Scaling up frailty: psychometric validation of the Functional Limitations and Geriatric Syndromes Frailty Questionnaire - a new tool for uniformly classifying vulnerable hospital patients

Bruno Bernardini^1,2*Rosa Pedale²Paola Arosio²Federico Piccioni²Stefano Mancin²Francesco Reggiani^2,3Giovanna Cerina²Sara Ghirmai²Carla Corsini²Riccardo Levi^2,3Maria Vittoria Fantacci²Laura Tabarretti²Giulia Goretti²Rodolfo Hurle^2*

• ¹Humanitas Research Hospital, Neurocenter, Neurorehabilitation, Rozzano (Milan), Italy
• ²IRCCS Humanitas Research Hospital, Rozzano, Italy
• ³Humanitas University, Milan, Italy

Abstract (number of words: 349) Background Comprehensive psychometric validation is essential to obtain a common metric for reliable diagnostic and prognostic decision-making in frailty. In this study, we used a single-factor approach to derive and psychometrically validate a standardized frailty measure from 23 reflective items from a new, multidomain, questionnaire. We used confirmatory factor analysis (CFA) and item response theory (IRT) to achieve this goal. Methods This single-centre, cross-sectional study included a convenience sample of 900 community-dwelling patients (median age: 73.4 years; IQR: 67.0–81.6; 59.7% male) undergoing elective surgery (n = 568, 63.1%) or admitted to the internal medicine unit for acute illnesses (n = 332, 36.9%). Of the elective patients, 50.4% completed the questionnaire via a web platform. The rest completed the questionnaire during a face-to-face interview at their preoperative visit or within 48 hours of admission. Results The CFA validated the single-factor solution for 16 of the 23 items in the questionnaire and confirmed the good internal consistency of the construct. IRT analyses showed that the 16 items of the Functional Limitation and Geriatric Syndrome Frailty Questionnaire (FLIGS-FQ-16) have good discriminatory power, satisfactory threshold parameters, and equal function for men and women. The FLIGS-FQ-16 score provides reliable information on the severity of frailty, ranging from 0.18 standard deviations below the population mean ("not frail") to 2.7 standard deviations above the population mean ("severely frail"). Applying the standardized FLIGS-FQ-16 threshold scores to our sample, we found an overall prevalence of frailty of 40.9%, with a significant difference between acute patients (75.3%) and elective patients (20.8%; p<0.001). Among acute patients, 37.6% were moderately or severely frail. Among elective patients, 19.0% were moderately frail and 1.8% were severely frail. Conclusions The five functional limitations and 11 geriatric syndromes of the FLIGS-FQ-16 aggregate into a robust single-factor construct with adequate psychometric properties that uniformly measure frailty up to the most severe levels. In addition to serving as a screening tool, the FLIGS-FQ-16 is useful for making individualized decisions and developing personalized treatment plans in perioperative medicine and the management of hospitalised older adults because it is based on treatable risk factors.