JAMA network open
-
Understanding the prevalence and symptoms of electronic cigarette (e-cigarette) dependence and its association with future e-cigarette use among youth may help to guide pediatric clinical services and health policy. ⋯ These findings suggest that e-cigarette dependence may be an expression of tobacco use disorder associated with future use persistence and escalation among youth. Electronic cigarette dependence may be a behavioral health consequence of adolescent vaping that warrants consideration in pediatric patient care and public health policy.
-
Randomized Controlled Trial
Effect of Physician Gender and Race on Simulated Patients' Ratings and Confidence in Their Physicians: A Randomized Trial.
Women and black physicians encounter workplace challenges because of their gender and race. It is unclear whether these individuals are assessed with lower patient satisfaction or confidence ratings compared with white male physicians. ⋯ No significant differences were observed for simulated patients' evaluations of female or black physicians, suggesting that bias in favor of white male physicians is negligible in survey-based measures of patient satisfaction.
-
The US opioid crisis was deemed a public health emergency in 2017. More than 130 individuals in the US die daily as a result of unintentional opioid overdose deaths. ⋯ Take-home naloxone as part of overdose education and naloxone distribution provided to patients in an opioid treatment program may be associated with a strategic targeted harm reduction response for reversing opioid overdose-related deaths. Policy makers may consider regulations to mandate overdose education and naloxone distribution in opioid treatment programs.
-
The ability to accurately predict in-hospital mortality for patients at the time of admission could improve clinical and operational decision-making and outcomes. Few of the machine learning models that have been developed to predict in-hospital death are both broadly applicable to all adult patients across a health system and readily implementable. Similarly, few have been implemented, and none have been evaluated prospectively and externally validated. ⋯ Prospective and multisite retrospective evaluations of a machine learning model demonstrated good discrimination of in-hospital mortality for adult patients at the time of admission. The data elements, methods, and patient selection make the model implementable at a system level.
-
Malignancy prediction models based on participant-related characteristics and imaging parameters from low-dose computed tomography (CT) may improve decision-making regarding nodule management and diagnosis in lung cancer screening. ⋯ This diagnostic study found that PanCan models showed excellent discrimination and calibration in prevalence screenings, confirming their ability to improve nodule management in screening settings, although calibration to nodules detected in follow-up scans should be improved. The models developed by the Mayo Clinic, Peking University People's Hospital, Department of Veterans Affairs, and UK Lung Cancer Screening Trial did not perform as well.