An algorithm to assist novices with electrocardiogram interpretation: Validation with the Delphi Method

Author(s):  
Susil Pallikadavath ◽  
Jamie Watts ◽  
Alastair Sandilands ◽  
Simon Gay
2020 ◽  
Author(s):  
Mohammad Alakchar ◽  
Abdisamad M. Ibrahim ◽  
Mohsin Salih ◽  
Mukul Bhattarai ◽  
Nitin Tandan ◽  
...  

BACKGROUND Interpretation of electrocardiograms (EKG) is an essential tool for every physician. Despite this, the diagnosis of life-threatening pathology on EKG remains suboptimal in trainees. The purpose of this study is to study resident attitudes and behaviours towards EKGs, and describe an innovative way to teach EKGs. OBJECTIVE Study attitudes and behaviours towards EKGs. Describe an innovative way to teach EKGs. METHODS Design: An observational cross-sectional study through an anonymous online survey of resident attitudes and comfort with EKG interpretation. This was followed by creation of a WhatsApp group for discussion and interpretation of EKGs with peers. At the end of the day, the official EKG interpretation was posted. Setting: Internal medicine residency at Southern Illinois University. Participants: Internal medicine residents Interventions: Creation of WhatsApp group to aid with EKG interpretation Measurements: A 17 item questionnaire, followed by detection of degree of participation in a WhatsApp group. RESULTS Forty-one out of 63 residents (65%) completed the survey. 85% of respondents thought that an interactive way to teach EKGs is the best method of teaching, and 73% did not feel confident interpreting EKGs. 30% often rely on automated EKG interpretation. Further analysis indicated that PGY-1 residents reported ordering fewer EKGs (correlation coefficient -0.399, p = 0.012) and were uncomfortable diagnosing QT prolongation on an EKG (correlation coefficient -0.310, p = 0.049). Residents in the third or greater year of training ordered more EKGs (correlation coefficient 0.379, p = 0.015), less frequently relied on the computer for EKG diagnosis (correlation coefficient 0.399, p = 0.010), and were comfortable diagnosing an acute myocardial infarction and atrial arrhythmias. CONCLUSIONS In conclusion, most IM trainees do not feel comfortable interpreting EKG, however, this does improve with PGY year. WhatsApp is a possible platform for teaching EKGs.


Author(s):  
Shifan Han ◽  
Xiaoyue Jia ◽  
Ruifang Zhu ◽  
Yan Cao ◽  
Zhuya Xu ◽  
...  

2020 ◽  
pp. 2516600X2097412
Author(s):  
A. K. M. Hedaitul Islam ◽  
Md. Rayhan Sarker ◽  
Md. Israil Hossain ◽  
Kauser Ali ◽  
K. M. Asadun Noor

Small- and medium-sized enterprises (SMEs) create more employment opportunities and thus, contribute to the national economy of a country. Footwear SMEs have been identified as an emerging economy in Bangladesh, which is facing several challenges. Very few studies focused on the challenges of SMEs’ business growth. However, until now, no literature particularly focused on the challenges of footwear SMEs and discussed how to tackle these challenges. To fill this research gap, we use the Fuzzy Delphi Method and fuzzy analytical hierarchy process, to find out the degree of importance of critical challenges of footwear SMEs. In our study, 16 critical challenges are identified among which lingering in cash flow (F3), fierce market competition (E1), access to finance (F2), unfavorable bank loan policy (F1), and poor supply chain management (E2) have been ascertained as the top five critical challenges, respectively. This study contributes to the existing literature of SMEs by identifying five new challenges from the context of the footwear industry. Furthermore, we suggest some possible measures to overcome the identified challenges. This study can guide the government, practitioners, and SME policymakers to address these challenges for the growth of any SME sector.


2021 ◽  
pp. 000486742110257
Author(s):  
Olivier Bonnot ◽  
Jose Luis Insua ◽  
Mark Walterfang ◽  
Juan Vincente Torres ◽  
Stefan Armin Kolb

Aim: The aim of this study was to develop a suspicion index that aids diagnosis of secondary schizophrenia spectrum disorders in regular clinical practice. Method: We used the Delphi method to rate and refine questionnaire items in consecutive rounds. Differences in mean expert responses for schizophrenia spectrum disorders and secondary schizophrenia spectrum disorders populations allowed to define low/middle/high predictive items, which received different weights. Algorithm performance was tested in 198 disease profiles by means of sensitivity and specificity. Results: Twelve experts completed the Delphi process, and consensus was reached in 19/24 (79.2%) items for schizophrenia spectrum disorders and 17/24 (70.8%) for secondary schizophrenia spectrum disorders. We assigned rounded values to each item category according to their predictive potential. A differential distribution of scores was observed between schizophrenia spectrum disorders and secondary schizophrenia spectrum disorders when applying the suspicion index for validation to 198 disease profiles. Sensitivity and specificity analyses allowed to set a >8/10/16 risk prediction score as a threshold to consider medium/high/very high suspicion of secondary schizophrenia spectrum disorders. Conclusion: Our final outcome was the Secondary Schizophrenia Suspicion Index, the first paper-based and reliable algorithm to discriminate secondary schizophrenia spectrum disorders from schizophrenia spectrum disorders with the potential to help improve the detection of secondary schizophrenia spectrum disorder cases in clinical practice.


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