RESPONSE TO DR KARI POIKOLAINEN: THE PERSISTENT, ALTERNATIVE ARGUMENT TO APPARENT CARDIOPROTECTIVE EFFECTS OF ALCOHOL
Notice bibliographique
Résumé
Addiction recently published a commentary by Poikolainen [1] on a cohort study by Harriss et al. [2] which supported the hypothesis that errors in the definition of ‘abstainers’ were responsible for apparent cardioprotective effects of alcohol, especially for male drinkers. Shaper et al. [3] first proposed that many prospective studies classified erroneously both former and occasional drinkers as ‘abstainers’. However, Poikolainen [1] also criticized our meta-analyses of the literature [4, 5] which supported the Shaper et al. hypothesis and suggested the possibility of gender differences in susceptibility to protection. Poikolainen [1] concluded: As usual in epidemiological research, scientists try to eliminate bias, confounding . . . Nevertheless, the protective effect of coronary heart disease incidence and all-cause mortality has remained. All but one meta-analysis agree on this point. The deviant one (1) [referenced here as [4]] found no protection, but was shown to have errors in the selection of studies and interpretation of findings (2–4) [referenced here as [6-8]]. We suggest that this conclusion suffers from at least two problems: It relied selectively on three of eight invited commentaries on our study [4] (see http://www.informaworld.com/smpp/title~content=g773385479~db=all) and overlooked our response to commentaries. The neglected five commentators on our research—Drs Andreasson, Holder, Rodgers et al., Romelsjö and Shaper—all endorsed efforts to understand more clearly potential misclassification error and confounding in these studies. Poikolainen [1] cites two objections to our study. First, it is alleged that there were mistakes in our selection of studies deemed to contain error—a position advanced by Klatsky [6] and Mukamal [7]. In order to identify probable misclassification error, we paid close attention to the precise wording of alcohol use questions found in all the studies examined in order to ensure that the functional meaning of specific drinking categories was very clear [4, 9]. We posit that the more ‘liberal’ definitions of drinking status applied by these studies (e.g. wording such as: ‘do you rarely/never drink?’ or ‘never or almost never drink’) contributed in large part to the possible mistaken conclusion that abstinence increases the risk of coronary heart disease. This domain of epidemiological research may be characterized as lacking in systematic attempts to address problems of confounding and bias (e.g. [10]), an important fact which Dr Poikolainen overlooks. Critical work which gives careful consideration to such issues warrants equally thoughtful consideration. In our view, it is entirely plausible that one well-designed study (e.g. [2]) may provide more insight into the true relationship between exposure and outcome than almost 30 years of systematically flawed and confounded studies.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».