Abstract
BackgroundThe aim of this study was to identify the risk factors associated with prolonged length of stay (LOS) in patients undergoing primary total hip arthroplasty (THA) managed with an enhanced recovery after surgery (ERAS) program and develop a prediction model for improving the perioperative management of THA.MethodsIn this single-center retrospective study, patients who underwent primary THA in accordance with ERAS from May 2018 to December 2019 were enrolled in this study. The primary outcome was prolonged LOS (> 48 h) beyond the first postoperative day. We collected the clinical patient’s clinical characteristics, surgery-related parameters, and laboratory tests. A logistic regression analysis explored the independent risk factors for prolonged LOS. According to published literature and clinical experience, a series of variables were selected to develop a nomogram prediction model to predict the risk of prolonged LOS following primary THA with an ERAS program. Evaluation indicators of the prediction model, including the concordance index (C-index), the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis, were reported to assess the performance of the prediction model. The bootstrap method was conducted to validate the performance of the designed nomogram.ResultsA total of 392 patients were included in the study, of whom 189 (48.21%) had prolonged LOS. The logistics regression analysis demonstrated that age, sex, hip deformities, intraoperative blood loss, operation time, postoperative Day 1 (POD) hemoglobin (Hb), POD albumin (ALB), and POD interleukin-6 (IL-6) were independent risk factors for prolonged LOS. The C-index was 0.863 (95% CI 0.808 to 0.918) and 0.845 in the bootstrapping validation, respectively. According to the results of the calibration, ROC curve, and decision curve analyses, we found that the nomogram showed satisfactory performance for prolonged LOS in this study.ConclusionsWe explored the risk factors for prolonged LOS following primary THA with an ERAS program and developed a prediction model. The designed nomogram was expected to be a precise and personalized tool for predicting the risk and prognosis for prolonged LOS following primary THA with an ERAS program.
Highlights
The aim of this study was to identify the risk factors associated with prolonged length of stay (LOS) in patients undergoing primary total hip arthroplasty (THA) managed with an enhanced recovery after surgery (ERAS) program and develop a prediction model for improving the perioperative management of THA
Among the A and B group, there were statistically significant differences were observed in age (P < 0.001), sex (P = 0.04), hip deformities (P = 0.035), hip joint mobility (P = 0.008), preoperative visual analogue score (VAS) (P = 0.012), preoperative Hb (P = 0.003), operation time (P < 0.001), anesthesia time (P < 0.001), intraoperative infusion volume (P < 0.001), out of bed activities time (P < 0.001), postoperative infusion volume (P < 0.001), total infusion volume on the day of surgery (P < 0.001), VAS score on the day of surgery (P < 0.001), postoperative Day 1 (POD) VAS score (P < 0.001), POD ALB (P < 0.001), POD IL-6 (P < 0.001), POD total blood loss (P = 0.044), and POD Hb change rate (P < 0.001)
Female Male body mass index (BMI) Harris score Hip deformities (%) No Yes Hip joint mobility (°) Preoperative VAS Preoperative Hb (g/L) Preoperative ALB (g/L) American Society of Anesthesiologists (ASA) (%) I II III IV Operation time Anesthesia time Intraoperative infusion volume Intraoperative blood loss Out of bed activities time (h) Postoperative infusion volume Total infusion volume on the day of surgery VAS score on the day of surgery Day 1 after surgery VAS score POD Hb (g/L) POD ALB (g/L) POD C-reactive protein (CRP) POD IL-6 POD total blood loss 1 day after surgery POD Hb change rate (%)
Summary
The aim of this study was to identify the risk factors associated with prolonged length of stay (LOS) in patients undergoing primary total hip arthroplasty (THA) managed with an enhanced recovery after surgery (ERAS) program and develop a prediction model for improving the perioperative management of THA. Henrik Kehlet [5], a Danish surgeon, has extensively addressed this complex pathophysiological phenomenon in the perioperative period since the late 1980s in collaboration with all surgical disciplines. As such, he used existing basic knowledge to change the perspectives in clinical practice. The ERAS program has been considered an efficient and cost-effective use of health resources
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