Khan, Muhammad Khuzzaim

Introduction: This study evaluated the impact of parallel-level patient transfers on bed utilization efficiency within the Mayo Clinic Health System in Southern Minnesota, focusing on optimizing resources across tertiary and critical access hospitals. Methods: A retrospective analysis of 179,066 Emergency Department visits (2018–2022) was conducted, with ~2% involving parallel-level transfers for observation or admission. Machine learning was utilized to identify patients suitable for parallel transfers based on demographics, comorbidities, and clinical factors. A Random Forest model with an AUROC of 0.87 guided transfer decisions. Saved patient days were calculated as the difference between the actual LOS and the benchmark LOS based on Diagnosis-Related Groups (DRGs). Generalized estimating equations analyzed length of stay (LOS) differences, adjusted for confounders, with 95% confidence intervals (CI). Statistical analyses were conducted using SPSS (v.26). Results: The mean patient age was 56 years (SD = 17.2), with 51.4% being female. Saved patient days increased from ~600 to 5200 days over the study period. Transferred patients had a 5.7% longer unadjusted LOS compared to non-transferred patients (95% CI: 2.9–8.6%, p < 0.001). After adjustment for demographics and comorbidities, the LOS difference was not significant (adjusted mean difference: 0.4%, 95% CI: −1.7–2.5%, p = 0.51). Conclusions: Parallel-level transfers increased saved patient days, reflecting enhanced resource utilization. However, the adjusted LOS differences were not significant, highlighting the need for robust transfer protocols and controlled studies to confirm these findings.

Abstract Background Acute respiratory failure is one of the most common causes of hospitalizations in the US. By 2030, the number of Americans with dementia is expected to reach nearly 9 million and 12 million in 2040. Dementia increases the risk of respiratory illnesses, including pneumonia. This study delves into the intricate interplay between dementia and acute respiratory failure. Methods Our retrospective study analyzed adult patients with acute respiratory failure and secondary diagnosis of dementia using ICD-10 codes in the National Inpatient Sample (NIS) Database from 2017 to 2020. An analysis was conducted on various demographic factors such as age, race, and gender. The study's primary endpoint was mortality, with mechanical ventilation, tracheostomy, and length of stay as secondary endpoints. To account for other variables that could have affected the results, we utilized a multivariate logistic regression with p < 0.05 considered significant. Results The study included 1,795,630 patients admitted with ARF, 112,175 of whom had dementia. The mean age in the dementia group was 80 years, compared to 65 years in the control group. Additionally, 62% of the dementia group were females, while the control group had 55% females. 73% of both groups were Caucasian white. Comorbidities observed in the dementia group include hypertension (81% vs. 72%), diabetes mellitus (36% vs. 35%), supraventricular tachycardia (29% vs. 20%), and sepsis (6% vs. 5%) with p-value less than 0.01. Rates and odds of mortality were higher in the dementia group (15,704 (14%) vs. 151,511 (9%), p-value < 0.01, aOR 1.08, p-value < 0.01). Patients with dementia had lower rates of in-hospital mechanical ventilation, but higher adjusted odds (27% vs. 28%; p < 0.01; aOR + 1.2, p < 0.01). Patients with dementia had lower rates and adjusted odds of undergoing a tracheostomy during their stay (762 (0.7) vs. 16,834 (1), p-value < 0.01, aOR 0.91 p-value 0.33).. Patients with dementia had a longer length of stay (LOS) than those without, with a mean difference of + 0.3 days and p-value < 0.01. Conclusions Clinicians should be aware that dementia was found to be an independent risk factor for mortality in patients admitted with acute respiratory failure.

Abstract Aim Type 1 diabetes mellitus is widely recognized as a chronic autoimmune disease characterized by the pathogenic destruction of beta cells, resulting in the loss of endogenous insulin production. Insulin administration remains the primary therapy for symptomatic treatment. Recent studies showed that disease‐modifying agents, such as anti‐CD3 monoclonal antibodies, have shown promising outcomes in improving the management of the disease. In late 2022, teplizumab received approval from the US Food and Drug Administration (FDA) as the first disease‐modifying agent for the treatment of type 1 diabetes. This review aims to evaluate the clinical evidence regarding the efficacy of anti‐CD3 monoclonal antibodies in the prevention and treatment of type 1 diabetes. Methods A comprehensive search of PubMed, Google Scholar, Scopus and Cochrane Central Register of Controlled Trials (CENTRAL) was conducted up to December 2022 to identify relevant randomized controlled trials. Meta‐analysis was performed using a random‐effects model, and odds ratios with 95% confidence intervals (CIs) were calculated to quantify the effects. The Cochrane risk of bias tool was employed for quality assessment. Results In total, 11 randomized controlled trials involving 1397 participants (908 participants in the intervention arm, 489 participants in the control arm) were included in this review. The mean age of participants was 15 years, and the mean follow‐up time was 2.04 years. Teplizumab was the most commonly studied intervention. Compared with placebo, anti‐CD3 monoclonal antibody treatment significantly increased the C‐peptide concentration in the area under the curve at shorter timeframes (mean difference = 0.114, 95% CI: 0.069 to 0.159, p = .000). Furthermore, anti‐CD3 monoclonal antibodies significantly reduced the patients' insulin intake across all timeframes (mean difference = −0.123, 95% CI: −0.151 to −0.094, p < .001). However, no significant effect on glycated haemoglobin concentration was observed. Conclusion The findings of this review suggest that anti‐CD3 monoclonal antibody treatment increases endogenous insulin production and improves the lifestyle of patients by reducing insulin dosage. Future studies should consider the limitations, including sample size, heterogeneity and duration of follow‐up, to validate the generalizability of these findings further.