EMLA (lidocaine-prilocaine) cream for pain relief during hysterosalpingography: a systematic review and meta-analysis of randomised placebo-controlled trials.
Ahmed Abu-ZaidSaeed BaradwanMohammed AbuzaidRayan AlSghanOsama AlomarHany SalemIsmail A Al-BadawiPublished in: Human fertility (Cambridge, England) (2022)
We systematically investigated the efficacy and safety of EMLA (5% lidocaine-prilocaine cream) versus placebo for pain relief among infertile patients undergoing hysterosalpingography (HSG). We screened four databases from inception until 25 November 2020. We included only randomised placebo-controlled trials (RCTs) and assessed their risk of bias. The main efficacy outcomes included safety and pain scores during the different stages of HSG. The pooled outcomes were summarised as mean difference (MD) with 95% confidence interval (CI). Three RCTs were included, comprising 258 patients (131 and 127 patients received EMLA and placebo, respectively). All RCTs revealed an overall low risk of bias. EMLA significantly reduced pain perception during cervical instrumentation of tenaculum and cannula ( MD = -1.53, 95% CI [-2.59, -0.47], p = 0.005) and at 24 h after completion of HSG ( MD = -1.30, 95% CI [-2.57, -0.03], p = 0.04). Despite EMLA decreased pain perception during the other procedural stages of HSG, the differences were not statistically significant compared with placebo. EMLA was safe and free of local and systemic adverse reactions. This meta-analysis advocates that topical application of 5% EMLA cream is safe and correlates with decreased pain perception during HSG, particularly during the cervical instrumentation step and at 24 h after HSG completion.
Keyphrases
- chronic pain
- placebo controlled
- double blind
- pain management
- neuropathic pain
- end stage renal disease
- patients undergoing
- clinical trial
- systematic review
- newly diagnosed
- chronic kidney disease
- phase iii
- open label
- peritoneal dialysis
- molecular dynamics
- metabolic syndrome
- spinal cord injury
- spinal cord
- type diabetes
- squamous cell carcinoma
- intensive care unit
- machine learning
- single molecule
- skeletal muscle
- obstructive sleep apnea
- adipose tissue
- extracorporeal membrane oxygenation
- artificial intelligence
- electronic health record