Question · asked by 1 review

Bilateral extraction of compromised mandibular first permanent molars vs Age- and gender-matched non-extraction controls: Skeletal development (occlusal plane rotation, facial height)

Population
Children (approximately 11 years or older) with compromised mandibular first permanent molars
Intervention
Bilateral extraction of compromised mandibular first permanent molars
Comparison
Age- and gender-matched non-extraction controls
Outcome
Skeletal development (occlusal plane rotation, facial height)

Bilateral lower first permanent molar extraction was associated with counter-clockwise rotation of the occlusal plane and a mild decrease in lower anterior face height in one case-control study; ungraded.

What each review found

Include earlier review versions
FindingEffectStudiesGRADE certainty
Bilateral extraction of compromised mandibular first permanent molars vs Age- and gender-matched non-extraction controls
Skeletal development (occlusal plane rotation, facial height) · Children (approximately 11 years or older) with compromised mandibular first permanent molars · Private clinics (Brazil)
Bilateral lower first permanent molar extraction was associated with counter-clockwise rotation of the occlusal plane and a mild decrease in lower anterior face height in one case-control study; ungraded.
Consequences of early extraction of compromised first permanent molar: a systematic review. (2018) All outcomes
Normando and Cavacami: decreased GnSN angle (P = 0.05), counter-clockwise rotation of the occlusal plane (mean 5.6 vs 12.6 degrees, P = 0.0001), and decreased lower anterior face height (P = 0.048). Table 3: Category…1 studyGRADE not reported

Findings are shown side by side, never pooled across reviews.

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Consequences of early extraction of compromised first permanent molar: a systematic review.
2018 All outcomes
May 2015 to 2017 (literature from 1960 to 2017)19Critically Low / Critically Low
How reviews are matched to this question

Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.