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Record W4312116104 · doi:10.1186/s13643-022-02156-3

Postoperative pain and pain management and neurocognitive outcomes after non-cardiac surgery: a protocol for a series of systematic reviews

2022· article· en· W4312116104 on OpenAlexaffabout
Maram Khaled, Denise Sabac, Maura Marcucci

Bibliographic record

VenueSystematic Reviews · 2022
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsHamilton Health SciencesImpactMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsMedicineRandomized controlled trialDeliriumMEDLINEOpioidChronic painCINAHLChecklistIncidence (geometry)AnesthesiaPhysical therapyIntensive care medicineInternal medicinePsychiatryPsychological intervention

Abstract

fetched live from OpenAlex

BACKGROUND: Postoperative delirium (POD) is common after non-cardiac surgery in older adults and can result in increased risk of adverse outcomes including postoperative cognitive dysfunction (POCD). Pain after surgery is also frequent and can persist as chronic postsurgical pain (CPSP). Evidence is inconsistent and controversial on whether acute and chronic postsurgical pain, and different postoperative pain management strategies (including opioid versus opioid-sparing strategies), is associated with the occurrence of POD and POCD. In this protocol, we propose a series of systematic reviews to answer the following research questions: In adults undergoing non-cardiac surgery, (1) is acute postsurgical pain associated with POD and/or POCD? (2) Are opioid-sparing/avoidance strategies of acute postoperative pain management associated with lower incidence and/or severity of POD and POCD, compared to predominantly opioid-based strategies? (3) Is CPSP associated with POCD? (4) Are opioid-sparing management strategies of CPSP associated with lower incidence and/or severity of POCD compared to standard of care or strategies not aiming at reduced opioid use? METHODS: We will search MEDLINE, EMBASE, Cochrane (CENTRAL), CINAHL, and PSYCHINFO. According to the research question, we will include cohort and case-control studies (questions 1 and 3) or randomized controlled trials and non-randomized studies (questions 2 and 4). The risk of bias will be assessed independently and in duplicate using the revised Cochrane risk-of-bias tool, the Newcastle-Ottawa Scale, and the Joanna-Briggs Institute critical appraisal checklist. Disagreements will be resolved by a third reviewer. Findings will be reported narratively, and where possible and appropriate, meta-analyses will be performed. Certainty of evidence will be assessed using the Grading of Recommendations Assessment, Development, and Evaluation approach. We will conduct the reviews in accordance with the guideline of the Preferred Reporting Items for Systematic Review and Meta-Analyses Protocols. DISCUSSION: Our systematic reviews will summarize available evidence to date on the association of postoperative pain and its management strategies with the incidence of POD and POCD in non-cardiac surgery. We will evaluate the existing evidence and its limitations and inform the design of future interventional studies comparing the effects of different pain management strategies on postoperative neurocognitive outcomes. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021192105.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.020
metaresearch head score (Gemma)0.032
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.120
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.032
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.053
GPT teacher head0.328
Teacher spread0.275 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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

Citations11
Published2022
Admission routes2
Has abstractyes

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