Prediction of post-interventional physical function in diabetic foot ulcer patients using patient reported outcome measurement information system (PROMIS)

Abstract

BackgroundInfected diabetic foot ulcer (DFU) patients present with an impaired baseline physical function (PF) that can be further compromised by surgical intervention to treat the infection. The impact of surgical interventions on Patient Reported Outcomes Measurement Information System (PROMIS) PF within the DFU population has not been investigated. We hypothesize that preoperative PROMIS scores (PF, Pain Interference (PI), Depression) in combination with relevant clinical factors can be utilized to predict postoperative PF in DFU patients. MethodsDFU patients from a single academic physician’s practice between February 2015 and November 2018 were identified (n = 240). Ninety-two patients met inclusion criteria with complete follow-up and PROMIS computer adaptive testing records. Demographic and clinical factors, procedure performed, and wound healing status were collected. Spearman's rank correlation coefficient, Chi-Squared tests and multidimensional modelling were applied to all variables’ pre- and postoperative values to assess patients’ postoperative PF. ResultsThe mean age was 60.5 (33–96) years and mean follow-up was 4.7 (3−12) months. Over 70 % of the patients’ initial PF were 2–3 standard deviations below the US population (n = 49; 28). Preoperative PF (p < 0.01), PI (p < 0.01), Depression (p < 0.01), CRF (p < 0.02) and amputation level (p < 0.04) showed significant univariate correlation with postoperative PF. Multivariate model (r = 0.55) showed that the initial PF (p = 0.004), amputation level (p = 0.008), and wound healing status (p = 0.001) predicted postoperative PF. ConclusionsMajority of DFU patients present with poor baseline PF. Preoperative PROMIS scores (PF, PI, Depression) are predictive of postoperative PROMIS PF in DFU patients. Postoperative patient’s physical function can be assessed by PFpostoperative = 29.42 + 0.34 (PFinitial) – 5.87 (Not Healed) – 2.63 (Amputation Category). This algorithm can serve as a valuable tool for predicting post-operative physical function and setting expectations.