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Effectiveness of Acupuncture for Pain Control After Cesarean Delivery

2022· article· en· W4214540077 on OpenAlexaff
Taras Usichenko, Berthold Henkel, Catharina Klausenitz, Thomas Heße, Guillermo Pierdant, Mike Cummings, Klaus Hahnenkamp

Bibliographic record

VenueJAMA Network Open · 2022
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineAcupuncturePlaceboRandomized controlled trialBlindingAnesthesiaVisual analogue scalePatient satisfactionPhysical therapyPlacebo-controlled studyRandomizationAdverse effectClinical trialSurgeryDouble blindInternal medicine

Abstract

fetched live from OpenAlex

IMPORTANCE: A pharmacological approach to pain control after cesarean delivery is often insufficient on its own. Acupuncture is a promising method for mitigating postoperative pain and reducing postoperative opioid requirements. OBJECTIVE: To evaluate the efficacy and effectiveness of acupuncture as an adjunctive therapy for pain control after cesarean delivery, compared with a placebo intervention and standard care alone. DESIGN, SETTING, AND PARTICIPANTS: This single-center, placebo-controlled, patient- and assessor-blinded randomized clinical trial was conducted from January 13, 2015, to June 27, 2018, at a tertiary university hospital in Greifswald, Germany. Participants were women who were scheduled for elective cesarean delivery under spinal anesthesia and were randomized to either the acupuncture group (n = 60) or placebo group (n = 60). Another 60 consecutive patients who met the eligibility criteria and received the standard postoperative analgesia were selected to form a nonrandomized standard care group. The intention-to-treat analysis was performed from August 19, 2019, to September 13, 2019. INTERVENTIONS: In addition to standard pain treatment, each patient in the acupuncture group received auricular and body acupuncture with indwelling intradermal needles, whereas patients in the placebo group were treated with nonpenetrating placebo needles. MAIN OUTCOMES AND MEASURES: The primary outcome was pain intensity on movement, which was measured using an 11-item verbal rating scale. Secondary outcomes were analgesia-related adverse effects, analgesics consumption, time to mobilization and Foley catheter removal, quality of patient blinding to randomization, and patient satisfaction with treatment of pain. RESULTS: A total of 180 female patients (mean [SD] age, 31 [5] years) were included in the intention-to-treat analysis. The mean pain intensity on movement in the acupuncture group on the first postoperative day was lower than in the placebo group (4.7 [1.8] vs 6.0 [2.0] points; Cohen d, 0.73; 95% CI, 0.31-1.01; P = .001) and the standard care group (6.3 [1.3] points; Cohen d, 1.01; 95% CI, 0.63-1.40; P < .001). On the first postoperative day, 59 patients (98%) in the acupuncture group were fully mobilized vs 49 patients (83%) in the placebo group (relative risk [RR], 1.18; 95% CI, 1.06-1.33; P = .01) and 35 patients (58%) in the standard care group (RR, 1.69; 95% CI, 1.36-2.09; P < .001). The Foley catheter was removed in a total of 57 patients (93%) from the acupuncture group vs 43 patients (72%) from the placebo group (RR, 1.33; 95% CI, 1.12-1.57; P = .003) and 42 patients (70%) from the standard care group (RR, 1.37; 95% CI, 1.14-1.62; P = .002). Other parameters were comparable across the 3 study groups. CONCLUSIONS AND RELEVANCE: Results of this trial showed that acupuncture was safe and effective in reducing pain and accelerating mobilization of patients after cesarean delivery. With consideration for personnel and time expenditures, acupuncture can be recommended as routine, supplemental therapy for pain control in patients after elective cesarean delivery. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02364167.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.299
Teacher spread0.285 · 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 designRandomized trial
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".

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Citations76
Published2022
Admission routes1
Has abstractyes

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