Husseinmccray2344

There is no large contemporary data from India to see the prevalence of burnout in HCWs in covid era. Burnout and mental stress is associated with electrocardiographic changes detectable by artificial intelligence (AI).

The present study aims to estimate the prevalence of burnout in HCWs in COVID-19 era using Mini Z-scale and to develop predictive AI model to detect burnout in HCWs in COVID-19 era.

This is an observational and cross-sectional study to evaluate the presence of burnout in HCWs in academic tertiary care centres of North India in the COVID-19 era. At least 900 participants will be enrolled in this study from four leading premier government-funded/public-private centres of North India. Each study centre will be asked to recruit HCWs by approaching them through various listed ways for participation in the study. Interested participants after initial screening and meeting the eligibility criteria, will be asked to fill the questionnaire (having demographic and work related with Mini Z questionnaire) to assess burnout. The healthcare workers will include physicians at all levels of training, nursing staff and paramedical staff who are involved directly or indirectly in COVID-19 care. The analysis of the raw electrocardiogram (ECG) data and development of algorithm using convolutional neural networks (CNN) will be done by experts.

In Summary, we propose that ECG data generated from the people with burnout can be utilized to develop AI-enabled model to predict the presence of stress and burnout in HCWs in COVID-19 era.

In Summary, we propose that ECG data generated from the people with burnout can be utilized to develop AI-enabled model to predict the presence of stress and burnout in HCWs in COVID-19 era.

Heart failure complicating acute myocardial infarction marks an ominous prognosis. Killip and Kimball's classification of heart failure remains a useful tool in these patients. Lung ultrasound can detect pulmonary congestion but its usefulness in this scenario is unknown.

To investigate the diagnostic accuracy of lung ultrasound to predict heart failure in patients with acute myocardial infarction.

Patients admitted with acute myocardial infarction and without heart failure were evaluated with a lung ultrasound. MEK inhibitor The presence of B-lines was recorded and counted. The presence of new heart failure (Killip Class B, C, or D) during hospitalization was evaluated by a cardiologist blinded to the results of lung ultrasound. A ROC curve analysis was done to evaluate the diagnostic accuracy of B-lines to predict heart failure.

200 patients were included. Three patients were diagnosed with cardiogenic shock, 5 with acute pulmonary edema, and 17 with mild heart failure. Patients who develop heart failure had a median of 14B-lines, however, patients who remained in Killip class A had a median of 2 (p=0,0001). The area under the ROC curve of the sum of B-lines to predict any form of heart failure was 0,91 (CI95% 86-97). The best cut-off value was 5B-lines, with a sensitivity of 88% (IC95% 68,8-97,5) and specificity of 81% (IC95% 73,9-86,2).

Lung ultrasound done at admission can help to predict heart failure In patients with acute myocardial infarction.

Lung ultrasound done at admission can help to predict heart failure In patients with acute myocardial infarction.

Hearing loss affects access to spoken language, which can affect cognition and development, and can negatively affect social wellbeing. We present updated estimates from the Global Burden of Disease (GBD) study on the prevalence of hearing loss in 2019, as well as the condition's associated disability.

We did systematic reviews of population-representative surveys on hearing loss prevalence from 1990 to 2019. We fitted nested meta-regression models for severity-specific prevalence, accounting for hearing aid coverage, cause, and the presence of tinnitus. We also forecasted the prevalence of hearing loss until 2050.

An estimated 1·57 billion (95% uncertainty interval 1·51-1·64) people globally had hearing loss in 2019, accounting for one in five people (20·3% [19·5-21·1]). Of these, 403·3 million (357·3-449·5) people had hearing loss that was moderate or higher in severity after adjusting for hearing aid use, and 430·4 million (381·7-479·6) without adjustment. The largest number of people with moderate-the burden of unaddressed hearing loss in these settings.

Bill & Melinda Gates Foundation and WHO.

Bill & Melinda Gates Foundation and WHO.

Near-infrared spectroscopy (NIRS) and intravascular ultrasound are promising imaging modalities to identify non-obstructive plaques likely to cause coronary-related events. We aimed to assess whether combined NIRS and intravascular ultrasound can identify high-risk plaques and patients that are at risk for future major adverse cardiac events (MACEs).

PROSPECT II is an investigator-sponsored, multicentre, prospective natural history study done at 14 university hospitals and two community hospitals in Denmark, Norway, and Sweden. We recruited patients of any age with recent (within past 4 weeks) myocardial infarction. After treatment of all flow-limiting coronary lesions, three-vessel imaging was done with a combined NIRS and intravascular ultrasound catheter. Untreated lesions (also known as non-culprit lesions) were identified by intravascular ultrasound and their lipid content was assessed by NIRS. The primary outcome was the covariate-adjusted rate of MACEs (the composite of cardiac death, myocardial inMACEs (7·83, 4·12-14·89). Large plaque burden (787 [22%] of 3629 lesions, present in 530 [59%] of 898 patients) was also an independent predictor of non-culprit lesion-related MACEs. Lesions with both large plaque burden by intravascular ultrasound and large lipid-rich cores by NIRS had a 4-year non-culprit lesion-related MACE rate of 7·0% (95% CI 4·0-10·0). Patients in whom one or more such lesions were identified had a 4-year non-culprit lesion-related MACE rate of 13·2% (95% CI 9·4-17·6).

Combined NIRS and intravascular ultrasound detects angiographically non-obstructive lesions with a high lipid content and large plaque burden that are at increased risk for future adverse cardiac outcomes.

Abbott Vascular, Infraredx, and The Medicines Company.

Abbott Vascular, Infraredx, and The Medicines Company.