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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]

Neighborhood socioeconomic status (SES) and greenspace can affect respiratory health. However, it is unclear whether effects of neighborhood SES and greenspace on respiratory health still exist regardless of temperature variations. This paper conducted a two-stage, age-stratified case time-series study. The first goal is to examine the associations between two temperature metrics (daily mean temperature [DMT] and diurnal temperature range [DTR]) and respiratory emergency department (ED) visits among four age groups in New York City. The second goal is to evaluate whether neighborhood SES and greenspace would be determinants of respiratory ED visits independent from temperature varying factors. A distributed lag nonlinear model was applied on ED data from 135 zip codes (October 2016 - February 2020). Our first-stage analysis indicated that older adults aged 65+ had higher risk of ED visits (RR=2.78, 95% eCI: 2.41, 3.22; with 7 days of lag) on days with low DMT (-10 °C), followed by adults aged 18-64 (RR=2.48, 95% eCI: 2.32, 2.65), children and youth aged 5-17 (RR=1.38, 95% eCI: 1.24, 1.53), and young children aged 0-4 (RR=1.04, 95% eCI: 0.96, 1.13). However, no excess respiratory ED visits were observed on days with high DMT (30 °C). Higher DTR was associated with higher risk, with children and youth more susceptible when DTR was high (DTR 20 °C; RR=5.70, 95% eCI: 3.42, 9.49; with 7 days of lag). The second-stage analysis indicated neighborhood SES and greenspace had significant associations with respiratory ED visits regardless of temperature variations. Specifically, Higher income and greenspace exposure were negatively associated with ED visits among all age groups. Neighborhood SES and greenspace could affect respiratory morbidity regardless of weather conditions. Daily temperature variations accelerated the short-term risk among population subgroups under different weather conditions (e.g., higher risk of days with low DMT among older adults, higher risk of days with high DTR among children and youth aged 5-17), which could create co-effects with neighborhood SES and greenspace on respiratory health. • Respiratory ED visit was significantly associated with both DMT and DTR. • Older adults more vulnerable to low DMT (RR=2.78, 95% eCI: 2.41, 3.22). • Youth aged 5-17 more vulnerable to high DTR (RR=5.70, 95% eCI: 3.42, 9.49). • SES and greenspace associated with respiratory ED visit regardless of temperature. • Intracity examination of impacts of DMT and DTR on health allows local actions. [ABSTRACT FROM AUTHOR]