Comment on “Mortality and Cause of Death in Hearing Loss Participants: A Longitudinal Follow-Up Study Using a National Sample Cohort”
Notice bibliographique
Résumé
To the Editor: We recently reviewed the article published by Kim et al. (1) in the human communication epidemiology research group. The study aims to estimate the risk of mortality in subjects with severe and profound hearing loss according to the cause of death. The authors assume that changes in the auditory system lead to a greater risk of serious falls that lead to death (1). In studies in which the causal chain of diseases and illnesses are analyzed, depending on the basic epistemological and epidemiological framework, it is recommended that the links between the exposures and the outcome studied, as well as the variables related to exposure and outcome even if they are not the objective of the study, must be considered in the analysis models (2). Furthermore, considering that the planning of a study requires theoretical models defined a priori and based on the existing literature in addition to the definition of the statistical analyzes to be performed, including the covariables that will be inserted in the analysis models that will be performed reduces the probability that relevant variables are left out of the necessary adjustments for proper testing of the hypotheses on screen (3,4). In this case we refer mainly to confounding factors, since not considering these can, among others, lead researchers to find spurious associations (5). Literature research on the relationship between severe and profound hearing loss from the age of 40 and over and mortality rates opens a relevant range of possibilities already explored before (6–13) and not explored by the authors in the discussion or even in the fragilities of the study. Analyzing Table 1 of the manuscript, in which the authors present the characteristics of the studied population, there is a high proportion of subjects from the rural area in both groups of hearing impaired, severe and profound (59.7 and 65.1%, respectively) (1). The two studies previously carried out and cited by the authors (Genther et al., 2015) (14) and Karpa et al. (15) have lower hazard ratio and do not present information on the residence of their population (if rural or from the cities). We think that an important causal factor related to mortality and hearing loss in the researched population, exposure to pesticides and agrochemicals (16–18), was not considered by the authors in their analysis and in the discussion of the data. This is an important and current element of causation of health problems in death, as highlighted in the literature (19). Despite the fact that modern epidemiology demonstrates that health transposes the individual level of understanding of the health-disease process, it is also necessary to consider individual aspects such as the period of acquisition of hearing loss, whether acquired or congenital, labor aspects and exposure to noise and health-related aspects (5), such as self-perceived health (20), access to health services (21), and other associated psychological disorders (22,23), as these are related to both exposure and outcome under study and, although this information was not available for the study, it should be considered in the discussion of the findings. The discussion and conclusions are not fully supported by the presented methodology and results. Hearing is a complex system and the relationship between hearing loss and death is possibly not a direct cause. Thus, we highlight the importance of a critical and cautious reading of the data presented, especially in relation to its application in health policies and clinic.
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 | 0,018 | 0,096 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,004 | 0,005 |
| Science ouverte | 0,007 | 0,002 |
| Intégrité de la recherche | 0,034 | 0,035 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,007 |
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 ».