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DOI 10.1016/j.bja.2025.07.035

Медицинская библиотека · British journal of anaesthesia · 2025

Robotic process automation to identify patients at high risk for perioperative myocardial infarction or injury: a prospective, blinded, paired reader-controlled single-centre study.

Durak Koray, Burri-Winkler Katrin, Huré Gabrielle, Strebel Ivo, Reinhardt Julia, Thommen Vanessa, Pargger Mirjam, Glarner Noemi, Haziri Fisnik, Seeberger Esther, Doyle Nadine, Bolliger Daniel, Steiner Luzius A, Mujagic Edin, Lardinois Didier, Schären Stefan, Mueller Andreas, Mahfoud Felix, Gualandro Danielle Menosi, Puelacher Christian, Mueller Christian

СтатьяНаблюдательное исследованиеПеревод в очереди

Аннотация

BACKGROUND

Although current guidelines recommend active surveillance for perioperative myocardial infarction, injury, or both in high-risk patients, implementation remains limited in most institutions worldwide because of a lack of resources.

METHODS

We hypothesised that robotic process automation (RPA), a software technology that enables virtual bots to replicate human tasks within digital systems, could accurately replace experienced clinical staff. Manual screening by experienced clinical staff and RPA screening were carried out simultaneously and blinded to identify high-risk patients eligible for active surveillance for myocardial infarction/injury, according to predefined screening criteria. Discrepant identification was reviewed by an independent clinician blinded to the origin of the identification, generating a reference standard classification of paired reader-controlled patients to investigate the primary diagnostic endpoint: relative true positive fraction.

RESULTS

In 660 participants (median age 60 yr, interquartile range 42-73 yr, 54.8% female), 77/660 (12%) were eligible for active surveillance for perioperative myocardial infarction or injury according to the reference standard classification. RPA screening achieved 75 (97%) true positive identifications, compared with 63 (82%) identified from manual screening (relative true positive fraction: 1.19, 95% confidence interval 1.08-1.32, P=0.004). The number needed to screen to identify one additional true positive using RPA screening was 6. RPA screening had a sensitivity of 0.97 (0.91-0.99), compared with 0.82 (0.72-0.89) for. Both approaches had high specificity (RPA screening: 0.98 [0.97-0.99], compared with manual screening: 1.0 [0.99-1.00]). The estimated annual cost of RPA screening was 81% lower compared with manual screening.

CONCLUSIONS

RPA screening was superior to standard-of-care manual screening by experienced clinical staff in identifying patients at high risk for perioperative myocardial infarction or injury.

CLINICAL TRIAL REGISTRATION: NCT02573532.

Для цитирования: Durak Koray, Burri-Winkler Katrin, Huré Gabrielle, Strebel Ivo, Reinhardt Julia, Thommen Vanessa, Pargger Mirjam, Glarner Noemi, Haziri Fisnik, Seeberger Esther, Doyle Nadine, Bolliger Daniel, Steiner Luzius A, Mujagic Edin, Lardinois Didier, Schären Stefan, Mueller Andreas, Mahfoud Felix, Gualandro Danielle Menosi, Puelacher Christian, Mueller Christian. Robotic process automation to identify patients at high risk for perioperative myocardial infarction or injury: a prospective, blinded, paired reader-controlled single-centre study.. British journal of anaesthesia. 2025. DOI: 10.1016/j.bja.2025.07.035.

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