CASE REPORT | doi:10.20944/preprints202208.0453.v1
Subject: Medicine & Pharmacology, Anesthesiology Keywords: electrocardiogram; pulmonary hypertension; right axis deviation; dextrocardia; technical errors
Online: 26 August 2022 (09:27:06 CEST)
A 57-year-old male with a history of hyperlipidemia and mild pulmonary hypertension presented for a left inguinal hernia repair. Preoperative electrocardiogram showed severe right axis deviation at 177 degrees and abnormal repolarization. Right ventricular hypertrophy secondary to pulmonary hypertension was the primary differential but was quickly ruled out due to the patient being asymptomatic and having great exercise tolerance. Dextrocardia was also ruled out due to normal progression on the precordial leads. The simultaneous severe right axis deviations of P, R, and T waves raised suspicion for erroneous lead placement. The repeat electrocardiogram confirmed the diagnosis.
ARTICLE | doi:10.20944/preprints202209.0223.v1
Subject: Life Sciences, Other Keywords: Covid; Covid testing; sample pooling; resources; time; binary system; probability; positivity rate
Online: 15 September 2022 (08:14:36 CEST)
In Los Angeles, at one point, the Covid-19 testing positivity rate was 6.25%, or one in sixteen. This translates to, on average, one in sixteen specimens testing positive and the vast majority testing negative. Usually, we run sixteen tests on sixteen specimens to identify the positive one(s). This process can be time consuming and expensive. Since a group of negative specimens pooled together for testing will produce a negative result, one single test could potentially eliminate many specimens. Only when the pooled specimen tests positive do we need further testing to identify the positive one(s). Based on this concept, we designed a strategy that will identify the positive specimen(s) efficiently. Assuming one in sixteen specimens is positive, we find that only four tests are needed. Furthermore, we can run them simultaneously, saving both resources and time. Although, in the real world, we cannot make the assumption of only one positive specimen, the same strategy works with slight modification and proves to be much more efficient than the conventional testing. Our strategy returns an answer 48% of the time in four tests and one time cycle. Overall, the average number of tests is seven or eight depending on the follow-up testing, and the average time cycle is about one and a half.