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Enregistrement W3159962061 · doi:10.1097/cce.0000000000000385

Bias Due to Cohort Construction in the Study of Timing of Invasive Ventilation

2021· article· en· W3159962061 sur OpenAlexaff
Christopher J. Yarnell, Laveena Munshi

Notice bibliographique

RevueCritical Care Explorations · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueRespiratory Support and Mechanisms
Établissements canadiensUniversity of TorontoMount Sinai Hospital
Organismes subventionnairesnon disponible
Mots-clésVentilation (architecture)CohortEnvironmental scienceMedicineEngineeringInternal medicineMechanical engineering

Résumé

récupéré en direct d'OpenAlex

To the Editor: We congratulate the authors of Dupuis et al (1) for their thoughtful and topical article published in the recent issue of Critical Care Explorations. The question of which patients with hypoxemic respiratory failure truly benefit from invasive ventilation, both during and before the coronavirus disease 2019 (COVID-19) pandemic, is a core controversy in Critical Care Medicine. The pandemic has highlighted the fundamental lack of data and analyses that appropriately answer this question. Dupuis et al (1) attempt to address this important and challenging question in their study and found an increased odds of death among COVID-19 pneumonia patients who experienced invasive ventilation in the first 2 days of ICU admission as opposed to patients who did not experience invasive ventilation in the first 2 days of ICU admission. They used inverse probability of treatment weighting to reduce the impact of measured confounding on their results. We wish to highlight bias due to cohort construction in the study by Dupuis et al (1) that cannot be removed by statistical analysis and to explain how a “target trial” approach can help minimize such bias. In this cohort analysis, patients were compared according to whether or not they received “early” invasive ventilation (within 2 d of ICU admission). However, many of the patients classified as receiving early invasive ventilation were already invasively ventilated on ICU admission, which introduces both confounding and selection bias by comparing patients already ventilated to patients who were never ventilated (2). The bias has likely shifted the results toward finding early invasive ventilation harmful because patients who were already invasively ventilated at ICU admission were likely to be sicker than those who were not ventilated early. Inverse probability weighting may not even resolve the measured confounding for these patients because the adjusted covariates are measured after invasive ventilation has been already initiated. The inclusion of these patients also impedes clinical application of the results by a physician seeing a patient at ICU admission because the question of when to initiate invasive ventilation is irrelevant for patients who are already invasively ventilated. Similar bias due to cohort construction has appeared in other studies of timing of invasive ventilation (3–6). Identifying and minimizing bias due to cohort construction is more straightforward in randomized trials because the enrolment process makes it obvious that intervention and control populations must meet the same eligibility criteria. The “target trial” is a helpful concept intended to reduce bias in observational studies (7). It uses the inclusion and exclusion criteria from a hypothetical randomized trial to ensure that all patients included in an observational study were eligible for the intervention (2,8). To use the target trial concept, first you imagine the hypothetical randomized trial that would answer your research question. Then, you adapt the inclusion and exclusion criteria of that trial to your observational data. The target trial for the research question addressed by Dupuis et al (1) could be one that enrolls patients with COVID-19 pneumonia at admission to ICU and randomizes them to invasive ventilation within the first 2 days (“early”) or not (“nonearly”). This makes it clear that you must exclude patients already invasively ventilated on ICU admission because they would not have been eligible for the hypothetical randomized trial. They could not have been randomized to the “nonearly” invasive ventilation arm. In conclusion, we congratulate once more Dupuis et al (1) for their contribution to the problem of identifying which patients with hypoxemic respiratory failure truly benefit from invasive ventilation. We suggest future studies of invasive ventilation consider using the target trial concept in order to minimize bias and maximize the clinical applicability of results.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,479
Score d'incertitude au seuil0,174

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,141
Tête enseignante GPT0,372
Écart entre enseignants0,230 · 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 tête enseignante, pas un consensus.

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

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

En bref

Citations2
Publié2021
Routes d'admission1
Résumé présentoui

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