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Biomedical subjects

Lora Lee Pless

Publications and source records attributed to Lora Lee Pless.

2 recordsLinked to original sources

Pharmacological Interventions for Weight Reduction in Patients With Schizophrenia Treated With Antipsychotics: A Systematic Review and Network Meta-Analysis.

IMPORTANCE: Significant weight gain is a concerning adverse effect of antipsychotic medications experienced by patients with schizophrenia spectrum disorders (SSDs). Its high prevalence and significant contribution to cardiometabolic morbidity in this population warrant better consensus on the management of antipsychotic-induced weight gain and related comorbidity. OBJECTIVES: To evaluate the association between pharmacological interventions and changes in body weight among antipsychotic-treated patients with SSDs. DATA SOURCES: Ovid MEDLINE, Embase, PsycINFO, the Cochrane Central Register of Controlled Trials (CENTRAL), CINAHL, ClinicalTrials.gov, and the International Clinical Trials Registry Platform (ICTRP) Search Portal were searched up to December 5, 2025. STUDY SELECTION: Randomized clinical trials examining any pharmacological intervention for weight reduction in antipsychotic-treated patients with SSDs were included. No restrictions to study duration were applied. DATA EXTRACTION AND SYNTHESIS: A systematic review and frequentist random-effects network meta-analysis was conducted. Certainty in the evidence was assessed using the Confidence in Network Meta-Analysis (CINeMA) tool. The first round of data analysis took place between May 2025 to November 2025 and was updated in December 2025. MAIN OUTCOMES AND MEASURES: The primary outcome was change in body weight following treatment with pharmacological agent vs placebo or standard care. Secondary outcomes included other anthropometric and metabolic parameters. RESULTS: A total of 95 studies examining 39 individual pharmacological interventions were included in this review (pooled N = 5898). The network meta-analysis found that semaglutide (mean difference [MD], -10.98 kg; 95% CI, -13.33 to -8.62; k = 3; moderate certainty), liraglutide (MD, -5.43 kg; 95% CI, -8.54 to -2.33; k = 2; moderate certainty), topiramate (MD, -3.95 kg; 95% CI, -5.89 to -2.02; k = 5; moderate certainty), metformin (MD, -3.86 kg; 95% CI, -5.02 to -2.70; k = 16; moderate certainty), and exenatide (MD, -2.97 kg; 95% CI, -5.83 to -0.11; k = 3; moderate certainty) were associated with the most significant reductions in body weight compared to placebo. Other interventions including ramelteon, nizatidine, and aripiprazole were also found to be associated with weight-reducing effects but with very low certainty of evidence. Clinically meaningful weight change of 5% or greater was observed with semaglutide and metformin. Beneficial effects on other metabolic outcomes were also noted with several of the medications, and there were no major concerns with gastrointestinal adverse effects or leaving the study early (ie, dropouts) between interventions. CONCLUSIONS AND RELEVANCE: This systematic review and network meta-analysis found substantial variability in weight-related outcomes across pharmacological interventions for antipsychotic-treated individuals with SSDs. Semaglutide, liraglutide, topiramate, metformin, and exenatide were associated with the greatest reductions in body weight and were supported by the highest-certainty evidence, providing guidance for clinicians managing antipsychotic-associated weight gain.

Humans

Methods for cost-efficient, whole genome sequencing surveillance for enhanced detection of outbreaks in a hospital setting.

INTRODUCTION: Outbreaks of healthcare-associated infections (HAI) result in substantial patient morbidity and mortality; mitigation efforts by infection prevention teams have the potential to curb outbreaks and prevent transmission to additional patients. The incorporation of whole genome sequencing (WGS) surveillance of suspected high-risk pathogens often identifies outbreaks that are not detected by traditional infection prevention methods and provides evidence for transmission. Our approach to real-time WGS surveillance, the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT), has 1) identified serious outbreaks that were otherwise undetected and 2) shown the potential to be cost saving. METHODS: We describe our cost-efficient methods to perform WGS surveillance and data analysis of pathogens for institutions that are interested in expanding infection prevention surveillance. We provide an overview of the weekly workflow of EDS-HAT during two distinct phases over three years. RESULTS: In an average week at our tertiary healthcare system, we sequenced 60 samples at a cost of less than $100 each during Phase 1, and 80 samples for less than $70 each in Phase 2, inclusive of laboratory reagents and staff salaries. The average turnaround time, from sample collection to reporting data to infection prevention, was nine days. CONCLUSIONS: Performing EDS-HAT in real-time can be both feasible and time-efficient. Providing such timely information to aid in outbreak detection could identify transmission events sooner and thus could increase patient safety.

Disease Outbreaks