Eric Chou M.D.

Chou, E., Y. L. Hsieh, J. Wolfshohl, F. Green and T. Bhakta (2020). “Onsite telemedicine strategy for coronavirus (COVID-19) screening to limit exposure in ED.” Emerg Med J May 3. pii. [Epub ahead of print].

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Coronavirus (severe acute respiratory syndrome coronavirus 2) outbreak is a public health emergency and a global pandemic. During the present coronavirus disease (COVID-19) crisis, telemedicine has been recommended to screen suspected patients to limit risk of exposure and maximise medical staff protection. We constructed the protective physical barrier with telemedicine technology to limit COVID-19 exposure in ED. Our hospital is an urban community hospital with annual ED volume of approximately 50 000 patients. We equipped our patient exam room with intercom and iPad for telecommunication. Based on our telemedicine screening protocol, physician can conduct a visual physical examination on stable patients via intercom or videoconference. Telemedicine was initially used to overcome the physical barrier between patients and physicians. However, our protocol is designed to create a protective physical barrier to protect healthcare workers and enhance efficiency in ED. The implementation can be a promising protocol in making ED care more cost-effective and efficient during the COVID-19 pandemic and beyond.

Wang, C. H., W. T. Chang, C. H. Huang, M. S. Tsai, T. C. Lu, E. Chou, Y. W. Wu and W. J. Chen (2020). “Associations between Central Obesity and Outcomes of Adult In-hospital Cardiac Arrest: A Retrospective Cohort Study.” Sci Rep 10(1): 4604.

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To investigate the association between central obesity and outcomes following in-hospital cardiac arrest (IHCA). A single-centred retrospective study was conducted. Adult patients that experienced IHCA during 2006-2015 were screened. Body mass index (BMI) was calculated at hospital admission. Central obesity-related anthropometric parameters were measured by analysing computed tomography images. A total of 648 patients were included, with mean BMI of 23.0 kg/m(2). The proportions of BMI-defined obesity in this cohort were underweight (13.1%), normal weight (41.4%), overweight (31.5%) and obesity (14.0%). The mean waist circumference was 85.9 cm with mean waist-to-height ratio (WHtR) of 0.53. The mean sagittal abdominal diameter was 21.2 cm with mean anterior and posterior abdominal subcutaneous adipose tissue (SAT) depths of 1.6 and 2.0 cm, respectively. Multivariate logistic regression analyses indicated BMI of 11.7-23.3 kg/m(2) (odds ratio [OR]: 2.53, 95% confidence interval [CI]: 1.10-5.85; p-value = 0.03), WHtR of 0.49-0.59 (OR: 3.45, 95% CI: 1.56-7.65; p-value = 0.002) and anterior abdominal SAT depth <1.9 cm (OR: 2.84, 95% CI: 1.05-7.74; p-value = 0.04) were positively associated with the favourable neurological outcome. Central obesity was associated with poor IHCA outcomes, after adjusting for the effects of BMI.

Chou, E. H., C. H. Wang, R. Monfort, A. Likourezos, J. Wolfshohl, T. C. Lu, Y. L. Hsieh, L. Haines, E. Dickman and J. Lin (2020). “Association of ultrasound-related interruption during cardiopulmonary resuscitation with adult cardiac arrest outcomes: A video-reviewed retrospective study.” Resuscitation 149: 74-80.

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OBJECTIVES: To determine the association of focused transthoracic echocardiography (ECHO) related interruption during cardiopulmonary resuscitation (CPR) with patient outcomes in the Emergency Department (ED). METHODS: This was a retrospective, single center, cohort study, conducted in an urban community teaching ED. Eligible study subjects were adult patients in the ED with sustained cardiac arrest. Exclusion criteria include traumatic cardiac arrest and age less than 18. All resuscitations were video recorded and were subsequently reviewed by 2 study investigators. The no-flow time from chest compression interruption was analyzed using video review and separated into ECHO-related and non-ECHO related. Our primary outcome was patient survival to hospital discharge and the secondary outcome was the rate of return of spontaneous circulation (ROSC). Multivariate logistic regression analyses were performed to examine the associations between independent variables and outcomes. RESULTS: From January 2016 to May 2017, a total of 210 patients were included for final analysis. The median total no-flow time observed on video was 99.5s (IQR: 54.0-160.0s). Among these, a median of 26.5s (IQR: 0.0-59.0s) was ECHO-related and a median of 60.5s (IQR: 34.0-101.9) was non-ECHO-related. The ECHO-related no-flow time between 77 and 122s (OR: 7.31, 95 % confidence interval [CI]: 1.59-33.59; p-value=0.01) and ECHO-related interruption<==2 times (OR: 8.22, 95% CI: 1.51-44.64; p-value=0.01) were positively associated with survival to hospital discharge. ECHO-related interruption<==2 times (OR: 5.55, 95% CI: 2.44-12.61; p-value<0.001) was also positively associated with ROSC. CONCLUSION: Short ECHO-related interruption during CPR was positively associated with ROSC and survival to hospital discharge. While ECHO can be a valuable diagnostic tool during CPR, the no-flow time associated with ECHO should be minimized.

Wang, C. H., W. T. Chang, K. I. Su, C. H. Huang, M. S. Tsai, E. Chou, T. C. Lu, W. J. Chen, C. C. Lee and S. C. Chen (2020). “Neuroprognostic accuracy of blood biomarkers for post-cardiac arrest patients: A systematic review and meta-analysis.” Resuscitation 148: 108-117.

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AIM: To summarise and compare the prognostic accuracy of the blood biomarkers of brain injury, including NSE and S-100B, for neurological outcomes in adult post-cardiac arrest patients. METHODS: We systematically searched PubMed and Embase databases from their inception to March 2019. We selected studies providing sufficient data of prognostic values of NSE or S-100B to predict neurological outcomes in adult post-cardiac arrest patients. We adopted QUADAS-2 to assess risk of bias and a Bayesian bivariate random-effects meta-analysis model to synthesise the prognostic data. The study protocol was registered with PROSPERO (CRD42018084933). RESULTS: We included 42 studies involving 4806 patients in the meta-analysis. The NSE was associated with a pooled sensitivity of 0.56 (95% credible interval [CrI], 0.47-0.65) and pooled specificity of 0.99 (95% CrI, 0.98-1.00). The S-100B was associated with a pooled sensitivity of 0.63 (95% CrI, 0.46-0.78) and pooled specificity of 0.97 (95% CrI, 0.92-1.00). The heterogeneity for NSE (I(2), 22.4%) and S-100B (I(2), 16.1%) was low and publication bias was not significant. In subgroup analyses, both biomarkers were associated with high specificity across all subgroups with regard to different populations (i.e. whether patients were out-of-hospital cardiac arrest or whether patients received targeted temperature management), different timings of measurement, and different timings of outcome assessment. CONCLUSIONS: The prognostic performance was comparable between NSE and S-100B. Both biomarkers may be integrated into a multimodal neuroprognostication algorithm for post-cardiac arrest patients and institution-specific cut-off points for both biomarkers should be established.

Wang, C. H., W. T. Chang, K. I. Su, C. H. Huang, M. S. Tsai, E. Chou, T. C. Lu, W. J. Chen, C. C. Lee and S. C. Chen (2020). “Neuroprognostic accuracy of blood biomarkers for post-cardiac arrest patients: A systematic review and meta-analysis.” Resuscitation 148: 108-117.

Full text of this article.

AIM: To summarise and compare the prognostic accuracy of the blood biomarkers of brain injury, including NSE and S-100B, for neurological outcomes in adult post-cardiac arrest patients. METHODS: We systematically searched PubMed and Embase databases from their inception to March 2019. We selected studies providing sufficient data of prognostic values of NSE or S-100B to predict neurological outcomes in adult post-cardiac arrest patients. We adopted QUADAS-2 to assess risk of bias and a Bayesian bivariate random-effects meta-analysis model to synthesise the prognostic data. The study protocol was registered with PROSPERO (CRD42018084933). RESULTS: We included 42 studies involving 4806 patients in the meta-analysis. The NSE was associated with a pooled sensitivity of 0.56 (95% credible interval [CrI], 0.47-0.65) and pooled specificity of 0.99 (95% CrI, 0.98-1.00). The S-100B was associated with a pooled sensitivity of 0.63 (95% CrI, 0.46-0.78) and pooled specificity of 0.97 (95% CrI, 0.92-1.00). The heterogeneity for NSE (I(2), 22.4%) and S-100B (I(2), 16.1%) was low and publication bias was not significant. In subgroup analyses, both biomarkers were associated with high specificity across all subgroups with regard to different populations (i.e. whether patients were out-of-hospital cardiac arrest or whether patients received targeted temperature management), different timings of measurement, and different timings of outcome assessment. CONCLUSIONS: The prognostic performance was comparable between NSE and S-100B. Both biomarkers may be integrated into a multimodal neuroprognostication algorithm for post-cardiac arrest patients and institution-specific cut-off points for both biomarkers should be established.