Infectious Complications Following Regional Anesthesia: A Narrative Review and Contemporary Estimates of Risk
Bibliographic record
Abstract
INTRODUCTION: Infectious complications following regional anesthesia (RA) while rare, can be devastating. The objective of this review was to estimate the risk of infectious complications following central neuraxial blocks (CNB) such as epidural anesthesia (EA), spinal anesthesia (SA) and combined spinal epidural (CSE), and peripheral nerve blocks (PNB). MATERIALS AND METHODS: A literature search was conducted in PubMed, Embase and Cochrane databases to identify reference studies reporting infectious complications in the context of RA subtypes. Both prospective and retrospective studies providing incidence of infectious complications were included for review to provide pooled estimates (with 95% CI). Additionally, we explored incidences specifically associated with spinal anesthesia, incidences of central nervous system (CNS) infections and, the incidences of overall and CNS infections following CNB in obstetric population. RESULTS: The pooled estimate of overall infectious complications following all CNB was 9/100 000 (95% CI: 5, 13/100 000). CNS infections following all CNB was estimated to be 2/100 000 (95% CI: 1, 3/100 000) and even rarer following SA (1/100 000 (95% CI: 1, 2/100 000)). Obstetric population had a lower rate of overall (1/100 000 (95% CI: 1, 3/100 000)) and CNS infections (4 per million (95% CI: 0.3, 1/100 000)) following all CNB. For PNB catheters, the reported rate of infectious complications was 1.8% (95% CI: 1.2, 2.5/100). DISCUSSION: Our review suggests that the risk of overall infectious complications following neuraxial anesthesia is very rare and the rate of CNS infections is even rarer. The infectious complications following PNB catheters seems significantly higher compared with CNB. Standardizing nomenclature and better reporting methodologies are needed for the better estimation of the infectious complications.
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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 | 0.006 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".