Bibliographic record
Abstract
OBJECTIVE: This systematic review aims to evaluate current choices in practice and outcomes of biomaterials used in patch repair of congenital diaphragmatic hernia (CDH). BACKGROUND: Multiple biomaterials, both novel and combinations of pre-existing materials are employed in patch repair of large size CDHs. METHODS: A literature search was performed across Embase, Medline, Scopus, and Web of Science. Publications that explicitly reported patch repair, material used, and recurrences following CDH repair were selected. RESULTS: Sixty-three papers were included, presenting data on 4595 patients, of which 1803 (39.2%) were managed using 19 types of patches. Goretex® (GTX) (n=1106) was the most frequently employed patch followed by Dualmesh® (n=267), Surgisis® (n=156), Marlex®/GTX® (n=56), Tutoplast dura® (n=40), Dacron® (n=34), Dacron®/GTX® (n=32), Permacol® (n=24), Teflon® (n=24), Surgisis®/GTX® (n=15), Sauvage® Filamentous Fabric (n=13), Marlex® (n=9), Alloderm® (n=8), Silastic® (n=4), Collagen coated Vicryl® mesh (CCVM) (n=1), Mersilene® (n=1), and MatriStem® (n=1) Biomaterials were further subgrouped as: synthetic nonresorbable (SNOR) (n=1458), natural resorbable (NR) (n=241), combined natural and synthetic nonresorbable (NSNOR) (n=103), and combined natural and synthetic resorbable (NSR) (n=1). The overall recurrence rate for patch repair was 16.6% (n=299). For patch types with n>20, recurrence rate was lowest in GTX/Marlex (3.6%), followed by Teflon (4.2%), Dacron (5.6%), Dualmesh (12.4%), GTX (14.8%), Permacol (16.0%), Tutoplast Dura (17.5%), SIS/GTX (26.7%), SIS (34.6%), and Dacron/GTX (37.5%).When analyzed by biomaterial groups, recurrence was highest in NSR (100%), followed by NR (31.5%), NSNOR (17.5%), and SNOR the least (14.0%). CONCLUSION: In this cohort, over one-third of CDH were closed using patches. To date, 19 patch types/variations have been employed for CDH closure. GTX is the most popular, employed in over 60% of patients; however, excluding smaller cohorts (n<20), GTX/Marlex is associated with the lowest recurrence rate (3.6%). SNOR was the material type least associated with recurrence, while NSR experienced recurrence in every instance.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".