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Objective: Smartphones and wearable devices can be effective tools to objectively assess patient mobility and well-being before and after spine surgery. In this retrospective observational study, the authors investigated the relationship between these longitudinal perioperative patient activity data and socioeconomic and demographic correlates, assessing whether smartphone-captured metrics may allow neurosurgeons to distinguish intergroup patterns.

Methods: A multi-institutional retrospective study of patients who underwent spinal decompression with and without fusion between 2017 and 2021 was conducted.

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Purpose: The aim of this study was to propose a lateral oscillating device for the prevention of pressure ulcers by understanding the mechanisms of tissue protection in healthy individuals during prolonged decubitus. We also sought to determine the optimal time interval for oscillation, considering peak pressure peaks and tolerable pressure limits as a function of individual characteristics such as age, weight, height, gender, and BMI.

Methods: A quasi-experimental, descriptive and analytical observational study was conducted between January 2022 and June 2023 with a sample of 25 healthy volunteers.

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Estimating avoidable burden of stillbirth attributable to greenness improvement in Iran.

Ecotoxicol Environ Saf

December 2024

Department of Epidemiology and Health Statistics, School of Public Health, Wenzhou Medical University, Wenzhou 325035, China. Electronic address:

Introduction: Expanding evidence suggests beneficial impacts of greenspace on human health, yet the relationships between greenness and stillbirth remain unknown. This study aimed to quantify the risk and burden of stillbirth associated with maternal greenness exposure during pregnancy.

Methods: A total of 3,982,304 eligible birth records across 31 provinces in Iran from 2013 to 2018 were included in this study.

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Purpose: This study analyzed inter-institute conformity and dose gradient variability of CyberKnife (CK) brain SRS/SRT plans. The feasibility of multi-center predictive models was investigated, aiming at guided/automated planning optimization.

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