Effectiveness of non-pharmacological interventions in reducing pain in preterm infants: A systematic review and network meta-analysis.

OBJECTIVE

To identify the most effective non-pharmacological measures for pain control in preterm infants in the Neonatal Intensive Care Unit (NICU).

METHODS

A Systematic review and network meta-analysis of randomized clinical trials published in English, Portuguese, and Spanish from April 2020 to December 2023. The data sources used were MedLine via PubMed, LILACS, EMBASE, The Cochrane Central Register of Controlled Trials, and Pedro. We performed the risk of bias analysis with Rob 2 and the certainty of the evidence and strength of the recommendation using the Grading of Recommendations Assessment, Development, and Evaluation system. We assessed heterogeneity using the Higgins and Thompson I test, the classification of interventions using the P-score, and inconsistencies using the Direct Evidence Plot.

RESULTS

From 210 publications identified, we utilized 12 studies in analysis with 961 preterm infants, and we combined ten studies in network meta-analysis with 716 preterm infants, and 12 combinations of non-pharmacological measures. With moderate confidence, sensory saturation, sugars, non-nutritive sucking, maternal heart sound, lullaby, breast milk odor/taste, magnetic acupuncture, skin-to-skin contact, and facilitated tucking have been shown to reduce pain in preterm infants when compared to no intervention, placebo, proparacaine or standard NICU routine: sensory saturation [SMD 5,25 IC 95%: -8,98; -1,53], sugars [SMD 2,32 IC 95%: -3,86; -0,79], pacifier [SMD 3,74 IC 95%: -7,30; 0,19], and sugars and pacifier SMD [3,88 IC 95% -7,72; -0,04].

CONCLUSION

Non-pharmacological measures are strongly recommended for pain management in preterm infants in the NICU.

IMPLICATIONS FOR CLINICAL PRACTICE

The findings of this study have important implications for policy and practice. This is the only systematic review that compared the effectiveness of non-pharmacological measures, thus making it possible to identify which measure presents the best results and could be the first choice in clinical decision making.

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