Association between postsurgical pain and heart rate variability: protocol for a scoping review
Bibliographic record
Abstract
INTRODUCTION: Surgical interventions can elicit neuroendocrine responses and sympathovagal imbalance, ultimately affecting cardiac autonomic function. Cardiac complications account for 30% of postoperative complications and are the leading cause of morbidity and mortality following non-cardiac surgery. One cardiovascular parameter, heart rate variability (HRV), has been found to be predictive of postoperative morbidity and mortality. HRV is defined as variation in time intervals between heartbeats and is affected by cardiac autonomic balance. Furthermore, altered HRV has been shown to predict cardiovascular events in non-surgical settings. In multiple studies, experimentally induced pain in healthy humans leads to reduced HRV suggesting a causal relationship. In a different studies, chronic pain has been associated with altered HRV, however, in the setting of clinical pain conditions, it remains unclear how much HRV impairment is due to pain itself versus autonomic changes related to analgesia. We aim to review the available evidence describing the association between postsurgical pain and HRV alterations in the early postoperative period. METHODS AND ANALYSIS: We will conduct a scoping review of relevant studies using detailed searches of MEDLINE and EMBASE, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Included studies will involve participants undergoing non-cardiac surgery and investigate outcomes of (1) measures of pain intensity; (2) measures of HRV and (3) statistical assessment of association between #1 and #2. As secondary review outcomes included studies will also be examined for other cardiovascular events and for their attempts to control for analgesic treatment and presurgical HRV differences among treatment groups in the analysis. This work aims to synthesise available evidence to inform future research questions related to postsurgical pain and cardiac complications. ETHICS AND DISSEMINATION: Ethics review and approval is not required for this review. The results will be submitted for publication in peer-reviewed journals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.050 | 0.063 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.016 | 0.016 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.082 | 0.011 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".