RESUMEN
OBJECTIVES: To assess the impact of adding the Prognostic Nutritional Index (PNI) to the U.S. Veterans Health Administration frailty index (VA-FI) for the prediction of time-to-death and other clinical outcomes in Veterans hospitalized with Heart Failure. METHODS: A retrospective cohort study of veterans hospitalized for heart failure (HF) from October 2015 to October 2018. Veterans ≥50 years with albumin and lymphocyte counts, needed to calculate the PNI, in the year prior to hospitalization were included. We defined malnutrition as PNI ≤43.6, based on the Youden index. VA-FI was calculated from the year prior to the hospitalization and identified three groups: robust (≤0.1), prefrail (0.1-0.2), and frail (>0.2). Malnutrition was added to the VA-FI (VA-FI-Nutrition) as a 32nd deficit with the total number of deficits divided by 32. Frailty levels used the same cut-offs as the VA-FI. We compared categories based on VA-FI to those based on VA-FI-Nutrition and estimated the hazard ratio (HR) for post-discharge all-cause mortality over the study period as the primary outcome and other adverse events as secondary outcomes among patients with reduced or preserved ejection fraction in each VA-FI and VA-FI-Nutrition frailty groups. RESULTS: We identified 37,601 Veterans hospitalized for HF (mean age: 73.4 ± 10.3 years, BMI: 31.3 ± 7.4 kg/m2). In general, VA-FI-Nutrition reclassified 1959 (18.6%) Veterans to a higher frailty level. The VA-FI identified 1,880 (5%) as robust, 8,644 (23%) as prefrail, and 27,077 (72%) as frail. The VA-FI-Nutrition reclassified 382 (20.3%) from robust to prefrail and 1577 (18.2%) from prefrail to frail creating the modified-prefrail and modified-frail categories based on the VA-FI-Nutrition. We observed shorter time-to-death among Veterans reclassified to a higher frailty status vs. those who remained in their original group (Median of 2.8 years (IQR:0.5,6.8) in modified-prefrail vs. 6.3 (IQR:1.8,6.8) years in robust, and 2.2 (IQR:0.7,5.7) years in modified-frail vs. 3.9 (IQR:1.4,6.8) years in prefrail). The adjusted HR in the reclassified groups was also significantly higher in the VA-FI-Nutrition frailty categories with a 38% increase in overall all-cause mortality among modified-prefrail and a 50% increase among modified-frails. Similar trends of increasing adverse events were also observed among reclassified groups for other clinical outcomes. CONCLUSION: Adding PNI to VA-FI provides a more accurate and comprehensive assessment among Veterans hospitalized for HF. Clinicians should consider adding a specific nutrition algorithm to automated frailty tools to improve the validity of risk prediction in patients hospitalized with HF.
Asunto(s)
Fragilidad , Insuficiencia Cardíaca , Desnutrición , Evaluación Nutricional , Veteranos , Humanos , Masculino , Anciano , Estudios Retrospectivos , Femenino , Desnutrición/diagnóstico , Desnutrición/epidemiología , Medición de Riesgo/métodos , Veteranos/estadística & datos numéricos , Fragilidad/complicaciones , Persona de Mediana Edad , Estados Unidos/epidemiología , Hospitalización/estadística & datos numéricos , Pronóstico , Evaluación Geriátrica/métodos , Evaluación Geriátrica/estadística & datos numéricos , Estado Nutricional , United States Department of Veterans Affairs/estadística & datos numéricos , Anciano de 80 o más AñosRESUMEN
INTRODUCTION: Implantable loop recorders (ILR) are used to screen for atrial fibrillation (AF) in patients with cryptogenic stroke (CS). However, there is limited real-world data regarding the long-term rate of AF detection using ILR and management consequences in patients with CS. The objective is to assess the rate of AF detection in patients with CS in a real-world study over 36 months of follow-up and its consequences on stroke prevention. METHODS: This retrospective study included patients with an ILR placed for CS at Baylor College of Medicine and Baylor St. Luke's Medical Center between January 2014 and July 2021. The primary outcome was AF detection in patients with ILR. The secondary outcome was the rate of subsequent strokes after ILR placement in patients with or without diagnosed AF. The AF detection rate in our cohort was compared to the rate in CRYSTAL-AF Trial at 36-month follow-up. The impact of AF detection on clinical management was examined. RESULTS: We identified 225 patients. 51.1% were women and 38.2% African American. Among 85 patients with ILR labeled AF, 43 patients had true AF, and 42 had incorrectly labeled AF (48.3% false positive). The estimated AF detection rate at 36 months follow-up was 28.6% (95% CI, 26.6%-30.6%). 58.1% of patients with AF were initiated on oral anticoagulation, 80.0% of whom were started on a direct oral anticoagulant. 13.8% of patients had recurrent strokes after ILR implantation; 4 of whom were diagnosed with AF. CONCLUSION: Compared to CRYSTAL-AF, the AF detection rate in our cohort is similar, but this cohort includes a higher proportion of female and African American patients. Most patients with recurrent strokes after ILR implant did not have AF during 36 months of monitoring.