Modeling mortality prediction in older adults with dementia receiving COVID-19 vaccination.

OBJECTIVE: This study compared COVID-19 outcomes between vaccinated and unvaccinated older adults with and without cognitive impairment. METHOD: Electronic health records from Israel from March 2020-February 2022 were analyzed for a large cohort (N = 85,288) aged 65 + . Machine learning constructed models to predict mortality risk from patient factors. Outcomes examined were COVID-19 mortality and hospitalization post-vaccination. RESULTS: Our study highlights the significant reduction in mortality risk among older adults with cognitive disorders following COVID-19 vaccination, showcasing a survival rate improvement to 93%. Utilizing machine learning for mortality prediction, we found the XGBoost model, enhanced with inverse probability of treatment weighting, to be the most effective, achieving an AUC-PR value of 0.89. This underscores the importance of predictive analytics in identifying high-risk individuals, emphasizing the critical role of vaccination in mitigating mortality and supporting targeted healthcare interventions. CONCLUSIONS: COVID-19 vaccination strongly reduced poor outcomes in older adults with cognitive impairment. Predictive analytics can help identify highest-risk cases requiring targeted interventions.

Exploring the Self-Reported Physical and Psychological Effects in a Population Exposed to a Regional Conflict.

BACKGROUND: Conflict profoundly impacts community health and well-being. While post-conflict research exists, little is known about initial effects during active hostilities. OBJECTIVE: To assess self-reported changes in health behaviors, distress, and care access within one month of regional warfare onset in a conflict-affected community. METHODS: An online survey was conducted in November 2023 among 501 residents (mean age 40.5 years) of a community where war began October 7th. Measures evaluated physical health, mental health, diet, substance use, sleep, weight changes, and healthcare access before and after the declaration of war. RESULTS: Relative to pre-war, respondents reported significantly increased rates of tobacco (56%) and alcohol (15%) consumption, worsening sleep quality (63%), elevated distress (18% sought help; 14% needed but didn't receive it), and postponed medical care (36%). Over a third reported weight changes. Distress was higher among females and those endorsing maladaptive coping. CONCLUSION: Within one month, substantial impacts on community psychosocial and behavioral health emerged. Unmet mental health needs and risk-taking behaviors were early indicators of conflict's health consequences. Continuous monitoring of conflict-affected communities is needed to inform tailored interventions promoting resilience and prevent entrenchment of harms over time.

Optimising wound monitoring: Can digital tools improve healing outcomes and clinic efficiency.

BACKGROUND: Chronic wounds present significant challenges for patients and nursing care teams worldwide. Digital health tools offer potential for more standardised and efficient nursing care pathways but require further rigorous evaluation. OBJECTIVE: This retrospective matched cohort study aimed to compare the impacts of a digital tracking application for wound documentation versus traditional manual nursing assessments. METHODS: Data from 5236 patients with various wound types were analysed. Propensity score matching balanced groups, and bivariate tests, correlation analyses, linear regression, and Hayes' Process Macro Model 15 were utilised for a mediation-moderation model. RESULTS: Digital wound tracking was associated with significantly shorter healing durations (15 vs. 35 days) and fewer clinic nursing visits (3 vs. 5.8 visits) compared to standard nursing monitoring. Digital tracking demonstrated improved wound size reduction over time. Laboratory values tested did not consistently predict healing outcomes. Digital tracking exhibited moderate negative correlations with the total number of nursing visits. Regression analysis identified wound complexity, hospitalizations, and initial wound size as clinical predictors for more nursing visits in patients with diabetes mellitus (p < .01). Digital tracking significantly reduced the number of associated nursing visits for patients with peripheral vascular disease. CONCLUSION: These findings suggest that digital wound management may streamline nursing care and provide advantages, particularly for comorbid populations facing treatment burdens. REPORTING METHOD: This study adhered to STROBE guidelines in reporting this observational research. RELEVANCE TO CLINICAL PRACTICE: By streamlining documentation and potentially shortening healing times, digital wound tracking could help optimise nursing resources, enhance wound care standards, and improve patient experiences. This supports further exploration of digital health innovations to advance evidence-based nursing practice. PATIENT OR PUBLIC CONTRIBUTION: This study involved retrospective analysis of existing patient records and did not directly include patients or the public in the design, conduct, or reporting of the research.

Conflict-Related Breakdowns in Routine Medical Care - Longitudinal Outcomes for Civilians with Pre-Existing Cognitive Impairment.

Individuals with dementia face increased vulnerability during crises like armed conflicts. However, little is known about how conflicts affect dementia care delivery and patients' health. We conducted a longitudinal cohort study using medical record data. The study included 23,733 adults aged≥65 years with a diagnosis of dementia and 249,749 matched adults without dementia. Data were collected at baseline (March-October 2023), and two follow-up timepoints (December 2023 and February 2024), bracketing an armed conflict between Israel and Palestinian militant groups that began on October 7, 2023. We compared changes over time in clinical characteristics, medication use, healthcare utilization, costs between groups. Dementia prevalence was stable, but psychotropic medication use declined more sharply in those with dementia. Rates of depression diagnoses fell, and obesity rose in both groups. Healthcare utilization decreased substantially post-conflict, with fewer outpatient visits, hospitalizations, and emergency visits. Cost divergence between groups also increased over time. Machine learning identified shifting clusters of service users from high to mainly low users' post-conflict. The conflict severely disrupted routine dementia care and altered health behaviors. Flexible service delivery and access promotion strategies are needed to support vulnerable populations like people with dementia during crises.

Harnessing innovation to help meet the needs of elders: field testing an electronic tool to streamline geriatric assessments across healthcare settings.

BACKGROUND: As populations age globally, effectively managing geriatric health poses challenges for primary care. Comprehensive geriatric assessments (CGAs) aim to address these challenges through multidisciplinary screening and coordinated care planning. However, most CGA tools and workflows have not been optimised for routine primary care delivery. OBJECTIVE: This study aimed to evaluate the impact of a computerised CGA tool, called the Golden Age Visit, implemented in primary care in Israel. METHODS: This study employed a quasiexperimental mixed-methods design to evaluate outcomes associated with the Golden Age electronic health assessment tool. Quantitative analysis used electronic medical records data from Maccabi Healthcare Services, the second largest health management organisation (HMO) in Israel. Patients aged 75 and older were included in analyses from January 2017 to December 2019 and January 2021 to December 2022. For patients, data were also collected on controls who did not participate in the Golden Age Visit programme during the same time period, to allow for comparison of outcomes. For physicians, qualitative data were collected via surveys and interviews with primary care physicians who used the Golden Age Visit SMARTEST e-assessment tool. RESULTS: A total of 9022 community-dwelling adults aged 75 and older were included in the study: 1421 patients received a Golden Age Visit CGA (intervention group), and 7601 patients did not receive the assessment (control group). After CGAs, diagnosis rates increased significantly for neuropsychiatric conditions and falls. Referrals to physiotherapy, occupational therapy, dietetics and geriatric outpatient clinics also rose substantially. However, no differences were found in rates of hip fracture or relocation to long-term care between groups. Surveys among physicians (n=151) found high satisfaction with the programme. CONCLUSION: Implementation of a large-scale primary care CGA programme was associated with improved diagnosis and management of geriatric conditions. Physicians were also satisfied, suggesting good uptake and feasibility within usual care. Further high-quality studies are still needed but these results provide real-world support for proactively addressing geriatric health needs through structured screening models.