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Enregistrement W4411413448 · doi:10.2106/jbjs.25.00366

Skin Antisepsis: When New Evidence Emerges, Reevaluate Your Practice

2025· article· en· W4411413448 sur OpenAlexaff
Gerard P. Slobogean, Nathan N. O’Hara, Sheila Sprague

Notice bibliographique

RevueJournal of Bone and Joint Surgery · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueWound Healing and Treatments
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésMedicineComputer science

Résumé

récupéré en direct d'OpenAlex

Commentary We thank Dr. Datti for drawing attention to the PREPARE (A Pragmatic Randomized Trial Evaluating Preoperative Alcohol Skin Solutions in Fractured Extremities) trial results published in The New England Journal of Medicine (NEJM). We categorically disagree with his assertions: The current 90-day surveillance period for the primary outcome was appropriate because the rationale for skin antisepsis preventing infections that present months later is mechanistically questionable, and prolonged surveillance would have been susceptible to the competing risk of other exogenous causes. Sample-size estimates are designed to balance the risk of type-I and II errors. Although we observed a significant effect sizesmaller than hypothesized (odds ratio [OR], 0.76 instead of 0.64), our estimate was based on the best available evidence2,3. Similarly, the primary statistical approach used null-hypothesis testing with significance set at p < 0.05. The p value for the primary comparison was below this threshold, and the null hypothesis was rejected. NEJM copy editing rounded the confidence interval (CI) to 1.00. As indicated by Dr. Datti, the Appendix of the published study1 reports the CI with greater precision and confirms it was <1.000. The interpretation of the fragility index is incorrect and dangerous. In this cohort of 6,785 patients with closed fractures, 185 patients experienced a surgical site infection (SSI). It is true that a few more infections in the iodine group would alter the statistical conclusion; however, it must be noted that an appropriately designed trial intentionally recruits just enough patients to observe an effect that can reject the null hypothesis (according to the sample-size estimate). It should also be noted that the fragility index is designed for use with a Fisher exact test. It cannot be applied to the estimates obtained from the multilevel statistical model used to account for the correlation between the recruitment clusters and the alternating treatment periods. In addition, a properly conducted trial should never have a large fragility index because it would be unethical to keep randomizing patients to receive an inferior treatment beyond the necessary confidence to reject the null hypothesis. We have referenced a few elegant editorials on this topic4,5. A subgroup effect assesses whether a treatment works better or worse in certain subpopulations. We used the ICEMAN (Instrument for assessing the Credibility of Effect Modification Analyses) criteria for considering potential subgroup effects6. Bacterial pathogens (an outcome) and surgical trauma (an intervention) occur downstream from the exposure (antisepsis); these are not baseline characteristics that meet credible subgroup criteria. The assertion that the magnitude of benefit should increase with the severity of the clinical condition is flawed. It is unclear why one would assume that skin antisepsis is expected to be more effective in a highly contaminated open fracture with a diverse and high concentration of bacteria compared with a closed-fracture surgical site with only skin flora. Yet, the estimated absolute SSI reductions in the closed and fracture cohorts were similar (0.8% and 0.9%, respectively); this similar effect did not reach significance in the open fracture group because the baseline risk was higher—presumably from the environmental contamination that allowed bacteria to infiltrate the wound hours prior to the skin antisepsis. Finally, we agree that clinical medicine is a probabilistic science. We also performed a Bayesian analysis, which was reported in the Appendix of the published study1. Using a neutral moderate prior that assumes no treatment benefit from iodine povacrylex, our trial data suggest a 97% probability of any treatment benefit (OR, <1.0) for patients with closed fracture and a 74% probability for patients with open fracture. These probabilities of benefit far exceed the theoretical concern for iodine-related thyroid toxicity in adult patients or the case reports of life-threatening anaphylaxis from chlorhexidine antisepsis7. We conclude by inviting readers to reflect on the clinical decision. Skin antisepsis is a mandatory step prior to surgical incision. The surgeon must use a solution, and in most hospitals in North America, alcohol-based solutions of chlorhexidine gluconate and iodine povacrylex are shelved next to each other. The availability, ease of use, and cost are essentially identical. Yet, the surgeon must still choose one. The PREPARE trial provides the best available evidence to guide this choice for orthopaedic surgeons. The results suggest a clinically important benefit to skin antisepsis with iodine povacrylex in alcohol over chlorhexidine gluconate in alcohol for closed fractures, and no harm, with potential benefit, for open fractures. When new data emerge, we reevaluate our practice—and we hope that you do, too.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,066
score de la tête « metaresearch » (Gemma)0,396
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,066
Score d'incertitude au seuil0,348

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0660,396
Méta-épidémiologie (sens strict)0,0020,002
Méta-épidémiologie (sens large)0,0050,004
Bibliométrie0,0050,004
Études des sciences et des technologies0,0030,010
Communication savante0,0090,021
Science ouverte0,0110,004
Intégrité de la recherche0,0400,049
Charge utile insuffisante (le modèle a refusé de juger)0,0160,009

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,131
Tête enseignante GPT0,384
Écart entre enseignants0,253 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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