Evidence map›Paper›PMID 41275004›Full record

ArticleSurgical endoscopy2026

Automated tagging of intraoperative physiologic events: understanding the clinical consequences.

Andrew P Bain, Bahaa Succar, Jaffer Odeh, Amr Al Abbas, Samantha Bishop, Mary Grace Reed, Bingchun Wan, Herbert J Zeh, John C Mansour, Sonja Bartolome

Abstract read
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In one paragraph

Article in Surgical endoscopy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Andrew P BainDepartment of Surgery, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9159, USA. Andrew.bain@utsouthwestern.edu.ORCID 0000-0001-5815-8810
Bahaa SuccarDepartment of Surgery, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9159, USA.
Jaffer OdehDepartment of Anesthesiology and Pain Management, UT Southwestern Medical Center, Dallas, TX, USA.
Amr Al AbbasDepartment of Surgery, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9159, USA.
Samantha BishopDepartment of Quality and Operational Excellence, UT Southwestern Medical Center, Dallas, TX, USA.
Mary Grace ReedDepartment of Quality and Operational Excellence, UT Southwestern Medical Center, Dallas, TX, USA.
Bingchun WanDepartment of Surgery, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9159, USA.
Herbert J ZehDepartment of Surgery, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9159, USA.
John C MansourDepartment of Surgery, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9159, USA.
Sonja BartolomeDepartment of Pulmonary and Critical Care Medicine, UT Southwestern Medical Center, Dallas, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionHypotension, hypoxia, and hypothermia tissue have unclear effects on postoperative outcomes. The Operating Room Black Box™ (ORBB) is a novel monitoring platform that automates "tagging" of intraoperative hypotension, hypoxia, and hypothermia. We hypothesized that intraoperative physiologic event tags would serve as predictive variables of adverse postoperative outcomes.

methodsUsing the ORBB, tags were prospectively applied for moderate and severe episodes of hypotension, hypothermia, and hypoxia. Regression modeling was performed to examine the association between intraoperative tags and adverse outcomes of surgical site infection, patient safety indicator (PSI) events, length of stay, readmission, return to OR, and mortality.

results2875 cases were performed and monitored with the ORBB tag system between August 17, 2020 and September 3, 2022. 567 cases (19%) were tagged. Regression models had improved performance after adding in intraoperative physiologic data. Hypothermia and hypoxia were independent predictors of increased return to the operating room (p < 0.02, p < 0.01, respectively). Hypotension was an independent predictor of length of stay (p < 0.03) and patient safety indicator events (p = 0.03). Comorbidities, length of case, BMI, age, and ASA status played significant roles in the predictive models.

conclusionIntraoperative physiologic events are important variables to consider regarding postoperative complications and should be incorporated into quality and safety analysis. As real-time OR data monitoring becomes a reality, work must be done to identify the intraoperative events and patient factors that most affect outcomes. This retrospective modeling serves as the first step toward intraoperative predictive analytics that can provide decision support for postoperative care.

Indexed as

HypotensionHypothermiaHypoxiaIntraoperative ComplicationsMonitoring, IntraoperativePostoperative ComplicationsAdultAgedFemaleHumansLength of StayMaleMiddle AgedPatient SafetyProspective StudiesAutomationIntraoperative eventsIntraoperative safety

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.