Notice bibliographique
Résumé
Xue et al. point out that not all potential variables were considered in our analyses and suggest that body mass index and ethnicity may confound the association between hypotension and organ injury. Revised models that include these two variables demonstrate no important effect on the relationship between hypotension and our outcomes (table 1).Xue et al. also wonder whether organ injury results from the hypotension or its treatment. As we discussed in our article, this certainly needs to be considered when interpreting our results.1 However, including vasopressor use in our analyses is unlikely to be helpful. The issue of indication bias (i.e., the severity of hypotension is correlated to the likelihood of receiving vasopressors and the dose of vasopressor received) is extremely difficult to resolve even with advance statistical techniques. Randomized, controlled trials to prevent hypotension are likely the only sufficiently robust method of determining whether a mean arterial pressure less than 55 mmHg is injurious. Importantly, our work informs the definition of hypotension for any such trial and thereby improves the likelihood treatment can be studied safely and with maximum likelihood of demonstrating a benefit.Xue et al. also question the timing of creatinine and cardiac enzyme determinations in relation to the time of surgery. We defined the outcome as within 7 days of surgery, and our sensitivity analyses restricting the definition to within 3 days of surgery demonstrated no material differences. We agree that early detection of organ injury, particularly in the first 3 days after surgery, is a crucial first step in discovering effective treatments for perioperative events. The Vascular events In noncardiac Surgery patIents cOhort evaluatioN (VISION) study demonstrated that more than half of myocardial injuries would be missed without routine postoperative troponin monitoring during the initial 3 postoperative days.2 Older studies suggest that more than 80% of acute kidney injury, which is usually clinically silent, also typically occurs in a similar time frame and this is corroborated by our study in which 82% of acute kidney injury occurred in the first 3 days after surgery.3 Further researches to establish effective treatments after perioperative complications such as renal and cardiac injury are urgently needed.Xue et al.’s final comment suggests that we need to determine the cause of death and its relatedness to organ injury. This information is not available in our dataset; furthermore, we do not believe that relatedness can be reliably determined or likely to be immediately helpful. Take for example the following hypothetical scenario. A patient suffers a silent intraoperative myocardial injury that results in postoperative delirium and fatigue and mild acute kidney injury. This results in immobility and ultimately in a venous thromboembolism. The ensuing chest pain is treated with narcotics which along with the some mild thrombotic event results in some pulmonary function compromise. This predisposes the patient to a hospital-acquired pneumonia which is ultimately fatal. Had any one of these factors been avoided, the patient may have survived. However, attributing the cause of death to any single complication of surgery ignores the contributions of the others. Because of the complicated nature of the causal pathways to postoperative death, we do not believe that it is appropriate to examine specific causes of death in analyses such as ours.The authors declare no competing interests.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,066 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,004 | 0,005 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,018 | 0,032 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,042 | 0,034 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».