Multivariate Analysis of Factors Associated with and Predicting Post-Thyroidectomy Hypoglycaemia: Experience of the Surgery a Department at Ibn Sina Hospital
Condé Abraham Y., Ouhammou Y., M. Djodbé, O. Mkira, Hamzaoui J., Asatach Y., Pr Ifrine L., Pr Belkouchi A., Pr el Malki H. O.
Asian Journal of Research in Surgery · pp. 354–360 · Published 9 Dec 2023
Abstract
Background: Post-thyroidectomy hypocalcaemia continues to be a regular complication. Therefore, it is necessary to identify predictive factors to improve preoperative risk assessment and reduce complications. Materials and Methods: This retrospective study was performed at the Surgical Department A of Ibn Sina Hospital from 2007 to 2022 and analyzed 539 thyroidectomy cases. The objective is to ascertain the factors that contribute to postoperative hypocalcaemia, whether it is transient or permanent. Parameters consist of age, gender, past medical history, preoperative symptoms, thyroid hormone levels, diagnosis, surgical procedure type, detection of parathyroid gland, incidentaloma, lymph node dissection, and operator proficiency. Results: The findings reveal that postoperative hypocalcaemia occurred in 31.91% of patients, 6.39% of whom necessitated extended calcium supplementation. Significant factors associated with the condition included being female, having preoperative hyperthyroidism, undergoing total thyroidectomy, experiencing accidental parathyroidectomy, and having a multinodular goiter. Presence, or lack thereof, of parathyroid glands, parathyroid incidentaloma, surgical expertise, and incidents of hematoma or hemorrhaged requiring revision surgery were also significant factors. Conclusion: There was no statistically significant impact from surgical history, hypertension, or diabetes. Understanding these predictive factors is essential to improve surgical strategies, optimize patient care, and potentially reduce hospitalization costs associated with post-thyroidectomy hypocalcemia. Further research should investigate the interaction between these factors and refine risk prediction models to enhance patient outcomes.
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