ArticlePatient safety in surgery2024
Predictive value of a novel digital risk calculator to determine early patient outcomes after major surgery: a proof-of-concept pilot study.
Article in Patient safety in surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- [Prehabilitation for nononcological patients in visceral surgery].Chirurgie (Heidelberg, Germany) · 2025Pooled it
- Artificial intelligence and machine learning in transplantation surgery care pathway.World journal of transplantation · 2026Review
- Article
- Incidence of failure-to-rescue after coronary artery bypass grafting: a multicenter observational study from the REPLICCAR II registry in Brazil.Patient safety in surgery · 2025Article
- Validity, Accuracy, and Safety Assessment of an Aerobic Interval Training Using an App-Based Prehabilitation Program (PROTEGO MAXIMA Trial) Before Major Surgery: Prospective, Interventional Pilot Study.JMIR mHealth and uHealth · 2025Article
- Machine learning approaches for improvement of patient safety in surgery.Patient safety in surgery · 2024Article
- Usability Testing of a Digitized Interventional Prehabilitation Tool for Health Care Professionals and Patients Before Major Surgeries: Formative and Summative Evaluation.JMIR formative research · 2024Article
- Introduction of AI Technology for Objective Physical Function Assessment.Bioengineering (Basel, Switzerland) · 2024Review
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Authors and funding
16 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundA structured risk assessment of patients with validated and evidence-based tools can help to identify modifiable factors before major surgeries. The Protego Maxima trial investigated the value of a new digitized risk assessment tool that combines tools which can be easily used and implemented in the clinical workflow by doctors and qualified medical staff. The hypothesis was that the structured assessment and risk-grouping is predictive of short-term surgical quality reflected by complications and overall survival.
methodsThe Protego Maxima Trial was a prospective cohort analysis of patients undergoing major surgery (visceral, thoracic, urology, vascular and gynecologic surgeries) as key inclusion criterion and the absence of an acute or acute on chronically decompensated pulmo-cardiovascular decompensation. Patients were risk-scored with the software (The Prehab App) that includes a battery of evidence-based risk assessment tools that allow a structured risk assessment. The data were grouped to predefined high and low risk groups and aggregate and individual scores. The primary outcome was to validate the predictive value of the RAI score and the TUG for overall survival in the high and low risk groups. Secondary outcomes were surgical outcomes at 90-days after surgery (overall survival, Clavien-Dindo (CD) 1-5 (all complications), and CD 3-5 (major complications)). The study was carried out in accordance with the DIN ISO 14,155, and the medical device regulation (MDR) at Frankfurt University Hospital between March 2022 and January 2023.
resultsIn total 267 patients were included in the intention to treat analysis. The mean age was 62.1 ± 12.4 years. Patients with a RAI score > 25 and/or a timed up and go (TUG) > 8 s had a higher risk for mortality at 90 days after surgery. The low-risk group predicted beneficial outcome and the high-risk group predicted adverse outcome in the ROC analysis (Area Under the Curve Receiver Operator Characteristics: AUROC > 0.800; p = 0.01). 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).
conclusionThe proof-of-concept trial showed that a risk assessment with 'The Prehab App' may be viable to estimate the preoperative risk for mortality and major complications before major surgeries. The overall performance in this initial set of data indicated a certain reliability of the scoring and risk grouping, especially of the RAI score and the TUG. A larger data set will be required to proof the generalizability of the risk scoring to every subgroup and may be fostered by artificial intelligence approaches.
trial registrationEthics number: 2021-483-MDR/MPDG-zuständig monocentric; The Federal Institute for Pharmaceuticals and Medical Devices/BfArM, reference number: 94.1.04-5660-13655; Eudamed: CIV-21-07-0307311; German Clinical Trial Registry: DRKS 00026985.
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