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Record W4220730671 · doi:10.2147/ibpc.s347395

Perioperative Hypertension Etiologies in Patients Undergoing Noncardiac Surgery in University Health Network Hospitals–Canada from 2015–2020

2022· article· en· W4220730671 on OpenAlexaffabout

Bibliographic record

VenueIntegrated Blood Pressure Control · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsPerioperativeEtiologyMEDLINEDiseaseBlood pressure

Abstract

fetched live from OpenAlex

Introduction: Perioperative hypertension, defined as increased blood pressure around the surgery, is a known risk factor for perioperative complications, including cardiovascular events. Identifying reasons associated with hypertension in each period is of great help in preventing and better managing perioperative hypertension. Objective: The aim of the study was to explore common etiologies of hypertension during the perioperative period (pre, intra, and post-operation) in patients who underwent noncardiac surgeries in University Health Network (UHN) hospitals, Canada, from 2015 to 2020. Patients and Methods: We retrospectively analyzed the medical records of 174 patients undergoing noncardiac surgeries who experienced perioperative hypertension. We assessed the prevalence of 10 reasons for perioperative hypertension as a whole and also each period separately according to the physicians' notes in patients' medical records. Two-way measurements ANOVA was used to determine the change of mean hypertension among patients for specific etiology. Results: The common etiologies of perioperative hypertension were poorly controlled hypertension (21.8%), excessive fluid therapy (19.5%), excessive vasopressor (18.4%), and medication withdrawal (13.7%). Regarding each period separately, the most common reasons were poorly controlled hypertension for pre (42.9%) and intraoperative period (22.7%) and fluid overload for the postoperative period (20.1%). Poor control of hypertension showed both within-subject statistical significance for systolic and between-subject statistical significance for diastolic blood pressure. Conclusion: Poorly controlled hypertension is the most significant etiology of perioperative hypertension in patients undergoing noncardiac surgeries. Apart from poorly controlled hypertension, as a patient-related factor, iatrogenic factors such as excessive vasopressor therapy, aggressive fluid replacement and poor management of antihypertensive medications can also cause perioperative hypertension.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.109
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.190
Teacher spread0.185 · 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 teacher head, 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

Citations13
Published2022
Admission routes2
Has abstractyes

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