Factors affecting hormonal outcomes in patients undergoing surgery for non-functioning pituitary neuroendocrine tumors: a prospective observational study.

Surgical resection of non-functioning pituitary neuroendocrine tumors (NF-PitNET) is associated with new onset hormonal axis (HA) dysfunction, and factors predicting HA dysfunction are controversial, especially in large and giant NF-PitNET. Thus, we evaluated the postoperative hormonal function and assessed factors affecting HA dysfunction in patients with NF-PitNET. This prospective observational study involved 50 patients who underwent endoscopic surgical resection of NF-PitNET in the Department of Neurosurgery (April 2023-March 2024).

Use of Artificial Intelligence for the Development of Predictive Model to Help in Decision-Making for Patients with Degenerative Lumbar Spine Disease.

 The aim of the study was to develop a prognostic model using artificial intelligence for patients undergoing lumbar spine surgery for degenerative spine disease for change in pain, functional status, and patient satisfaction based on preoperative variables included in following categories-sociodemographic, clinical, and radiological.  A prospective cohort of 180 patients with lumbar degenerative spine disease was included and divided into three classes of management-conservative, decompressive surgery, and decompression with fixation. Preoperative variables, change in outcome measures (visual analog scale-VAS, Modified Oswestry Disability Index-MODI, and Neurogenic Claudication Outcome Score-NCOS), and type of management were assessed using Machine Learning models.

Predictors of Outcome After Traumatic Brain Injuries: Experience of a Tertiary Health Care Institution in Northwest India.

Background And Objective: Traumatic brain injury (TBI) is a major health issue in developing nations such as India along with underreporting of TBI data because of a lack of major studies targeting the population with TBI. Various lacunae from field to tertiary centers are responsible for this significant burden of TBIs. We studied the epidemiologic profile of 1150 patients with TBI including the predictors of the outcome of TBIs in a tertiary health care institution in North India to identify the modifiable factors that could be used to improve the outcome and reduce the TBI burden.