Concerns about the Validation of the Berlin Questionnaire and American Society of Anesthesiologist Checklist as Screening Tools for Obstructive Sleep Apnea in Surgical Patients
Notice bibliographique
Résumé
We appreciate the questions from Drs. Perez Valdivieso and Bes-Rastrollo regarding our article.1When we prepared the manuscript, we were considering publishing postoperative complications as a separate paper. In that way we could have presented data on postoperative complications more comprehensively.We agree with the doctors that it would be more accurate to state that the STOP questionnaire and American Society of Anesthesiologists (ASA) checklist identified the patients with higher incidence of postoperative respiratory complications. Since the odds ratio was calculated based on the incidence of total postoperative complications, it is not conflicting to the above statement that the 95% CI of the odds ratio presented in table 71for the STOP questionnaire and ASA checklist included the null value.To further evaluate the predictive value of different apnea-hypopnea index (AHI) cutoffs, high risk score on the STOP questionnaire, STOP-Bang scoring model, Berlin questionnaire, and ASA checklist, we did multivariate logistic regressions on the potential risk factors for total postoperative complications and respiratory complications. The analysis was carried out with the procedure LOGISTIC from the SAS statistical package (SAS Institute Inc., Cary, NC). The candidate factors were selected to enter the model through the stepwise method. The P value for an effect to enter and stay in the model was 0.1. In models, AHI > 5, AHI > 15, AHI > 30, STOP questionnaire high risk, STOP-Bang scoring model high risk, Berlin questionnaire high risk, or ASA checklist high risk was respectively combined with age (> 50), sex (male), and preexisting conditions (hypertension, gastroesophageal reflux disease, diabetes, and asthma) as candidate risk factors. The result suggested that AHI > 5, AHI > 15, or STOP-Bang high risk were, respectively, significant predictors for total postoperative complications and respiratory complications, with P < 0.05 and a 95% CI of an odds ratio excluding 1. The score of high risk on the STOP questionnaire or ASA checklist was a significant predictor for postoperative respiratory complications. The other predictive factor retained in final models was gastroesophageal reflux disease, with P = 0.0776 and odds ratio = 1.828 (95% CI: 0.931–3.592).Of the 211 patients, 44 had an AHI > 30. Compared with the patients with an AHI ≤ 30, this group of patients had a significantly higher percentage of men (75% vs . 46%, P = 0.0005), bigger neck circumference (42 ± 8 vs . 38.±4 cm, P = 0.0035) and higher prevalence of hypertension (61% vs . 39%, P = 0.0132). They did show a higher rate of total postoperative complication (25% vs . 22.2%), severe desaturation (18% vs . 9%), intensive care unit admission (11% vs . 5%), and prolonged oxygen therapy (18% vs . 10%). However, the differences were not statistically significant. There were several possible explanations why we did not see the significantly increased incidence of postoperative complication in this group of patients. The first is the awareness of obstructive sleep apnea by anesthesiologists and surgeons, because of the requirement of our institutional research ethics board to inform anesthesiologists and surgeons if patients had an AHI > 30. The patients with AHI > 30 from the hospital which automatically monitor a patients in the intensive care unit for first night if the patient had a AHI > 30 showed a lower rate of postoperative complication (21% vs . 28%) and increased prolonged oxygen therapy (21% vs . 16%), as compared with the patients with AHI > 30 who were from the other hospital, although the difference is not significant. The second possible reason is that the sample size was too small.As we stated in the original paper,2there was a self-selection of patients involved in the process of conducting the study. Because of the difficulty to arrange a sleep study before surgery, and the stress the patients faced before surgery, it was almost impossible to avoid self-selection for this kind of study.*University of Toronto, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada. frances.chung@uhn.on.ca
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 | 0,337 | 0,593 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,006 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».