Citations

Introduction/Objectives: We aimed to investigate the effect of family structure on depression program outcomes for adolescents enrolled in a depression-focused, primary care-based collaborative care program. Methods: This was a retrospective study of primary care patients ages 12 to 18 years seen at a Midwestern academic center with data obtained by medical record review. We used logistic regression models to assess the effect of family structure on program graduation and achievement of a single Patient Health Questionnaire 9–Modified for Adolescents (PHQ-9M) score <5 at any time while enrolled. Results: Adolescents were divided into 2 groups, Both Parents in Household (n = 179) and Parents Not Together (n = 161). The Both Parents in Household group had higher rates of graduation (38.0% vs 23.6%, P = .005) and achieving single PHQ-9M scores <5 (64.1% vs 46.2%, P = .002) than the Parents Not Together group. Discussion: Youth residing with both parents had higher rates of successful outcomes in a depression-focused collaborative care program.

BACKGROUND: Cognitive impairment is common in patients with heart failure and preserved ejection fraction but its clinical correlates and prognostic associations are poorly understood. METHODS: We analyzed cognitive function, using the Mini-Mental State Examination (MMSE), in patients with heart failure and preserved ejection fraction enrolled in a prespecified substudy of the PARAGON-HF trial (Prospective Comparison of Angiotensin Receptor Neprilysin Inhibitor With Angiotensin Receptor Blocker Global Outcomes in Heart Failure With Preserved Ejection Fraction). Logistic regression analyses were performed to determine the variables associated with lower MMSE scores at baseline and postbaseline decline in MMSE scores at 48 weeks. Cox proportional hazards regression and semiparametric proportional rates models were used to examine the risk of clinical outcomes related to baseline MMSE scores, and decline in MMSE scores during follow-up, adjusted for prognostic variables including NT-proBNP (N-terminal pro-B-type natriuretic peptide). RESULTS: At baseline, cognitive function was normal (MMSE score 28–30) in 1809 of 2895 patients (62.5%), borderline (score 24–27) in 794 (27.4%), and impaired (score <24) in 292 (10.1%). Variables associated with both a lower MMSE score at baseline and a decline in score from baseline included older age, a history of stroke or transient ischemic attack, and lower serum albumin. Compared with those with baseline MMSE scores of 28 to 30, patients in the lower MMSE score categories had a stepwise increase in the risk of the composite of time to first heart failure hospitalization or cardiovascular death, with an adjusted hazard ratio of 1.27 (95% CI, 1.06–1.53) for those with scores of 24 to 27 and 1.58 (95% CI, 1.21–2.06) for those with scores <24, respectively. These associations were also found for the individual components of the composite and all-cause death. Likewise, cognitive impairment was associated with a 50% higher risk of total (first and repeat) heart failure hospitalizations and cardiovascular deaths. Examining the change in MMSE score from baseline, a decrease in MMSE score during follow-up was associated with a higher risk of death. CONCLUSIONS: In patients with heart failure and preserved ejection fraction, even modest baseline impairment of cognitive function was associated with worse outcomes, including death. A decline in MMSE score during follow-up was a strong predictor of mortality, independent of other prognostic variables.

OBJECTIVE Imaging surveillance with serial MRI, or a "wait-and-scan" approach, is a management option for patients with small or medium-sized vestibular schwannomas (VSs). Prior publications have indicated no distinct quality of life advantage to upfront treatment compared with initial wait-and-scan management. However, imaging surveillance is dependent on patient adherence to follow-up. In this study, the authors aimed to identify rates and predictors of patient loss to follow-up during wait-and-scan management of sporadic VS. METHODS A single-center study was conducted including all patients from 2013 to 2018 who had undergone upfront imaging surveillance of sporadic VS. Patient data were retrospectively obtained from the electronic medical record. Outcomes of interest included loss to follow-up unrelated to death and inconsistent adherence to imaging surveillance recommendations. Logistic regression analyses were conducted to evaluate factors associated with loss to follow-up. RESULTS Over a 6-year study period, 270 patients underwent initial imaging surveillance of a sporadic VS. The median tumor diameter was 8.6 mm (range 1–28.9 mm). At the time of censoring, 106 patients (39.3%) had received treatment, 157 (58.1%) had been advised to continue follow-up, and 7 (2.6%) had died of non–VS-related causes. In total, 73 patients (27.0%) were completely lost to follow-up prior to the first treatment or death. Additionally, 60 patients (22.2%) missed at least 1 MRI follow-up or imaging follow-up was delayed by more than 1 year. Multivariable logistic regression identified an out-of-state residence (OR 3.05, 95% CI 1.58–5.89, p = 0.0009) and a smaller tumor size (unit OR per 1-mm increase in size, OR 0.88, 95% CI 0.83–0.95, p = 0.0006) to be associated with loss to follow-up. Patients living ≥ 350 miles from the hospital or with tumors ≤ 3 mm at the time of initial clinic evaluation were most likely to be lost to follow-up. Only a smaller tumor size was associated with an increased risk of inconsistent imaging follow-up (unit OR per 1-mm increase in size, OR 0.92, 95% CI 0.87–0.98, p = 0.007). CONCLUSIONS Patients undergoing imaging surveillance of VS are at risk for loss to follow-up and inconsistent imaging surveillance. Patients with smaller tumors or those living farther away from the treating institution are at highest risk for being lost to follow-up.

Abstract Objectives Social support (SS) and social isolation (SI) are social determinants of health (SDOH) associated with psychiatric outcomes. In electronic health records (EHRs), individual-level SS/SI is typically documented in narrative clinical notes rather than as structured coded data. Natural language processing (NLP) algorithms can automate the otherwise labor-intensive process of extraction of such information. Materials and Methods Psychiatric encounter notes from Mount Sinai Health System (MSHS, n = 300) and Weill Cornell Medicine (WCM, n = 225) were annotated to create a gold-standard corpus. A rule-based system (RBS) involving lexicons and a large language model (LLM) using FLAN-T5-XL were developed to identify mentions of SS and SI and their subcategories (eg, social network, instrumental support, and loneliness). Results For extracting SS/SI, the RBS obtained higher macroaveraged F1-scores than the LLM at both MSHS (0.89 versus 0.65) and WCM (0.85 versus 0.82). For extracting the subcategories, the RBS also outperformed the LLM at both MSHS (0.90 versus 0.62) and WCM (0.82 versus 0.81). Discussion and Conclusion Unexpectedly, the RBS outperformed the LLMs across all metrics. An intensive review demonstrates that this finding is due to the divergent approach taken by the RBS and LLM. The RBS was designed and refined to follow the same specific rules as the gold-standard annotations. Conversely, the LLM was more inclusive with categorization and conformed to common English-language understanding. Both approaches offer advantages, although additional replication studies are warranted.