MMR vaccine research. The data has been restricted to the publication from India, thereby, has throwing some understanding into the MRR vaccine research in India over the last 28 years- 1994 to 2021. The data have been compared based on scientometric analysis. Qualitative and quantitative analysis have also been taken into account in order to give a comparative insight into the research. The comparison was done based on citation data, usage count data, year of publication, journals, publication media, domains focussed on the papers, and type of document. Astonishingly, in 2021, the most number of papers were published, most of them have related MMR vaccine as a potential immunity developer against COVID-19 infection. A total of 43 articles were retrieved from the search, the numbers are quite big, and the highest citation among them being 99 which was published in 2014, which is quite impressive for such a short duration of time. The comparative study suggests a positive growth of MMR vaccine research in India. [ABSTRACT FROM AUTHOR]

Plant nutrients are essential for the production of healthy crops for the world's expanding population and thus, they are a vital component of sustainable agriculture. Increased crop production depends on the type of fertilizers used to supplement essential nutrients for plants. The nutrient level fertilizers provide depends on their nature-each type of fertilizer has its advantages and disadvantages concerning crop growth and soil fertility. The management of using fertilizer must aim to ensure both an enhanced and safeguarded environment. Thus, a balanced fertilization strategy must be implemented. An experiment was conducted under field conditions to assess the effects of combinations of bio-fertilizers on agronomic and quality criteria of Brassica juncea (brown mustard), Basella alba (climbing spinach), and Amaranthus dubius (red spinach). Randomized block design with three replicas were used for the study, one set with the application of fertilizers containing Azotobacter, Rhizobium, Sesbania, Bacillus subtilis, Bacillus cereus, Bacillus megaterium, Pseudomonas fluorescens and Glomus (Mycorrhizal inoculant)-under bio-fertilizer; another with a mixture of urea, Potassium Nitrate, Super Phosphate, Potassium Sulfate, and Maple EM solution as chemical fertilizer and a control (water). Results indicated that yield and other plant criteria like chlorophyll content and gel volume were enhanced in bio-fertilizer treated plants compared to the plants grown with chemical fertilizer and control. In general, the application of bio-fertilizer significantly increased leaf length by 16-50%, the total number of leaves by 50-80%, plant size 19.15-63.15%, and gel volume by 147% (approximately) in comparison with untreated plants. [ABSTRACT FROM AUTHOR]

Light at night has been implicated in health risks associated with night-shift work and circadian system disruption, but there are scant data on actual nighttime light exposures experienced by night-shift workers and how they affect melatonin levels. This study analysed salivary melatonin assays and calibrated personal light-exposure measurements obtained from a larger 20-week field study to explore the association between nocturnal melatonin levels and light exposures in 27 nurses working night shifts at four hospitals in southern New York and southern Indiana. Complete time-matched melatonin and light exposure data were available for 20 of the participants, who underwent three 2-week data collection periods (6 weeks total), each separated by six weeks. A mixed-effects model was used to quantify the adjusted association between melatonin levels and light exposures. No significant association was found between the measures after adjusting for age and years working night shifts (β = −6.8, p = 0.26). This study demonstrates that healthcare environments can provide sufficient light for visual tasks without affecting melatonin levels, a marker of the circadian system. Our research also highlights the value of personal light-measurement devices when examining the relationship between exposure to light at night, melatonin levels and the potential for circadian disruption. [ABSTRACT FROM AUTHOR]

Background: Spina bifida is a type of neural tube defect (NTD); NTDs are developmental malformations of the spinal cord that result from failure of neural tube closure during embryogenesis and are likely caused by interactions between genetic and environmental factors. Arsenic induces NTDs in animal models, and studies demonstrate that mice with genetic defects related to folate metabolism are more susceptible to arsenic's effects. We sought to determine whether 25 single-nucleotide polymorphisms (SNPs) in genes involved in folate and arsenic metabolism modified the associations between maternal arsenic exposure and risk of spina bifida (a common NTD) among a hospital-based case-control study population in Bangladesh., Methods: We used data from 262 mothers and 220 infants who participated in a case‒control study at the National Institutes of Neurosciences & Hospital and Dhaka Shishu Hospital in Dhaka, Bangladesh. Neurosurgeons assessed infants using physical examinations, review of imaging, and we collected histories using questionnaires. We assessed arsenic from mothers' toenails using inductively coupled plasma mass spectrometry (ICP-MS), and we genotyped participants using the Illumina Global Screening Array v1.0. We chose candidate genes and SNPs through a review of the literature. We assessed SNP-environment interactions using interaction terms and stratified models, and we assessed gene-environment interactions using interaction sequence/SNP-set kernel association tests (iSKAT)., Results: The median toenail arsenic concentration was 0.42 μg/g (interquartile range [IQR]: 0.27-0.86) among mothers of cases and 0.47 μg/g (IQR: 0.30-0.97) among mothers of controls. We found an two SNPs in the infants' AS3MT gene (rs11191454 and rs7085104) and one SNP in mothers' DNMT1 gene (rs2228611) were associated with increased odds of spina bifida in the setting of high arsenic exposure (rs11191454, OR 3.01, 95% CI: 1.28-7.09; rs7085104, OR 2.33, 95% CI: 1.20-4.and rs2228611, OR 2.11, 95% CI: 1.11-4.01), along with significant SNP-arsenic interactions. iSKAT analyses revealed significant interactions between mothers' toenail concentrations and infants' AS3MT and MTR genes (p = 0.02), and mothers' CBS gene (p = 0.05)., Conclusions: Our results support the hypothesis that arsenic increases spina bifida risk via interactions with folate and arsenic metabolic pathways and suggests that individuals in the population who have certain genetic polymorphisms in genes involved with arsenic and folate metabolism may be more susceptible than others to the arsenic teratogenicity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Competing Interests: Competing interests DT received research funding from Sobi, Sumitomo, Cogent Biosciences and Gilead and honoraria from Sobi, Novartis, AbbVie, PharmaEssentia, Sierra Oncology, GSK and Cogent Biosciences. CDD received honoraria from Abbvie, AstraZeneca, BMS, Genentech, GenMab, GSK, Immunogen, Notable Labs, Rigel, Schrodinger, and Servier and grant support from LLS Scholar in Research Award. TMK received research funding from AbbVie and Genentech and honoraria from AbbVie. FR received research funding from AbbVie and BMS and honoraria from AbbVie and BMS. AM received research funding from BMS, Incyte and Novartis. AA received research funding from Novartis, BMS, Onconova, Medimmune, Ariad, GSK, Celgene, Eisai, ALX Oncology, H3B Biomedicine/Hemavant. MK has received honoraria from Protagonist, Silence Therapeutics, Morphosys, Incyte, AbbVie and Kura. JF received research funding from Oryzon Genomics, Taiho Oncology, and Syros. RK received research funding from BMS and honoraria from Abbvie, BMS, DSI, Geron, Janssen, Jazz, PharmaEssentia, Rigel, Servio, Sobi, and Sumitomo. JM received research funding from Incyte, BMS, Novartis, Abbvie, Geron, Kartos, Karyopharm, Sobi and PharmaEssentia and honoraria from Incyte, BMS, Abbvie, Kartos, Geron, GSK, Roche, Merck, Pfizer, PharmaEssentia, MorphoSys, Novartis, Galecto, Sobi, Sumitomo, and Karyopharm. EP received research funding from Incyte, BMS, and Blueprint and honoraria from BMS, GSK, Sobi, Blueprint, Taiho, PharmaEssentia. DAS received research funding from Aprea and Jazz and honoraria from AbbVie, Aprea, Agios, Celyad, Froghorn, Gilead,Incyte, Intellisphere LLC, Kite, Megenta, Novartis, AvenCell, Astellas, BlueBird Bio, BMS, Dark Blue Therapeutics, Intellia, Jasper Therapeutics, Kite, Magenta Therapeutics, NKARTA, Novartis, Orbital Therapeutics, Rigel Pharmaceuticals, Shattuck Labs, Servier, Syndax, and Syros. MMP received research funding from Stemline, Kura Oncology, Solu Therapeutics, Epigenetix and Polaris Pharmaceuticals. GMB received research funding from IFM Therapeutics, Takeda Oncology, Solu Theraputics. The remaining of the authors have no potential competing interests to disclose. Ethics approval and consent to participate This study received approval by the Institutional Review Boards from all participating institutions and research was conducted in accordance with the Declaration of Helsinki. Given the retrospective nature of this analysis, informed consent was not required by local regulatory authorities.

Introduction: Hernias following iliac bone grafting are a rare but significant complication, with the earliest case reported in 1945. Repairing these hernias is challenging. Appropriate repair techniques are needed to minimise morbidity and recurrence. We present our experience with three cases of post-iliac graft hernia repair with mesh anchored to titanium mini-plates and a systematic review of current literature., Method: We conducted a systematic review of the literature in February 2024 on two online databases, PubMed®/MEDLINE and EMBASE, in accordance with PRISMA guidelines. Keywords used were "Hernia," "Iliac," and "Graft." Data on demographics, initial pathology, time to presentation, type of hernia repair, and outcome were collected. Studies not in English and related to other types of hernia were excluded., Results: We included 30 studies out of 751 results, spanning from 1975 to 2023. There were 40 reported cases of hernias post iliac bone grafting. The age distribution ranged from 37 to 88 years, with a median age of 60. The majority of patients (40 %) presented within one year. Fracture management, accounting for 19 cases (47.5 %), was the main indication for bone grafting. Mesh repair was performed in 31 cases (77.5 %). Seven cases (17.5 %) of recurrence were reported., Conclusion: Recurrence is a common complication in patients with post-iliac graft hernias. Open mesh repair is the most frequently performed surgery and involves various techniques. While titanium mini-plates as anchors enable a pre-peritoneal plane mesh repair, long-term follow-up and comparative studies are needed to evaluate its efficacy compared to simple mesh., Competing Interests: Competing interests The authors declare that they have no financial or non-financial interests that are directly or indirectly related to the work submitted for publication. There are no conflicts of interest to disclose., (Copyright © 2024 Royal College of Surgeons of Edinburgh (Scottish charity number SC005317) and Royal College of Surgeons in Ireland. Published by Elsevier Ltd. All rights reserved.)

Epigenetic modifications control gene expression and are essential for turning genes on and off to regulate and maintain differentiated cell types. Epigenetics are also modified by a multitude of environmental exposures, including diet and pollutants, allowing an individual's environment to influence gene expression and resultant phenotypes and clinical outcomes. These epigenetic modifications due to gene-environment interactions can also be transmitted across generations, raising the possibility that environmental influences that occurred in one generation may be transmitted beyond the second generation, exerting a long-lasting effect. In this review, we cover the known mechanisms of epigenetic modification acquisition, reprogramming and persistence, animal models and human studies used to understand multigenerational epigenetic transmission, and examples of environmentally induced epigenetic change and its transmission across generations. We highlight the importance of environmental health not only on the current population but also on future generations that will experience health outcomes transmitted through epigenetic inheritance., (© 2024. The Author(s).)

Objectives: The American Academy of Pediatrics recommends that children and adolescents with Down syndrome receive anticipatory guidance regarding development and behavior. However, few tools provide specific guidance on developmental norms for children with Down syndrome. Our objective was to estimate age ranges at which children and adolescents with Down syndrome achieve developmental milestones to facilitate developmental screening by pediatric practitioners., Methods: We used standardized questionnaires to obtain information from clinicians and caregivers of children with Down syndrome who received care at the Boston Children's Hospital Down Syndrome Program between March 2018 and March 2023. Data included information from 2599 visits for 842 individuals with Down syndrome ages 2 months to 24 years. We used mixed-effects logistic regressions to predict the probability of achieving 25 specific developmental milestones with 15%, 30%, 45%, 60%, 75%, and 90% probability as a function of age. We further stratified results by individuals' sex., Results: We present age norms for our study's population of people with Down syndrome for key milestones in academic, adaptive, language, and motor domains by calculating the ages at which milestone achievement was 75% probable. We then compare these norms to published norms for the general population., Conclusions: This study provides clinicians and families with age-based norms for achievement of key developmental milestones for children and adolescents with Down syndrome., (Copyright © 2024 by the American Academy of Pediatrics.)

Purpose: To investigate changes in breast cancer incidence rates associated with Medicaid expansion in California., Methods: We extracted yearly census tract-level population counts and cases of breast cancer diagnosed among women aged between 20 and 64 years in California during years 2010-2017. Census tracts were classified into low, medium and high groups according to their social vulnerability index (SVI). Using a difference-in-difference (DID) approach with Poisson regression models, we estimated the incidence rate, incidence rate ratio (IRR) during the pre- (2010-2013) and post-expansion periods (2014-2017), and the relative IRR (DID estimates) across three groups of neighborhoods., Results: Prior to the Medicaid expansion, the overall incidence rate was 93.61, 122.03, and 151.12 cases per 100,000 persons among tracts with high, medium, and low-SVI, respectively; and was 96.49, 122.07, and 151.66 cases per 100,000 persons during the post-expansion period, respectively. The IRR between high and low vulnerability neighborhoods was 0.62 and 0.64 in the pre- and post-expansion period, respectively, and the relative IRR was 1.03 (95% CI 1.00 to 1.06, p = 0.026). In addition, significant DID estimate was only found for localized breast cancer (relative IRR = 1.05; 95% CI, 1.01 to 1.09, p = 0.049) between high and low-SVI neighborhoods, not for regional and distant cancer stage., Conclusions: The Medicaid expansion had differential impact on breast cancer incidence across neighborhoods in California, with the most pronounced increase found for localized cancer stage in high-SVI neighborhoods. Significant pre-post change was only found for localized breast cancer between high and low-SVI neighborhoods., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Introduction: Six hospitals within the New York City public hospital system implemented the Consult for Addiction Treatment and Care in Hospitals (CATCH) program, an interprofessional addiction consult service. A stepped-wedge cluster randomized controlled trial tested the effectiveness of CATCH for increasing initiation and engagement in post-discharge medication for opioid use disorder (MOUD) treatment among hospital patients with opioid use disorder (OUD). The objective of this study was to identify facility characteristics that were associated with stronger performance of CATCH., Methods: This study used a mixed methods multiple-case study design. The six hospitals in the CATCH evaluation were each assigned a case rating according to intervention reach. Reach was considered high if ≥50 % of hospitalized OUD patients received an MOUD order. Cross-case rating comparison identified attributes of high-performing hospitals and inductive and deductive approaches were used to identify themes., Results: Higher-performing hospitals exhibited attributes that were generally absent in lower-performing hospitals, including (1) complete medical provider staffing; (2) designated office space and resources for CATCH; (3) existing integrated OUD treatment resources; and (4) limited overlap between the implementation period and COVID-19 pandemic., Conclusions: Hospitals with attributes indicative of awareness and integration of OUD services into general care were generally higher performing than hospitals that had siloed OUD treatment programs. Future implementations of addiction consult services may benefit from an increased focus on hospital- and community-level buy-in and efforts to integrate MOUD treatment into general care., Competing Interests: Declaration of competing interest None., (Copyright © 2024. Published by Elsevier Inc.)

Arsenic is associated with lung disease and experimental models suggest that arsenic-induced degradation of the chloride channel CFTR (cystic fibrosis transmembrane conductance regulator) is a mechanism of arsenic toxicity. We examined associations between arsenic exposure, sweat chloride concentration (measure of CFTR function), and pulmonary function among 285 adults in Bangladesh. Participants with sweat chloride ≥ 60 mmol/L had higher arsenic exposures than those with sweat chloride < 60 mmol/L (water: median 77.5 μg/L versus 34.0 μg/L, p = 0.025; toenails: median 4.8 μg/g versus 3.7 μg/g, p = 0.024). In linear regression models, a one-unit μg/g increment in toenail arsenic was associated with a 0.59 mmol/L higher sweat chloride concentration, p < 0.001. We found that toenail arsenic concentration was associated with increased odds of airway obstruction (OR: 1.97, 95%: 1.06, 3.67, p = 0.03); however, sweat chloride concentration did not mediate this association. Our findings suggest that sweat chloride concentration may be a novel biomarker for arsenic exposure and also that arsenic likely acts on the lung through mechanisms other than CFTR dysfunction.

Importance: Medications for opioid use disorder (MOUD) are highly effective, but only 22% of individuals in the US with opioid use disorder receive them. Hospitalization potentially provides an opportunity to initiate MOUD and link patients to ongoing treatment., Objective: To study the effectiveness of interprofessional hospital addiction consultation services in increasing MOUD treatment initiation and engagement., Design, Setting, and Participants: This pragmatic stepped-wedge cluster randomized implementation and effectiveness (hybrid type 1) trial was conducted in 6 public hospitals in New York, New York, and included 2315 adults with hospitalizations identified in Medicaid claims data between October 2017 and January 2021. Data analysis was conducted in December 2023. Hospitals were randomized to an intervention start date, and outcomes were compared during treatment as usual (TAU) and intervention conditions. Bayesian analysis accounted for the clustering of patients within hospitals and open cohort nature of the study. The addiction consultation service intervention was compared with TAU using posterior probabilities of model parameters from hierarchical logistic regression models that were adjusted for age, sex, and study period. Eligible participants had an admission or discharge diagnosis of opioid use disorder or opioid poisoning/adverse effects, were hospitalized at least 1 night in a medical/surgical inpatient unit, and were not receiving MOUD before hospitalization., Interventions: Hospitals implemented an addiction consultation service that provided inpatient specialty care for substance use disorders. Consultation teams comprised a medical clinician, social worker or addiction counselor, and peer counselor., Main Outcomes and Measures: The dual primary outcomes were (1) MOUD treatment initiation during the first 14 days after hospital discharge and (2) MOUD engagement for the 30 days following initiation., Results: Of 2315 adults, 628 (27.1%) were female, and the mean (SD) age was 47.0 (12.4) years. Initiation of MOUD was 11.0% in the Consult for Addiction Treatment and Care in Hospitals (CATCH) program vs 6.7% in TAU, engagement was 7.4% vs 5.3%, respectively, and continuation for 6 months was 3.2% vs 2.4%. Patients hospitalized during CATCH had 7.96 times higher odds of initiating MOUD (log-odds ratio, 2.07; 95% credible interval, 0.51-4.00) and 6.90 times higher odds of MOUD engagement (log-odds ratio, 1.93; 95% credible interval, 0.09-4.18)., Conclusions: This randomized clinical trial found that interprofessional addiction consultation services significantly increased postdischarge MOUD initiation and engagement among patients with opioid use disorder. However, the observed rates of MOUD initiation and engagement were still low; further efforts are still needed to improve hospital-based and community-based services for MOUD treatment., Trial Registration: ClinicalTrials.gov Identifier: NCT03611335.

Background: Arsenic has been associated with diabetes and impaired glucose tolerance in many studies, although some reports have shown null findings., Methods: We conducted a cross-sectional study among 300 adults in Bangladesh. Participants were randomly selected from a roster of 1800 people who previously participated in studies of arsenic and skin lesions. We measured fasting glucose and insulin levels. We assessed drinking water arsenic concentration using graphite furnace atomic absorption spectrophotometry (GF-AAS) and toenail arsenic concentration using inductively coupled mass spectrometry (ICP-MS). We ran covariant-adjusted, linear regression and spline models to examine associations of arsenic concentrations with the homeostatic model assessment of insulin resistance (HOMA-IR), a marker of insulin resistance, and HOMA of beta-cell function (HOMA-β), a marker of beta-cell function., Results: Among 285 participants with complete data, the median (IQR) arsenic concentration was 4.0 (6.9) μg/g in toenails and 39.0 (188.5) μg/L in drinking water. Arsenic concentrations were not associated with insulin resistance or beta-cell function. HOMA-IR was 0.67% lower and HOMA-β was 0.28% lower per µg/g increment in toenail arsenic, but these effect estimates were small, and confidence intervals crossed the null value., Conclusions: Although arsenic exposure has been associated with diabetes, we found no evidence of an adverse effect on insulin resistance or beta-cell function., Competing Interests: The authors declare that they have no conflicts of interest with regard to the content of this report., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved.)

Importance: Machine learning has potential to transform cancer care by helping clinicians prioritize patients for serious illness conversations. However, models need to be evaluated for unequal performance across racial groups (ie, racial bias) so that existing racial disparities are not exacerbated., Objective: To evaluate whether racial bias exists in a predictive machine learning model that identifies 180-day cancer mortality risk among patients with solid malignant tumors., Design, Setting, and Participants: In this cohort study, a machine learning model to predict cancer mortality for patients aged 21 years or older diagnosed with cancer between January 2016 and December 2021 was developed with a random forest algorithm using retrospective data from the Mount Sinai Health System cancer registry, Social Security Death Index, and electronic health records up to the date when databases were accessed for cohort extraction (February 2022)., Exposure: Race category., Main Outcomes and Measures: The primary outcomes were model discriminatory performance (area under the receiver operating characteristic curve [AUROC], F1 score) among each race category (Asian, Black, Native American, White, and other or unknown) and fairness metrics (equal opportunity, equalized odds, and disparate impact) among each pairwise comparison of race categories. True-positive rate ratios represented equal opportunity; both true-positive and false-positive rate ratios, equalized odds; and the percentage of predictive positive rate ratios, disparate impact. All metrics were estimated as a proportion or ratio, with variability captured through 95% CIs. The prespecified criterion for the model's clinical use was a threshold of at least 80% for fairness metrics across different racial groups to ensure the model's prediction would not be biased against any specific race., Results: The test validation dataset included 43 274 patients with balanced demographics. Mean (SD) age was 64.09 (14.26) years, with 49.6% older than 65 years. A total of 53.3% were female; 9.5%, Asian; 18.9%, Black; 0.1%, Native American; 52.2%, White; and 19.2%, other or unknown race; 0.1% had missing race data. A total of 88.9% of patients were alive, and 11.1% were dead. The AUROCs, F1 scores, and fairness metrics maintained reasonable concordance among the racial subgroups: the AUROCs ranged from 0.75 (95% CI, 0.72-0.78) for Asian patients and 0.75 (95% CI, 0.73-0.77) for Black patients to 0.77 (95% CI, 0.75-0.79) for patients with other or unknown race; F1 scores, from 0.32 (95% CI, 0.32-0.33) for White patients to 0.40 (95% CI, 0.39-0.42) for Black patients; equal opportunity ratios, from 0.96 (95% CI, 0.95-0.98) for Black patients compared with White patients to 1.02 (95% CI, 1.00-1.04) for Black patients compared with patients with other or unknown race; equalized odds ratios, from 0.87 (95% CI, 0.85-0.92) for Black patients compared with White patients to 1.16 (1.10-1.21) for Black patients compared with patients with other or unknown race; and disparate impact ratios, from 0.86 (95% CI, 0.82-0.89) for Black patients compared with White patients to 1.17 (95% CI, 1.12-1.22) for Black patients compared with patients with other or unknown race., Conclusions and Relevance: In this cohort study, the lack of significant variation in performance or fairness metrics indicated an absence of racial bias, suggesting that the model fairly identified cancer mortality risk across racial groups. It remains essential to consistently review the model's application in clinical settings to ensure equitable patient care.

Objective: Reports on the management and survival of children with myelomeningocele defects in Bangladesh are limited. This study describes the characteristics and outcomes of these children, focusing on the timing of surgical repair and factors affecting survival., Methods: We enrolled patients with myelomeningoceles in a case-control study on arsenic exposure and spina bifida in Bangladesh. Cases were subsequently followed at regular intervals to assess survival. Demographic, clinical, and surgical characteristics were reviewed. Univariate tests identified factors affecting survival., Results: Between 2016 and 2022, we enrolled 272 patients with myelomeningocele. Postnatal surgical repair was performed in 63% of cases. However, surgery within 5 days after birth was infrequent (<10%) due to delayed presentation, and there was a high rate (29%) of preoperative deaths. Surgical repair significantly improved patient survival (P < 0.0001). Older age at time of surgery was also associated with improved survival rates, which most likely represents that those who survived to older ages prior to surgery accommodated better with their lesions. Patients who presented with ruptured lesions had lower survival rates., Conclusions: Timely neurosurgical repair of myelomeningoceles in Bangladesh is hindered by late patient presentation, resulting in a high preoperative patient death rate. Neurosurgical intervention remains a significant predictor of survival. Increased access to neurosurgical care and education of families and non-neurosurgical providers on the need for timely surgical intervention are important for improving the survival of infants with myelomeningoceles., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Introduction: With increasing tobacco product varieties, understanding tobacco use (TU) profiles and their associations with tobacco dependence (TD) has also become increasingly challenging., Aims and Methods: We aimed to identify TU profiles and their associations with TD over time, and to identify subgroups with high risk of TD. We included 3463 adult recent tobacco users who had complete TU and TD data across waves 1-4 of the Population Assessment of Tobacco and Health (PATH) study. We used a composite index of TD and a summed TD score from an established 16-item TD measure. We applied a latent class analysis to identify TU profiles based on participants' usage of eight common tobacco product groups at each survey wave and to check the stability of the TU profiles over time. We then used generalized estimating equations regressions to evaluate the longitudinal TU-TD association, adjusting for potential confounders., Results: We identified three distinct TU profiles that remained consistent across four survey waves: Dominant cigarette users (62%-68%), poly users with high propensity of using traditional cigarettes, e-cigarettes, and cigars (24%-31%), and dominant smokeless product users (7%-9%). Covariate-adjusted models showed that TD was significantly lower among the poly users and the dominant smokeless users, compared to that among the dominant cigarette users., Conclusions: Both TU profiles and their associations with TD were stable over time at the population level. Poly users and smokeless product users were consistently associated with lower TD than cigarette-dominant users, suggesting the need for tailored tobacco cessation interventions for users with different TU profiles., Implications: The finding of consistent TU profiles across four survey waves extends the current literature in capturing TU patterns in an evolving tobacco product landscape. The finding of the overall higher level of TD among the cigarette-dominant users compared to the other TU latent profiles (the Cig+eCig+Cigar dominant poly users and the dominant smokeless product users) can help identify high-risk groups for potential interventions. Our application of innovative statistical methods to high-quality longitudinal data from the PATH study helps improve the understanding of the dynamic TU-TD relationship over time., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: Spina bifida, a developmental malformation of the spinal cord, is associated with high rates of mortality and disability. Although folic acid-based preventive strategies have been successful in reducing rates of spina bifida, some areas continue to be at higher risk because of chemical exposures. Bangladesh has high arsenic exposures through contaminated drinking water and high rates of spina bifida. This study examines the relationships between mother's arsenic exposure, folic acid, and spina bifida risk in Bangladesh., Methods: We conducted a hospital-based case-control study at the National Institute of Neurosciences & Hospital (NINS&H) in Dhaka, Bangladesh, between December 2016 and December 2022. Cases were infants under age one year with spina bifida and further classified by a neurosurgeon and imaging. Controls were drawn from children seen at NINS&H and nearby Dhaka Shishu Hospital. Mothers reported folic acid use during pregnancy, and we assessed folate status with serum assays. Arsenic exposure was estimated in drinking water using graphite furnace atomic absorption spectrophotometry (GF-AAS) and in toenails using inductively coupled plasma mass spectrometry (ICP-MS). We used logistic regression to examine the associations between arsenic and spina bifida. We used stratified models to examine the associations between folic acid and spina bifida at different levels of arsenic exposure., Results: We evaluated data from 294 cases of spina bifida and 163 controls. We did not find a main effect of mother's arsenic exposure on spina bifida risk. However, in stratified analyses, folic acid use was associated with lower odds of spina bifida (adjusted odds ratio [OR]: 0.50, 95% confidence interval [CI]: 0.25-1.00, p = 0.05) among women with toenail arsenic concentrations below the median value of 0.46 µg/g, and no association was seen among mothers with toenail arsenic concentrations higher than 0.46 µg/g (adjusted OR: 1.09, 95% CI: 0.52-2.29, p = 0.82)., Conclusions: Mother's arsenic exposure modified the protective association of folic acid with spina bifida. Increased surveillance and additional preventive strategies, such as folic acid fortification and reduction of arsenic, are needed in areas of high arsenic exposure., (© 2024. The Author(s).)

Background: Malnutrition is associated with increased morbidity, mortality, and healthcare costs. Early detection is important for timely intervention. This paper assesses the ability of a machine learning screening tool (MUST-Plus) implemented in registered dietitian (RD) workflow to identify malnourished patients early in the hospital stay and to improve the diagnosis and documentation rate of malnutrition., Methods: This retrospective cohort study was conducted in a large, urban health system in New York City comprising six hospitals serving a diverse patient population. The study included all patients aged ≥ 18 years, who were not admitted for COVID-19 and had a length of stay of ≤ 30 days., Results: Of the 7736 hospitalisations that met the inclusion criteria, 1947 (25.2%) were identified as being malnourished by MUST-Plus-assisted RD evaluations. The lag between admission and diagnosis improved with MUST-Plus implementation. The usability of the tool output by RDs exceeded 90%, showing good acceptance by users. When compared pre-/post-implementation, the rate of both diagnoses and documentation of malnutrition showed improvement., Conclusion: MUST-Plus, a machine learning-based screening tool, shows great promise as a malnutrition screening tool for hospitalised patients when used in conjunction with adequate RD staffing and training about the tool. It performed well across multiple measures and settings. Other health systems can use their electronic health record data to develop, test and implement similar machine learning-based processes to improve malnutrition screening and facilitate timely intervention., (© 2024 The British Dietetic Association Ltd.)

Background: Black sexual minority men and Black transgender women (BSMM/BTW) experience disproportionate levels of HIV/STI-related risk factors as well as police harassment (PH). PH is linked to psychiatric risk and could play a role in substance use, sexual risk behavior, and HIV/STI risk., Methods: We used data from the HIV Prevention Trials Network 061(HPTN 061) study to examine associations between PH and HIV/STI-related outcomes. Using PH exposure measured at baseline and 6-month study visits, we examined an ordinal exposure (PH reported at both visits, PH reported at either visit, versus PH reported at neither baseline nor 6 months) and a binary exposure of persistent PH reported at both visits (yes versus no). We estimate risk ratios (RR) for associations between PH and depression, use of alcohol and methamphetamine, multiple partnerships, condomless sex, and syphilis., Results: Persistent PH (binary) was associated with a 20% or greater increase in the risk of depression (RR, 1.26 (1.07, 1.47)) and multiple partnerships (RR, 1.20 (1.05, 1.39)). There was evidence that ordinal PH was associated with elevated risk of alcohol use (RR, 1.17 (1.00, 1.36)); the point estimate for the association between persistent PH and alcohol use was similar but the imprecision was greater (RR, 1.16 (0.95, 1.42))., Conclusion: PH may influence not only mental health but also behavioral risks that contribute to HIV/STI among BSMM/BTW, highlighting the potential wide-ranging and downstream effects of PH on health. Further research is required to confirm associations and elucidate pathways through which PH may influence HIV/STI among BSMM/BTW., (© 2024. W. Montague Cobb-NMA Health Institute.)

Background: The stepped-wedge cluster randomized trial (SW-CRT) design has become popular in healthcare research. It is an appealing alternative to traditional cluster randomized trials (CRTs) since the burden of logistical issues and ethical problems can be reduced. Several approaches for sample size determination for the overall treatment effect in the SW-CRT have been proposed. However, in certain situations we are interested in examining the heterogeneity in treatment effect (HTE) between groups instead. This is equivalent to testing the interaction effect. An important example includes the aim to reduce racial disparities through healthcare delivery interventions, where the focus is the interaction between the intervention and race. Sample size determination and power calculation for detecting an interaction effect between the intervention status variable and a key covariate in the SW-CRT study has not been proposed yet for binary outcomes., Methods: We utilize the generalized estimating equation (GEE) method for detecting the heterogeneity in treatment effect (HTE). The variance of the estimated interaction effect is approximated based on the GEE method for the marginal models. The power is calculated based on the two-sided Wald test. The Kauermann and Carroll (KC) and the Mancl and DeRouen (MD) methods along with GEE (GEE-KC and GEE-MD) are considered as bias-correction methods., Results: Among three approaches, GEE has the largest simulated power and GEE-MD has the smallest simulated power. Given cluster size of 120, GEE has over 80% statistical power. When we have a balanced binary covariate (50%), simulated power increases compared to an unbalanced binary covariate (30%). With intermediate effect size of HTE, only cluster sizes of 100 and 120 have more than 80% power using GEE for both correlation structures. With large effect size of HTE, when cluster size is at least 60, all three approaches have more than 80% power. When we compare an increase in cluster size and increase in the number of clusters based on simulated power, the latter has a slight gain in power. When the cluster size changes from 20 to 40 with 20 clusters, power increases from 53.1% to 82.1% for GEE; 50.6% to 79.7% for GEE-KC; and 48.1% to 77.1% for GEE-MD. When the number of clusters changes from 20 to 40 with cluster size of 20, power increases from 53.1% to 82.1% for GEE; 50.6% to 81% for GEE-KC; and 48.1% to 79.8% for GEE-MD., Conclusions: We propose three approaches for cluster size determination given the number of clusters for detecting the interaction effect in SW-CRT. GEE and GEE-KC have reasonable operating characteristics for both intermediate and large effect size of HTE., (© 2024. The Author(s).)

Background: Human studies of genetic risk factors for neural tube defects, severe birth defects associated with long-term health consequences in surviving children, have predominantly been restricted to a subset of candidate genes in specific biological pathways including folate metabolism., Methods: In this study, we investigated the association of genetic variants spanning the genome with risk of spina bifida (i.e., myelomeningocele and meningocele) in a subset of families enrolled from December 2016 through December 2022 in a case-control study in Bangladesh, a population often underrepresented in genetic studies. Saliva DNA samples were analyzed using the Illumina Global Screening Array. We performed genetic association analyses to compare allele frequencies between 112 case and 121 control children, 272 mothers, and 128 trios., Results: In the transmission disequilibrium test analyses with trios only, we identified three novel exonic spina bifida risk loci, including rs140199800 (SULT1C2, p = 1.9 × 10 -7 ), rs45580033 (ASB2, p = 4.2 × 10 -10 ), and rs75426652 (LHPP, p = 7.2 × 10 -14 ), after adjusting for multiple hypothesis testing. Association analyses comparing cases and controls, as well as models that included their mothers, did not identify genome-wide significant variants., Conclusions: This study identified three novel single nucleotide polymorphisms involved in biological pathways not previously associated with neural tube defects. The study warrants replication in larger groups to validate findings and to inform targeted prevention strategies., (© 2024 Wiley Periodicals LLC.)

Incarceration can lead to different risk behaviors often due to increased distress and disruption of social networks. It is not well known, however, how these associations may differ by age. In this study, we measure age differences in longitudinal associations between incarceration and substance use, sex risk, and sexually transmitted infection (STI) among Black sexual minority men and Black transgender women (BSMM/BTW). We recruited BSMM/BTW from 2009 to 2011 that were part of the HIV Prevention Trials Network 061 study. We compared those less than 30 years old ( n = 375) to those 30 years old or greater ( n = 794) examining substance use, sex risk, and STI infection stratified by age. Logistic regression with inverse probability weighting was used for the statistical analysis. Approximately 59% of the sample reported incarceration history. In adjusted analysis, incarceration was more strongly associated with alcohol use and stimulant use among older individuals as was sexual risk behaviors including buying and selling sex. Concurrent partnerships were associated with the younger age groups. STI incidence was associated with younger individuals while associations with HIV infection were similar for the two age groups. Understanding differences in substance use and STI risk among age cohorts is imperative to the design and implementation of re-entry programs. Younger BSMM/BTW participating in re-entry support programs may benefit in particular from HIV/STI prevention and care efforts, while post-release substance abuse treatment and harm reduction programs should target older individuals with continued substance abuse., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: Early prediction of the need for invasive mechanical ventilation (IMV) in patients hospitalized with COVID-19 symptoms can help in the allocation of resources appropriately and improve patient outcomes by appropriately monitoring and treating patients at the greatest risk of respiratory failure. To help with the complexity of deciding whether a patient needs IMV, machine learning algorithms may help bring more prognostic value in a timely and systematic manner. Chest radiographs (CXRs) and electronic medical records (EMRs), typically obtained early in patients admitted with COVID-19, are the keys to deciding whether they need IMV., Objective: We aimed to evaluate the use of a machine learning model to predict the need for intubation within 24 hours by using a combination of CXR and EMR data in an end-to-end automated pipeline. We included historical data from 2481 hospitalizations at The Mount Sinai Hospital in New York City., Methods: CXRs were first resized, rescaled, and normalized. Then lungs were segmented from the CXRs by using a U-Net algorithm. After splitting them into a training and a test set, the training set images were augmented. The augmented images were used to train an image classifier to predict the probability of intubation with a prediction window of 24 hours by retraining a pretrained DenseNet model by using transfer learning, 10-fold cross-validation, and grid search. Then, in the final fusion model, we trained a random forest algorithm via 10-fold cross-validation by combining the probability score from the image classifier with 41 longitudinal variables in the EMR. Variables in the EMR included clinical and laboratory data routinely collected in the inpatient setting. The final fusion model gave a prediction likelihood for the need of intubation within 24 hours as well., Results: At a prediction probability threshold of 0.5, the fusion model provided 78.9% (95% CI 59%-96%) sensitivity, 83% (95% CI 76%-89%) specificity, 0.509 (95% CI 0.34-0.67) F 1 -score, 0.874 (95% CI 0.80-0.94) area under the receiver operating characteristic curve (AUROC), and 0.497 (95% CI 0.32-0.65) area under the precision recall curve (AUPRC) on the holdout set. Compared to the image classifier alone, which had an AUROC of 0.577 (95% CI 0.44-0.73) and an AUPRC of 0.206 (95% CI 0.08-0.38), the fusion model showed significant improvement (P<.001). The most important predictor variables were respiratory rate, C-reactive protein, oxygen saturation, and lactate dehydrogenase. The imaging probability score ranked 15th in overall feature importance., Conclusions: We show that, when linked with EMR data, an automated deep learning image classifier improved performance in identifying hospitalized patients with severe COVID-19 at risk for intubation. With additional prospective and external validation, such a model may assist risk assessment and optimize clinical decision-making in choosing the best care plan during the critical stages of COVID-19., (©Kim-Anh-Nhi Nguyen, Pranai Tandon, Sahar Ghanavati, Satya Narayana Cheetirala, Prem Timsina, Robert Freeman, David Reich, Matthew A Levin, Madhu Mazumdar, Zahi A Fayad, Arash Kia. Originally published in JMIR Formative Research (https://formative.jmir.org), 26.10.2023.)

Background: The National Comprehensive Cancer Network suggested that older women with low-risk breast cancer (LRBC; i.e., early-stage, node-negative, and estrogen receptor-positive) could omit adjuvant radiation treatment (RT) after breast-conserving surgery (BCS) if they were treated with hormone therapy. However, the association between RT omission and breast cancer-specific mortality among older women with comorbidity is not fully known., Methods: 1105 older women (≥65 years) with LRBC in 1998-2012 were queried from the Surveillance, Epidemiology, and End Results-Medicare Health Outcomes Survey data resource and were followed up through July 2018. Latent class analysis was performed to identify comorbidity burden classes. A propensity score-based inverse probability of treatment weighting (IPTW) was applied to Cox regression models to obtain subdistribution hazard ratios (HRs) and 95% CI for cancer-specific mortality considering other causes of death as competing risks, overall and separately by comorbidity burden class., Results: Three comorbidity burden (low, moderate, and high) groups were identified. A total of 318 deaths (47 cancer-related) occurred. The IPTW-adjusted Cox regression analysis showed that RT omission was not associated with short-term, 5- and 10-year cancer-specific death (p = 0.202 and p = 0.536, respectively), regardless of comorbidity burden. However, RT omission could increase the risk of long-term cancer-specific death in women with low comorbidity burden (HR = 1.98, 95% CI = 1.17, 3.33), which warrants further study., Conclusions: Omission of RT after BCS is not associated with an increased risk of cancer-specific death and is deemed a reasonable treatment option for older women with moderate to high comorbidity burden., (© 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Objective: Evaluate associations between racialized and homophobia-based police harassment (RHBPH) and healthcare distrust and utilization among Black Sexual Minority Men (BSMM)., Methods: We utilized data from a longitudinal cohort study from HIV Prevention Trials Network (HPTN) 061 with baseline, six and 12 month follow-up assessments. Using multivariable analysis, we evaluated associations between RHBPH and healthcare distrust and utilization reported at the 6 and 12 month visits., Results: Of 1553 BSMM present at baseline, 1160 were available at six-month follow-up. In multivariable analysis, increasing frequency of RHBPH was associated with increasing levels of distrust in healthcare providers (aOR 1.31, 95% CI: 1.00, 1.74) and missing 50% or more of healthcare visits at six-month follow-up (aOR 1.93, 95% CI: 1.09, 3.43)., Conclusions: Recent experiences of RHBPH are associated with reduced trust in and access to healthcare among BSMM, with more frequent RHBPH associated with greater vulnerability., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Feelemyer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Incarceration among Black sexual minority men and Black transgender women (BSMM/BTW) is disproportionately high in the United States. Limited research has documented the disruptive effect of incarceration on sexual networks and sexual partnership exchange among BSMM/BTW. We estimate the influence of incarceration on selling sex and mediating pathways among 1169 BSMM/BTW enrolled in the HIV Prevention Trials Network (HPTN) 061 cohort to assess this relationship. Mediators investigated were social support, violence, illicit drug use, and distress due to experienced racism and homophobia. During the 6 months following baseline, 14% of the cohort was incarcerated, including 24% of BTW. After adjustment, recent incarceration was associated with 1.57 (95% CI 1.02, 2.42) times the risk of subsequently selling sex. The hypothesized mediators together explained 25% of the relationship, with an indirect effect risk ratio of 1.09 (95% CI 0.97, 1.24). Our results document an association and call for more research investigating mechanisms., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Machine learning (ML)-based clinical decision support systems (CDSS) are popular in clinical practice settings but are often criticized for being limited in usability, interpretability, and effectiveness. Evaluating the implementation of ML-based CDSS is critical to ensure CDSS is acceptable and useful to clinicians and helps them deliver high-quality health care. Malnutrition is a common and underdiagnosed condition among hospital patients, which can have serious adverse impacts. Early identification and treatment of malnutrition are important., Objective: This study aims to evaluate the implementation of an ML tool, Malnutrition Universal Screening Tool (MUST)-Plus, that predicts hospital patients at high risk for malnutrition and identify best implementation practices applicable to this and other ML-based CDSS., Methods: We conducted a qualitative postimplementation evaluation using in-depth interviews with registered dietitians (RDs) who use MUST-Plus output in their everyday work. After coding the data, we mapped emergent themes onto select domains of the nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework., Results: We interviewed 17 of the 24 RDs approached (71%), representing 37% of those who use MUST-Plus output. Several themes emerged: (1) enhancements to the tool were made to improve accuracy and usability; (2) MUST-Plus helped identify patients that would not otherwise be seen; perceived usefulness was highest in the original site; (3) perceived accuracy varied by respondent and site; (4) RDs valued autonomy in prioritizing patients; (5) depth of tool understanding varied by hospital and level; (6) MUST-Plus was integrated into workflows and electronic health records; and (7) RDs expressed a desire to eventually have 1 automated screener., Conclusions: Our findings suggest that continuous involvement of stakeholders at new sites given staff turnover is vital to ensure buy-in. Qualitative research can help identify the potential bias of ML tools and should be widely used to ensure health equity. Ongoing collaboration among CDSS developers, data scientists, and clinical providers may help refine CDSS for optimal use and improve the acceptability of CDSS in the clinical context., (©Melanie Besculides, Madhu Mazumdar, Sydney Phlegar, Robert Freeman, Sara Wilson, Himanshu Joshi, Arash Kia, Ksenia Gorbenko. Originally published in JMIR Formative Research (https://formative.jmir.org), 13.07.2023.)