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Background: Recent research suggests that selective serotonin reuptake inhibitors (SSRIs) may reduce mortality in COVID-19 patients; however, research into their benefits for elderly Alzheimer's disease (AD) patients remains limited. Objective: To investigate the relationship between SSRIs therapy and the mortality risk after COVID-19 infection in elderly patients with and without AD. Methods: This retrospective cohort study leveraged a large database containing over 100 million electronic health records in the US from the TriNetX platform to compare the hazard rates of mortality after COVID-19 infection in elderly AD patients prescribed SSRIs versus propensity-score matched individuals prescribed other antidepressants. This study was also conducted in separate cohorts of patients without AD to compare the findings. Results: When compared with non-SSRI antidepressants, SSRIs were associated with lower risk for mortality after COVID-19 infection in elderly patients without AD over early, middle, and later stages of the pandemic with HRs of 0.84 (95% CI: 0.75–0.93), 0.86 (95% CI: 0.79–0.93), and 0.77 (95% CI: 0.71–0.33), respectively. When comparing SSRIs with non-SSRI antidepressants for mortality risk following COVID-19 among patients with AD, HRs of 0.95 (95% CI: 0.71–1.27), 0.80 (95% CI: 0.61–1.06), and 0.99 (95% CI: 0.75–1.32), were found respectively. Conclusions: Our findings suggest that the use of SSRIs is significantly associated with reduced mortality risk following COVID-19 in elderly patients without AD compared to other antidepressants. While a lower mortality risk was also observed among AD patients, the association was not statistically significant. [ABSTRACT FROM AUTHOR]

Semaglutide, a glucagon-like peptide-1 receptor agonist approved for type 2 diabetes and obesity, has been reported to be potentially beneficial in smoking cessation. In this retrospective observational study, investigators used a large electronic health record database to determine whether semaglutide use among patients with comorbid type 2 diabetes and tobacco use disorder was associated with changes in health care use measures related to their tobacco use. Visual Abstract. Association of Semaglutide With Tobacco Use Disorder in Patients With Type 2 Diabetes: Semaglutide, a glucagon-like peptide-1 receptor agonist approved for type 2 diabetes and obesity, has been reported to be potentially beneficial in smoking cessation. In this retrospective observational study, investigators used a large electronic health record database to determine whether semaglutide use among patients with comorbid type 2 diabetes and tobacco use disorder was associated with changes in health care use measures related to their tobacco use. Background: Reports of reduced desire to smoke in patients treated with semaglutide, a glucagon-like peptide receptor agonist (GLP-1RA) medication for type 2 diabetes mellitus (T2DM) and obesity, have raised interest about its potential benefit for tobacco use disorders (TUDs). Objective: To examine the association of semaglutide with TUD-related health care measures in patients with comorbid T2DM and TUD. Design: Emulation target trial based on a nationwide population-based database of patient electronic health records. Setting: United States, 1 December 2017 to 31 March 2023. Participants: Seven target trials were emulated among eligible patients with comorbid T2DM and TUD by comparing the new use of semaglutide versus 7 other antidiabetes medications (insulins, metformin, dipeptidyl-peptidase-4 inhibitors, sodium-glucose cotransporter-2 inhibitors, sulfonylureas, thiazolidinediones, and other GLP-1RAs). Measurements: The TUD-related health care measures (medical encounter for diagnosis of TUD, smoking cessation medication prescriptions, and smoking cessation counseling) that occurred within a 12-month follow-up were examined using Cox proportional hazards and Kaplan–Meier survival analyses. Results: The study compared 222 942 new users of antidiabetes medications including 5967 of semaglutide. Semaglutide was associated with a significantly lower risk for medical encounters for TUD diagnosis compared with other antidiabetes medications, and was strongest compared with insulins (hazard ratio [HR], 0.68 [95% CI, 0.63 to 0.74]) and weakest but statistically significant compared with other GLP-1RAs (HR, 0.88 [CI, 0.81 to 0.96]). Semaglutide was associated with reduced smoking cessation medication prescriptions and counseling. Similar findings were observed in patients with and without a diagnosis of obesity. For most of the group comparisons, the differences occurred within 30 days of prescription initiation. Limitation: Documentation bias, residual confounding, missing data on current smoking behavior, body mass index, and medication adherence. Conclusion: Semaglutide was associated with lower risks for TUD-related health care measures in patients with comorbid T2DM and TUD compared with other antidiabetes medications including other GLP-1Ras, primarily within 30 days of prescription. These findings suggest the need for clinical trials to evaluate semaglutide's potential for TUD treatment. Primary Funding Source: National Institutes of Health. [ABSTRACT FROM AUTHOR]

Background: Mild cognitive impairment (MCI) is a heterogeneous condition with high individual variabilities in clinical outcomes driven by patient demographics, genetics, brain structure features, blood biomarkers, and comorbidities. Multi‐modality data‐driven approaches have been used to discover MCI subtypes; however, disease comorbidities have not been included as a modality though multiple diseases including hypertension are well‐known risk factors for Alzheimer's disease (AD). The aim of this study was to examine MCI heterogeneity in the context of AD‐related comorbidities along with other AD‐relevant features and biomarkers. Methods: A total of 325 MCI subjects with 32 AD‐relevant comorbidities and features were considered. Mixed‐data clustering is applied to discover and compare MCI subtypes with and without including AD‐related comorbidities. Finally, the relevance of each comorbidity‐driven subtype was determined by examining their MCI to AD disease prognosis, descriptive statistics, and conversion rates. Results: We identified four (five) MCI subtypes: poor‐, average‐, good‐, and best‐AD prognosis by including comorbidities (without including comorbidities). We demonstrated that comorbidity‐driven MCI subtypes differed from those identified without comorbidity information. We further demonstrated the clinical relevance of comorbidity‐driven MCI subtypes. Among the four comorbidity‐driven MCI subtypes there were substantial differences in the proportions of participants who reverted to normal function, remained stable, or converted to AD. The groups showed different behaviors, having significantly different MCI to AD prognosis, significantly different means for cognitive test‐related and plasma features, and by the proportion of comorbidities. Conclusions: Our study indicates that AD comorbidities should be considered along with other diverse AD‐relevant characteristics to better understand MCI heterogeneity. [ABSTRACT FROM AUTHOR]