Is obesity a predisposing factor for free flap failure and complications? Comparison between breast and nonbreast reconstruction
Bibliographic record
Abstract
Obesity is a risk factor for postoperative morbidity in breast reconstruction. Although existing studies about nonbreast reconstruction are limited, previous research has demonstrated that obesity is not an important factor in poor outcomes in nonbreast reconstruction. Our study evaluates the effects of obesity on postoperative morbidity in nonbreast reconstruction in comparison to breast reconstruction. A systematic literature review and meta-analysis was performed using Medline, EMBASE, and Cochrane databases. Obesity was extracted for predictor variables and partial, total loss of flap, and complication were extracted for outcome variables. Subgroup analyses were performed according to reconstruction site. The Newcastle-Ottawa scale (NOS) was used to assess the quality of the studies, and the Cochrane risk of bias tool was used. Publication bias was evaluated using funnel plots. The search strategy identified 944 publications. After screening, 19 articles were selected for review. Partial flap loss, total flap loss, and complications in breast reconstruction occurred significantly more often in obese patients in comparison to nonobese patients (OR = 2.479, P = 0.021 for partial loss, OR = 3.083, P = 0.002 for total loss, OR = 2.666, P = 0.001 for complications). In contrast, partial flap loss, total flap loss, and complications in nonbreast reconstruction were not significantly different in obese patients in comparison to nonobese patients (OR = 0.786, P = 0.629 for partial loss, OR = 0.960, P = 0.961 for total loss, and OR = 1.009, P = 0.536 for complications). In contrast to the relationship between obesity and poor outcomes in breast reconstruction, our study suggests the obesity is not a predisposing factor for poor outcomes in nonbreast reconstruction. Long-term studies are needed to confirm these findings.
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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.019 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".