The short‐term psychological impact of complications after breast reconstruction
Bibliographic record
Abstract
OBJECTIVES: Few studies have focused on the psychological impact of postoperative complications after breast reconstruction (BR). As postoperative complications after BR usually lead to a prolonged recovery time and sometimes require additional surgery, the short-term impact on distress was investigated. METHODS: Pre- and postoperatively, psychological questionnaires were sent to 152 women who underwent either implant BR or deep inferior epigastric artery perforator flap BR (DIEPBR). In addition, patients and physicians' reports of postoperative complications during the first 4-6 weeks after BR were scored. The course of anxiety, depression and cancer-specific distress, and the effect of complications on distress were investigated. RESULTS: Implant BR patients reported decreased anxiety after surgery, and both groups reported reduced cancer-specific distress after surgery. However, depressive symptoms tended to increase after DIEPBR. If complications occurred, both reconstruction groups reported increased depressive and anxiety symptoms, and DIEPBR patients even had depressive symptoms of clinical concern. A significant number of patients with complications reported alarming levels of distress. Timing and laterality were not significantly correlated with distress. CONCLUSIONS: Complications after BR have a significant impact on emotional well-being shortly after surgery. As distress affects quality of life and health outcomes, it is of great importance to offer psychological support to these patients. Distress can be evaluated by monitoring the emotional impact of BR during post-surgery consults, or with the standard use of short psychological questionnaires that patients can complete at home.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".