Evidence map›Paper›PMID 41613310›Full record

ArticleFrontiers in medicine2025

Intraoperative hypotension trajectories and their predictive value for major postoperative complications: a retrospective cohort study.

Yingbo Ren, Chang Liu, Xin Wang, Mengwei Zhang, Hongyan Li

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Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yingbo RenDepartment of Anesthesiology, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, China.
Chang LiuDepartment of Anesthesiology, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, China.
Xin WangDepartment of Anesthesiology, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, China.
Mengwei ZhangDepartment of Anesthesiology, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, China.
Hongyan LiDepartment of Anesthesiology, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Intraoperative hypotension (IOH) is a common hemodynamic disturbance during major non-cardiac surgery, yet the prognostic significance of different temporal blood pressure patterns remains unclear. This study aimed to identify distinct IOH trajectories using group-based trajectory modeling (GBTM) and to evaluate their independent and incremental predictive value for major postoperative complications in high-risk surgical patients. Methods: We conducted a retrospective cohort study of 789 adults undergoing elective major abdominal, urologic, or gynecologic surgery between January 2018 and December 2023. Continuous invasive minute-by-minute mean arterial pressure (MAP) recordings were extracted from the anesthesia information management system. IOH was defined as MAP <65 mmHg. GBTM modeled MAP over absolute intraoperative time using polynomial time functions to identify three latent IOH trajectories based on duration and recurrence: transient mild (<10 min), moderate sustained (10-30 min), and prolonged/fluctuating (>30 min or ≥3 episodes). The primary composite outcome included acute kidney injury, postoperative delirium, unplanned ICU admission within 48 h, and 30-day all-cause mortality. Associations were examined using multivariable logistic regression, and predictive performance was evaluated using ROC curves, calibration, bootstrap internal validation, and decision curve analysis. Results: A clear exposure-response relationship was observed across trajectory groups: the primary composite complication occurred in 13.4% of patients in the transient mild group, 20.8% in the moderate sustained group, and 30.7% in the prolonged/fluctuating group (p for trend <0.001). Compared with transient mild hypotension, adjusted odds ratios were 1.58 (95% CI 1.03-2.43) for moderate sustained and 2.42 (95% CI 1.54-3.80) for prolonged/fluctuating trajectories. Incorporating trajectory classification into a clinical model markedly improved discrimination (AUC 0.860 vs. 0.578), calibration, and net clinical benefit compared with conventional IOH measures alone. Conclusion: Distinct intraoperative hypotension trajectories derived from high-resolution arterial pressure data were strongly and independently associated with major postoperative complications and substantially enhanced predictive accuracy beyond standard IOH metrics. Trajectory-based hemodynamic profiling may support individualized blood pressure management and early perioperative risk stratification.

Indexed as

blood pressure trajectorygroup-based trajectory modelingintraoperative hypotensionperioperative risk predictionpostoperative complications

Identifiers

PMID41613310
PMCPMC12847311

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