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Record W3200253919 · doi:10.1213/ane.0000000000005739

Association Between Intraoperative Arterial Hypotension and Postoperative Delirium After Noncardiac Surgery: A Retrospective Multicenter Cohort Study

2021· article· en· W3200253919 on OpenAlexaff
Luca J. Wachtendorf, Omid Azimaraghi, Peter Santer, Felix C. Linhardt, Michael Blank, Aiman Suleiman, Curie Ahn, Yinghui Low, Bijan Teja, Samir Kendale, Maximilian S. Schaefer, Timothy T. Houle, Richard J. Pollard, Balachundhar Subramaniam, Matthias Eikermann, Karuna Wongtangman

Bibliographic record

VenueAnesthesia & Analgesia · 2021
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineInterquartile rangeDeliriumOdds ratioAnesthesiaRetrospective cohort studyConfidence intervalMean arterial pressureSurgeryBlood pressureInternal medicineHeart rateIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: It is unclear whether intraoperative arterial hypotension is associated with postoperative delirium. We hypothesized that intraoperative hypotension within a range frequently observed in clinical practice is associated with increased odds of delirium after surgery. METHODS: Adult noncardiac surgical patients undergoing general anesthesia at 2 academic medical centers between 2005 and 2017 were included in this retrospective cohort study. The primary exposure was intraoperative hypotension, defined as the cumulative duration of an intraoperative mean arterial pressure (MAP) <55 mm Hg, categorized into and short (<15 minutes; median [interquartile range {IQR}], 2 [1-4] minutes) and prolonged (≥15 minutes; median [IQR], 21 [17-31] minutes) durations of intraoperative hypotension. The primary outcome was a new diagnosis of delirium within 30 days after surgery. In secondary analyses, we assessed the association between a MAP decrease of >30% from baseline and postoperative delirium. Multivariable logistic regression adjusted for patient- and procedure-related factors, including demographics, comorbidities, and markers of procedural severity, was used. RESULTS: Among 316,717 included surgical patients, 2183 (0.7%) were diagnosed with delirium within 30 days after surgery; 41.7% and 2.6% of patients had a MAP <55 mm Hg for a short and a prolonged duration, respectively. A MAP <55 mm Hg was associated with postoperative delirium compared to no hypotension (short duration of MAP <55 mm Hg: adjusted odds ratio [ORadj], 1.22; 95% confidence interval [CI], 1.11-1.33; P < .001 and prolonged duration of MAP <55 mm Hg: ORadj, 1.57; 95% CI, 1.27-1.94; P < .001). Compared to a short duration of a MAP <55 mm Hg, a prolonged duration of a MAP <55 mm Hg was associated with greater odds of postoperative delirium (ORadj, 1.29; 95% CI, 1.05-1.58; P = .016). The association between intraoperative hypotension and postoperative delirium was duration-dependent (ORadj for every 10 cumulative minutes of MAP <55 mm Hg: 1.06; 95% CI, 1.02-1.09; P =.001) and magnified in patients who underwent surgeries of longer duration (P for interaction = .046; MAP <55 mm Hg versus no MAP <55 mm Hg in patients undergoing surgery of >3 hours: ORadj, 1.40; 95% CI, 1.23-1.61; P < .001). A MAP decrease of >30% from baseline was not associated with postoperative delirium compared to no hypotension, also when additionally adjusted for the cumulative duration of a MAP <55 mm Hg (short duration of MAP decrease >30%: ORadj, 1.13; 95% CI, 0.91-1.40; P = .262 and prolonged duration of MAP decrease >30%: ORadj, 1.19; 95% CI, 0.95-1.49; P = .141). CONCLUSIONS: In patients undergoing noncardiac surgery, a MAP <55 mm Hg was associated with a duration-dependent increase in odds of postoperative delirium. This association was magnified in patients who underwent surgery of long duration.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.244
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations139
Published2021
Admission routes1
Has abstractyes

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