The incidence of unplanned reoperation after surgery during the same hospitalization is considered one of most important evaluation indicators for health care quality. The purpose of this study was to determine the incidence and risk factors related to unplanned reoperation after an endoscopic endonasal approach (EEA). All patients who underwent elective endoscopic endonasal surgery from January 2016 to December 2021 in the Department of Neurosurgery, Tangdu Hospital, Air Force Military Medical University, were included. We identified the patients who underwent an unplanned reoperation and those who did not and divided them into two groups. The demographic data and risk factors were compared between the groups by univariate and multivariate logistic regression analyses. Of the 1783 patients undergoing EEA for various lesions of the skull base, the incidence of unplanned reoperation was 2.3%. The most common unplanned reoperations were repair of cerebrospinal fluid (CSF) leakage (39%), sellar hematoma evacuation (34.1%), hemostasis of epistaxis (14.6%) and external ventricular drainage for obstructive hydrocephalus (9.8%). The maximum diameter of tumor ≥ 3 cm (OR 2.654, CI 1.236-5.698; p = 0.012), meningioma (OR 4.198, CI 1.169-15.072; p = 0.028), craniopharyngioma (OR 5.020, CI 2.020-12.476; p = 0.001) and other sellar lesions (OR 4.336, CI 1.390-13.527; p = 0.012) and an operation time ≥ 240 min (OR 2.299, CI 1.170-4.518; p = 0.016) were the independent risk factors for unplanned reoperations in multivariate regression analysis. Of the 41 patients undergoing unplanned reoperation, 16 patients died, twenty-one patients had panhypopituitarism, 13 patients had transient and 6 had permanent diabetes insipidus, and 11 patients presented with intracranial infection and 6 of these patients were cured. By reviewing our department's data, we stated the incidence and risk factors for unplanned reoperation. It is important for the hospital administration and neurosurgeons to place more emphasis on these indicators. Furthermore, we suggest some effective quality improvement initiatives to reduce the incidence of unplanned reoperation.
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http://dx.doi.org/10.1007/s10143-023-02134-w | DOI Listing |
J Clin Neurosci
December 2024
Section of Neurosurgery, Department of Surgery, Aga Khan University, Karachi, Pakistan. Electronic address:
Background: Blood transfusions (BT) are often needed in neurosurgical procedures, especially craniotomies for tumor resections, due to risks of anemia, ischemic brain injury, and hemorrhage. However, BT may increase the risk of perioperative complications. This study aimed to determine the incidence, associated factors, and outcomes of BT in patients undergoing craniotomy for intracranial tumor resection.
View Article and Find Full Text PDFBMJ Open
December 2024
Department of Anesthesiology, Shanghai Jiao Tong University School of Medicine Affiliated Ninth People's Hospital, Shanghai, China
Objectives: This study aimed to evaluate the predictive abilities of the 5-item modified Frailty Index (5-mFI), Prognostic Nutrition Index (PNI), and their combination in older adult patients undergoing oral cancer resection and free flap reconstruction.
Design: Retrospective cohort study.
Setting: Secondary care involving multiple centres treating older adult patients for oral cancer.
J Craniofac Surg
October 2024
Department of Plastic and Reconstructive Surgery, Johns Hopkins Hospital.
Purpose: The mandible is the second most fractured facial bone. The timing of open reduction internal fixation (ORIF) has been a subject of debate for decades. The authors sought to investigate the association between the timing of ORIF and the incidence of postoperative complications.
View Article and Find Full Text PDFJ Pers Med
December 2024
Division of Neurotology and Skull Base Surgery, Department of Otolaryngology-Head and Neck Surgery, University of California, Irvine, CA 92697, USA.
This study aimed to develop a machine learning (ML) algorithm that can predict unplanned reoperations and surgical/medical complications after vestibular schwannoma (VS) surgery. All pre- and peri-operative variables available in the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database (n = 110), except those directly related to our outcome variables, were used as input variables. A deep neural network model consisting of seven layers was developed using the Keras open-source library, with a 70:30 breakdown for training and testing.
View Article and Find Full Text PDFFront Public Health
December 2024
Department of Anesthesiology, Chengdu Fifth People's Hospital (The Second Clinical Medical College, Affiliated Fifth People's Hospital of Chengdu University of Traditional Chinese Medicine), Chengdu, China.
Background: Postoperative pneumonia, a prevalent form of hospital-acquired pneumonia, poses significant risks to patients' prognosis and even their lives. This study aimed to develop and validate a predictive model for postoperative pneumonia in surgical patients using nine machine learning methods.
Objective: Our study aims to develop and validate a predictive model for POP in surgical patients using nine machine learning algorithms.
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