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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. Key points/Highlights: Malnutrition is prevalent among hospitalised patients and frequently goes unrecognised, with the potential for severe sequelae. Accurate diagnosis, documentation and treatment of malnutrition have the potential of having a positive impact on morbidity rate, mortality rate, length of inpatient stay, readmission rate and hospital revenue. The tool's successful application highlights its potential to optimise malnutrition screening in healthcare systems, offering potential benefits for patient outcomes and hospital finances. [ABSTRACT FROM AUTHOR]

Background: During the past two decades of cannabis legalization, the prevalence of medical cannabis (MC) use has increased and there has also been an upward trend in alcohol consumption. As less restricted cannabis laws generate more adult cannabis users, there is concern that more individuals may be simultaneously using medical cannabis with alcohol. A few studies have examined simultaneous use of medical cannabis with alcohol, but none of those studies also assessed patients' current or previous non-medical cannabis use. This paper explores simultaneous alcohol and medical cannabis use among medical cannabis patients with a specific focus on previous history of cannabis use and current non-medical cannabis use. Methods: A retrospective cohort study of MC patients (N = 319) from four dispensaries located in New York. Bivariate chi-square tests and multivariable logistic regression are used to estimate the extent to which sociodemographic and other factors were associated with simultaneous use. Results: Approximately 29% of the sample engaged in simultaneous use and a large share of these users report previous (44%) or current (66%) use of cannabis for non-medical purposes. MC patients who either previously or currently use cannabis non-medicinally, men, and patients using MC to treat a pain-related condition, were significantly more likely to report simultaneous alcohol/MC use. Conclusions: Findings indicate that there may be differential risks related to alcohol/MC use, which should be considered by cannabis regulatory policies and prevention/treatment programs. If patients are using cannabis and/or alcohol to manage pain, clinicians should screen for both alcohol and cannabis use risk factors. [ABSTRACT FROM AUTHOR]

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are widely detected in pregnant women and associated with adverse outcomes related to impaired placental function. Human chorionic gonadotropin (hCG) is a dimeric glycoprotein hormone that can indicate placental toxicity. OBJECTIVES: Our aim was to quantify the association of serum PFAS with placental hCG, measured as an intact molecule (hCG), as free alpha- (hCGα) and beta-subunits (hCGβ), and as a hyperglycosylated form (h-hCG), and evaluate effect measure modification by social determinants and by fetal sex. METHODS: Data were collected from 326 pregnant women enrolled from 2015 to 2019 in the UPSIDE study in Rochester, New York. hCG forms were normalized for gestational age at the time of blood draw in the first trimester [multiple of the median (MoM)]. Seven PFAS were measured in second-trimester maternal serum. Multivariate imputation by chained equations and inverse probability weighting were used to evaluate robustness of linear associations. PFAS mixture effects were estimated by Bayesian kernel machine regression. RESULTS: Perfluorohexane sulfonic acid (PFHxS) [hCGβ: 0.29 log MoM units per log PFHxS; 95% confidence interval (CI): 0.08, 0.51] and perfluorodecanoic acid (PFDA) (hCG: -0.09; 95% CI: -0.16, -0.02) were associated with hCG in the single chemical and mixture analyses. The PFAS mixture was negatively associated with hCGα and positively with hCGβ. Subgroup analyses revealed that PFAS associations with hCG differed by maternal race/ethnicity and education. Perfluoropentanoic acid (PFPeA) was associated with hCGβ only in Black participants (-0.23; 95% CI: -0.37, -0.09) and in participants with high school education or less (-0.14; 95% CI: -0.26, -0.02); conversely, perfluorononanoic acid (PFNA) was negatively associated with hCGα only in White participants (-0.15; 95% CI: -0.27, -0.03) and with hCGβ only in participants with a college education or greater (-0.19; 95% CI: -0.36, -0.01). These findings were robust to testing for selection bias, confounding bias, and left truncation bias where PFAS detection frequency was <100%. Two associations were negative in male (and null in female) pregnancies: Perfluoroundecanoic acid (PFUnDA) with hCGα, and PFNA with h-hCG. CONCLUSIONS: Evidence was strongest for the association between PFHxS and PFDA with hCG in all participants and for PFPeA and PFNA within subgroups defined by social determinants and fetal sex. PFAS mixture associations with hCGα and hCGβ differed, suggesting subunit-specific types of toxicity and/or regulation. Future studies will evaluate the biological, clinical and public health significance of these findings. [ABSTRACT FROM AUTHOR]

The objective of this study was to analyze temporal changes in social needs (SN), comparing those who received routine annual in-person care to those receiving SN screenings through a combination of tele-social care and in-person care biannually. Our prospective cohort study used a convenience sample of patients from primary care practices. Baseline data were collected from April 2019 to March 2020. The intervention group (n = 336) received SN screening and referral telephone outreach from June 2020 to August 2021. The control group (n = 2890) was screened, in person, during routine visits at baseline and summer 2021. We used a repeated-measures logistic regression with general estimating equations to assess incremental change in individual SN for the intervention group. Food, housing, legal and benefit needs increased and peaked at the beginning of the pandemic and decreased after interventions (P < 0.001). There was a 32% decrease in the odds of food insecurity for those in the intervention group compared to the control group (adjusted OR 0.668, 95% confidence interval 0.444–1.004, P = 0.052), and a 75% decrease in the odds of housing insecurity (adjusted OR 0.247, 95% confidence interval 0.150–0.505, P < 0.001). During COVID-19, there was an increase in SN followed by a decrease after interventions were offered. Those who completed tele-social care showed greater improvements in social needs than those in routine care, with the greatest improvements in food and housing needs. [ABSTRACT FROM AUTHOR]