Non-pharmacologic techniques for interval intrauterine device placement: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To systematically review the evidence on the effectiveness of non-pharmacologic techniques for interval intrauterine device (IUD) placement. METHODS: We searched various databases from database inception to 15 December 2023 for randomised controlled trials (RCTs) examining non-pharmacologic techniques for IUD placement compared with placebo or pharmacologic techniques. Outcomes of interest were pain experienced with IUD placement, provider ease of placement, need for adjunctive placement measures, placement success, patient satisfaction, side effects and adverse events. We extracted data from included articles, assessed risk of bias, and determined certainty of evidence for all outcomes. RESULTS: Eleven RCTs met the inclusion criteria, examining 10 different non-pharmacologic techniques. The risk of bias was high in 10 trials and low in 1 trial. Of 11 RCTs that examined patient pain, two found reduced pain with the Valsalva breathing technique (where women inhaled deeply and held their breath during IUD placement), without tenaculum placement compared with routine care (i.e., use of a tenaculum) (OR 0.04; 95% CI 0.01 to 0.15) or acupuncture compared with routine care (mean difference -1.88; 95% CI -2.72 to -1.04). None of the four trials that assessed ease of IUD placement found differences between study groups. Across nine RCTs, most had high rates of placement success. One study each examined need for cervical dilation and patient satisfaction; the findings were similar between study groups. Overall, few side effects and no adverse events were reported across the studies. CONCLUSIONS: Non-pharmacologic techniques like the Valsalva manoeuvre and acupuncture may reduce patient pain with IUD placement (certainty of evidence ranging from moderate to low). However, evidence is limited, and more high-quality trials with larger sample sizes are needed. PROSPERO REGISTRATION NUMBER: CRD42024507788.
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 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 | 0.010 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".