Objective: To investigate further the hypothesis that ethnic groups would have different levels of knowledge and perceptions of congestive heart failure (CHF) and treatments for this condition, a cross sectional survey was conducted of patients who were attending the heart failure clinics in two teaching hospitals of Birmingham, UK, that serve a multiethnic population. Methods: 103 patients with CHF (66 men, 37 women) were surveyed by standard questionnaire: 42 were white, 34 Indo-Asian, 22 Afro-Caribbean, and 5 Oriental. Results: When asked about their beliefs about control of one's health, 22 (64.7%) of Indo-Asians felt that God/fate controlled their health. The majority of white patients tended to believe that the greatest factor influencing their health was the doctor (15 (35.7%)). Of the total study cohort, only 68 (66%) of patients were aware of their primary diagnosis of heart failure; the majority of Indo-Asians (21 (61.8%)) were not aware of their diagnosis. Half of Indo-Asians (17 (50%)) felt that heart failure was not severe, in contrast to 40.9% (n = 9) of Afro-Caribbeans and only 19.1% (n = 8) of white patients. Of the study cohort, 38 (36.9%) were taking their drugs because their doctor told them to, a response most common among the Indo-Asians. The majority of Indo-Asians (22 (64.7%)) and Afro-Caribbeans (14 (63.6%)) stated that they did not have, or did not know whether they had enough, information about their drug. The corresponding figure for white patients was 21.4% (n = 9). When asked whether they took their medication regularly as prescribed, 7 (31.8%) of Afro-Caribbeans reported that they did not take their drugs regularly. Conclusions: Our study has highlighted deficiencies in the knowledge of CHF among patients from ethnic minority groups, as well as deficiencies in the information being given to these patients. There is a clear need to invest more in patient education for CHF, with special emphasis on certain high risk subgroups.

This study demonstrated variable adherence to pediatric cardiac arrest guidelines across a spectrum of EDs. Overall adherence was not associated with ED pediatric volume. Medium-high-volume EDs demonstrated the highest levels of adherence for BLS and PEA. Lower-volume EDs were noted to have lower adherence to BLS guidelines. Improved adherence was not directly associated with higher PRS score provider experience, simulation teamwork performance, or more providers with PALS training. This study demonstrates that current approaches optimizing the care of children in cardiac arrest in the ED (provider training, teamwork training, environmental preparation) are insufficient.

Interprofessional CED providers perceive that caring for pediatric patients is challenging due to case infrequency, the emotional toll of caring for sick children, and pediatric quality and safety deficits in their systems. These areas of focus can be used to generate specific strategies for improving CED pediatric readiness.

Proactive detection of hemodynamic shock can prevent organ failure and save lives. Thermal imaging is a non-invasive, non-contact modality to capture body surface temperature with the potential to reveal underlying perfusion disturbance in shock. In this study, we automate early detection and prediction of shock using machine learning upon thermal images obtained in a pediatric intensive care unit of a tertiary care hospital. 539 images were recorded out of which 253 had concomitant measurement of continuous intra-arterial blood pressure, the gold standard for shock monitoring. Histogram of oriented gradient features were used for machine learning based region-of-interest segmentation that achieved 96% agreement with a human expert. The segmented center-to-periphery difference along with pulse rate was used in longitudinal prediction of shock at 0, 3, 6 and 12 hours using a generalized linear mixed-effects model. The model achieved a mean area under the receiver operating characteristic curve of 75% at 0 hours (classification), 77% at 3 hours (prediction) and 69% at 12 hours (prediction) respectively. Since hemodynamic shock associated with critical illness and infectious epidemics such as Dengue is often fatal, our model demonstrates an affordable, non-invasive, non-contact and tele-diagnostic decision support system for its reliable detection and prediction.