Evidence map›Paper›PMID 41703067›Full record

ArticleAesthetic plastic surgery2026

Assessment and AI-Based Prediction of Complications in Reduction Mammoplasty: A Combined Statistical and Fuzzy Inference Approach in a 10-Year Cohort from Tehran Hospitals (2013-2023).

Nahid Nafissi, Pouya Derakhshan-Barjoei, Ebrahim Babaee, Mojdeh Bahadorzadeh

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Article in Aesthetic plastic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Nahid NafissiBreast Health and Cancer Research Center, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0000-0001-7454-9985
Pouya Derakhshan-BarjoeiDepartment of Electrical and Computer Engineering, Artificial Intelligence and Data Analysis Research Center, Science and Research Campus, Islamic Azad University, Tehran, Iran.ORCID http://orcid.org/0000-0001-5296-4555
Ebrahim BabaeePreventive Medicine and Public Health Research Center, Psychosocial Health Research Institute, Department of Community and Family Medicine, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0000-0001-7969-9122
Mojdeh BahadorzadehDepartment of General Surgery, Qom University of Medical Sciences, Qom, Iran. mbahadorzadeh@muq.ac.ir.ORCID http://orcid.org/0000-0002-2370-0478

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionGigantomastia causes physical, psychological, and dermatological issues, often with ptosis; reduction mammoplasty effectively relieves symptoms but carries minor (self-limiting or medically managed) and major (surgically requiring) complications, influenced by factors such as BMI and smoking.

methodThis retrospective cohort study included 439 patients (878 breasts) who underwent reduction mammoplasty by a single surgeon in Tehran hospitals from 2013 to 2023, with data extracted from medical records across three domains: surgical/anthropometric details, past medical history, and patient characteristics. Complications were categorized as major or minor and analyzed using conventional statistics and an artificial intelligence-based fuzzy inference system to predict postoperative outcomes.

resultOur analysis of 439 patients (878 breasts) revealed that suprasternal notch-to-nipple distance (SNN), BMI, smoking, underlying comorbidities, and pedicle type were significantly associated with postoperative complications, while age and weight of tissue resected (WTR) showed no significant effect. The free nipple graft technique and greater SNN were linked to the highest complication rates, with only 14 major complications reported overall, including 4 cases of complete nipple-areola necrosis.

conclusionOur study identifies high BMI, smoking, comorbidities, increased SNN distance, and free nipple graft/inferior pedicle techniques as key predictors of complications in reduction mammoplasty, supporting risk-adapted surgical planning. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Indexed as

BreastHypertrophyMammaplastyPostoperative ComplicationsAdultBody Mass IndexCohort StudiesFemaleHumansIranMiddle AgedNipplesRetrospective StudiesRisk AssessmentSoft ComputingYoung AdultAssessment-complicationReduction mammoplastySurgical techniques

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.