Healthcare disparities in pituitary surgery: a systematic review
Notice bibliographique
Résumé
OBJECTIVE: Pituitary surgery is a frequent neurosurgical procedure for the management of pituitary adenomas, but little research has been done on the impact of healthcare disparities on surgical results. Healthcare inequity/disparity in terms of race and socioeconomic status (SES), in addition to age and gender, was evaluated in this study to see if they affect the results of pituitary surgery. METHODS: A systematic literature search was carried out utilizing the MEDLINE (PubMed), Web of Science, Scopus, and Embase electronic databases from conception to 2023. The Newcastle-Ottawa Scale was used for quality assessment of the included studies. RESULTS: Twenty-one studies yielded a total of 381,643 patients, and removal of the studies with temporal overlap resulted in 134,832 patients with a mean ± SD age of 51.52 ± 0.41 years. Based on the available data, 46.63% of patients were male. Black patients were more likely to be recommended against surgery, while Asian or Pacific Islander patients were more likely to be recommended for surgery. Postoperative course and outcome showed mixed results, with some studies reporting higher rates of transient diabetes insipidus and stroke in racial minority populations. Private hospitals admitted more White patients, and certain racial groups had reduced access to high-volume centers. SES disparities were assessed in terms of insurance and income. Patients with government insurance or without insurance were more likely to be recommended active surveillance instead of definitive treatment. Furthermore, high SES was associated with a higher likelihood of receiving surgical treatment, better treatment outcomes, and better access to high-volume centers. In terms of age and gender disparity, older patients and females were less likely to be recommended for surgical treatment. Age and gender did not consistently impact postoperative course and treatment outcomes, with varying results across studies. No significant age and gender disparities were observed in hospital admissions and charges. CONCLUSIONS: This study revealed the presence of disparities in pituitary adenoma surgery based on race, SES, age, and gender. These disparities highlight the need for further research and interventions to ensure equitable access to appropriate surgical treatment and improved outcomes for all patients with pituitary adenomas.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,008 | 0,002 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,001 |
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; 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 ».