Perioperative medicine & outcomes
Dynamic Nomogram for Predicting the Risk of Perioperative Neurocognitive Disorders in Adults
Authors' conclusion
We developed a simple and rapid online tool to preoperatively screen patients' risk of PND using GLM based on multicenter data
Study context
- Population
- Surgical patients older than 45 years undergoing GA without history of PND, 3 academic hospitals in China; external validation on multiparameter intelligent monitoring in intensive care (MIMIC) Ⅳ1,051 multicentre + 2884 MIMIC Ⅳ analysed
- Comparison
- General linear model (GLM) vs artificial neural network (ANN) vs naive Bayes (NB) models for predicting PND
- Outcome
- Discrimination for PND (ROCAUC, PRAUC, Brier score, IPA, sensitivity, specificity)
Methodological detailsmulticentre, machine learning, case-control sampling 3:1, external validation, Online tool with 10 routine variables developed for preoperative screening
- Multicentre
- Machine learning
- Case-control sampling 3:1
- External validation
- Online tool with 10 routine variables developed for preoperative screening
Performance
As reported in the abstract
GLM performance on validation-1 dataset
| Test or model | ROCAUC | PRAUC | Sensitivity | Specificity | Brier score | Index of prediction accuracy (IPA) |
|---|---|---|---|---|---|---|
| GLM | 0.874 (95% CI 0.833-0.915) | 0.685 (95% CI 0.584-0.786) | 72.6% (95% CI 61.4%-81.5%) | 84.4% (95% CI 79.3%-88.4%) | 0.131 | 44.7% |
GLM
ROCAUC0.874 (95% CI 0.833-0.915)
PRAUC0.685 (95% CI 0.584-0.786)
Sensitivity72.6% (95% CI 61.4%-81.5%)
Specificity84.4% (95% CI 79.3%-88.4%)
Brier score0.131
Index of prediction accuracy (IPA)44.7%
Further findings
- GLM performance on validation-2 dataset (MIMIC Ⅳ)
- 0.761 (95% CI 0.712-0.809) · ROCAUC · PRAUC 0.475 (95% CI 0.370-0.581) · Brier score 0.053 · IPA 76.8%
Original publication
Dynamic Nomogram for Predicting the Risk of Perioperative Neurocognitive Disorders in Adults. Anesth Analg. Published 18 October 2023. doi:10.
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