Cost of Care and Surgical Outcomes between Direct-to-Implant and Staged Tissue Expander Breast Reconstruction
Bibliographic record
Abstract
BACKGROUND: Implant-based breast reconstruction (IBBR) can be performed in a single stage (direct to implant [DTI]) or 2 stages using a tissue expander (TE). Fixed costs and postoperative complications can incur a significant financial burden. In this article, we compare direct costs of DTI to TE IBBR and determine price drivers to ascertain their relative costs. METHODS: A retrospective chart review and analysis of specific cost data provided by the authors' institutional finance department of patients who underwent IBBR was conducted to evaluate differences in costs during an episode of care (EOC). Multivariable regression analysis and 1-way sensitivity analysis were conducted to determine key price drivers for each operation. RESULTS: A total of 205 patients (310 breasts) undergoing DTI ( n = 167 [54%]) or staged TE ( n = 143 [46%]) reconstruction were evaluated over their entire EOC. The DTI cohort had a lower rate of major complications (13% versus 22%; P = 0.033) but similar rates of aesthetic revisions (18% versus 19%; P = 0.835). The average cost of a DTI reconstruction ($13,719.39 ± $5499) was significantly lower than for staged TE patients ($16,589.54 ± $6586.95; P < 0.001), with lower operative costs ($10,460.2 ± $4059.81 and $12,242.87 ± $4403.81; P = 0.002) and number of postoperative visits (13.27 ± 7.76 and 23.03 ± 9.05; P < 0.001). There were no differences in operative costs from complications and aesthetic revisions. The cost of a DTI reconstruction is most sensitive to the rate of bilateral operations. For staged TE reconstruction, the episodic cost is most sensitive to the incorporation of acellular dermal matrices. CONCLUSION: DTI breast reconstruction incurs lower cost over an EOC compared with staged TE reconstruction, because of greater planned operative costs and number of postoperative follow-ups in the TE group.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".