Why the study?
Structured pre-surgical data analysis with validated digitized tools may improve risk assessment to balance the benefits of surgery against potential harms.
Does structured risk assessment with a digital health app predict 90-day mortality and complications in adult patients undergoing elective major surgery?
Cohort (n=267)
No
Does structured risk assessment with a digital health app predict 90-day mortality and complications in adult patients undergoing elective major surgery?
A structured digital risk assessment tool effectively predicts 90-day mortality and major complications in patients undergoing elective major surgery.
Answers are grounded in this paper and cite their sources.
Digital risk calculator predicted early postop outcomes; leaves open whether routine app use improves decision-making or reduces complications.
Introduction: Surgery puts patients at relevant risk for complications. Knowing a patient's risk helps to identify modifiable and unmodifiable factors to weigh the benefit of surgery against the risk of harm. A structured data analysis with validated tools will increase the reliability of risk assessment. Digitized solutions may add additional value. The Protego Maxima trial evaluated a health app for structured risk assessment before major surgeries and utilizing. The hypothesis was that the structured assessment is predictive of short-term surgical quality. Methods: Patients undergoing major surgery were risk-scored with the software (The Prehab App), and the scores were correlated with 90-day outcomes (survival, Clavien-Dindo (CD) 1-5 (all complications), and CD 3-5 (major complications)). Results: The study included 267 patients. Mean age was 62.1 ± 12.4 years, the risk analysis index (RAI)-score was 21.5 ± 9.7, the timed up and go (TUG) was 7.7 ± 2.3 seconds, 89 patients (33%) were anemic, and 238 patients had an Eastern Cooperative Oncology Group (ECOG) score of 0 (89.1%), 23 of 1 (8.6%), 6 of 2 or 3 (2.3%) which defined the risk groups (low risk: 156 (58.4%), high risk: 111 (41.6%). Receiver operator characteristics (ROC) showed a highly significant potential of the risk score in its prediction of mortality for the high-risk group (Area Under the Curve Receiver Operator Characteristics: AUROC = 0.842) and for the low-risk group (AUROC = 0,990) with difference in AUROCs of -0.149 (95% CI: -0.263; -0.034; p=0.01). The 90-day mortality was 2.2%. Complication rates were 59.9%; major complication rates were 22.5%. Risk groups (high vs. low) showed significant differences for 90-day survival (99.4% vs. 95.5%; p=0.04) and major complications (16.4% vs. 32.4%; p<0.001). Conclusion: The risk assessment with The Prehab App is a viable method to identify risk factors for mortality before major surgeries. The specific validated scoring tools deliver robust and reliable data.
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Sliwinski et al. (2024) conducted a cohort in Elective major surgery (n=267). High risk score (The Prehab App) vs. Low risk score was evaluated on Prediction of 90-day mortality (AUROC) (Difference in AUROCs -0.149, 95% CI -0.263 to -0.034, p=0.01).
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