A Nomogram for Predicting the Risk of Spinal Anesthesia-Induced Hypotension in Older Patients

TL;DR

This study developed a tool to predict the risk of low blood pressure after spinal anesthesia in older patients, using factors like age, BMI, and heart measurements.

Contribution

A new nomogram was developed and validated for predicting spinal anesthesia-induced hypotension in older patients.

Findings

The nomogram achieved high accuracy in predicting hypotension (AUC = 0.885).

Age, BMI, bupivacaine dose, and heart-related factors were significant predictors.

The tool showed good generalizability through internal and external validation.

Abstract

Background: Hypotension is a common complication following spinal anesthesia, and it is particularly prevalent in older patients. The study aimed to develop and validate a nomogram integrating echocardiographic and clinical predictors for spinal anesthesia-induced hypotension (SAIH) in older patients. Methods: This was an observational cohort study conducted at Peking University People’s Hospital. A total of 865 older patients (age ≥ 65), enrolled from 1 January 2023 to 31 December 2024, were randomly split into a training set (70%) and an internal validation set (30%). For temporal external validation, 349 patients from January to March 2025 were enrolled. LASSO, univariable, and multivariate logistic regression analyses were used to identify predictive factors. A nomogram was subsequently developed based on the results of multivariate logistic regression, and its predictive efficacy was evaluated via both internal and temporal external validation. Results: SAIH occurred in 271 patients (44.8%) in the training set, 110 patients (42.3%) in the internal validation set, and 173 patients (49.6%) in the external validation set. Age, body mass index (BMI), bupivacaine dose, sensory block level, baseline systolic blood pressure (SBP), history of hypertension, interventricular septum thickness at end-diastole (IVSd), early diastolic mitral annular velocity (e’), and E/e’ ratio were significant predictors of SAIH on multivariate analysis. The diagnostic performance of the nomogram was favorable (AUC = 0.885, 95% CI: 0.859–0.911). The AUC values of the internal validation set and temporal external validation set were 0.856 (0.811–0.901) and 0.895 (0.863–0.927). Conclusions: This study identifies age, BMI, bupivacaine dose, sensory block level, baseline SBP, history of hypertension, and IVSd as predictors of SAIH with good discrimination and clinical utility. We present a predictive nomogram that accurately predicts SAIH in older patients. The external validation illustrates its generalizability.

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