Asian spine journal · 2026
Development of a nomogram to predict the functional independence of activities of daily living in patients undergoing lumbosacral spine surgery: a retrospective study in Thailand.
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Thitithunwarat Nutkritta, Suksophonthana Nattakitta, Nisamaneepong Chuenchob, Kanyapila Paweena, Tanasakampai Arnuphap, Adchaithor Piangdaw, Sucharit Wiraphong
Аннотация
STUDY DESIGN: A retrospective study.
PURPOSE: To develop a nomogram to predict functional independence (FI) in patients undergoing lumbosacral spine surgery (LSSS).
OVERVIEW OF LITERATURE: LSSS aims to improve functional outcomes and restore activities of daily living. We hypothesized that demographic, clinical, surgical, and neurological characteristics could be used to predict FI, as defined by the Barthel index (BI) scores.
METHODS: The medical records of patients who underwent LSSS between October 2023 and September 2024 were reviewed. Univariate and multivariate logistic regression analyses were used to construct a predictive nomogram. Model performance was assessed using receiver operating characteristic curve analysis for discrimination and a bootstrap-based plot for calibration. Decision curve analysis and the Youden index were used to determine the optimal threshold probability for identifying patients requiring additional rehabilitation.
RESULTS: The study included 111 patients (35 men and 76 women; mean age, 63.66±11.37 years), of whom 68 (61.26%) achieved FI. The nomogram, incorporating preoperative BI score, hospital stay <7 days, and absence of metabolic comorbidities and postoperative anemia, demonstrated excellent discrimination (area under the receiver operating characteristic curve=0.91; 95% confidence interval, 0.84- 0.98) and good calibration with the goodness-of-fit test (p>0.05). The optimal threshold probability cutoff was 0.58, with a sensitivity of 84% and specificity of 88%. This tool demonstrated excellent discriminative ability between patients who required further rehabilitation and those who did not, with a Youden index of 0.71.
CONCLUSIONS: This nomogram exhibited excellent discrimination and good calibration and could serve as a predictive tool for FI on the day of hospital discharge. Its application may support discharge planning and facilitate patient stratification to optimize postoperative rehabilitation.
PURPOSE: To develop a nomogram to predict functional independence (FI) in patients undergoing lumbosacral spine surgery (LSSS).
OVERVIEW OF LITERATURE: LSSS aims to improve functional outcomes and restore activities of daily living. We hypothesized that demographic, clinical, surgical, and neurological characteristics could be used to predict FI, as defined by the Barthel index (BI) scores.
METHODS: The medical records of patients who underwent LSSS between October 2023 and September 2024 were reviewed. Univariate and multivariate logistic regression analyses were used to construct a predictive nomogram. Model performance was assessed using receiver operating characteristic curve analysis for discrimination and a bootstrap-based plot for calibration. Decision curve analysis and the Youden index were used to determine the optimal threshold probability for identifying patients requiring additional rehabilitation.
RESULTS: The study included 111 patients (35 men and 76 women; mean age, 63.66±11.37 years), of whom 68 (61.26%) achieved FI. The nomogram, incorporating preoperative BI score, hospital stay <7 days, and absence of metabolic comorbidities and postoperative anemia, demonstrated excellent discrimination (area under the receiver operating characteristic curve=0.91; 95% confidence interval, 0.84- 0.98) and good calibration with the goodness-of-fit test (p>0.05). The optimal threshold probability cutoff was 0.58, with a sensitivity of 84% and specificity of 88%. This tool demonstrated excellent discriminative ability between patients who required further rehabilitation and those who did not, with a Youden index of 0.71.
CONCLUSIONS: This nomogram exhibited excellent discrimination and good calibration and could serve as a predictive tool for FI on the day of hospital discharge. Its application may support discharge planning and facilitate patient stratification to optimize postoperative rehabilitation.