SARS-2 COVID-19-induced immunity response, a new prognostic marker for the pregnant population correlates inversely with neonatal Apgar score

Background: The COVID-19 infection has impacted pregnancy outcomes; however, few studies have assessed the association between haematological parameters and virus-related pregnancy and neonatal outcomes. We hypothesised differences in routine haematology indices in pregnant and non-pregnant COVID-19 patients as well as COVID-19-negative pregnant subjects and observed neonatal outcomes in all pregnant populations. Further, we tested if pattern identification in the COVID-19 pregnant population would facilitate prediction of neonates with a poor Apgar score. Methods: We tested our hypothesis in 327 patients (111 COVID-19-positive pregnant females, 169 COVID-19-negative pregnant females and 47 COVID-19-positive non-pregnant females) in whom standard routine laboratory indices were collected on admission. Results: Pregnant COVID-19-positive patients exhibited higher WBC, neutrophil, monocyte counts as well as neutrophil/lymphocyte and neutrophil/eosinophil ratio compared to non-pregnant COVID-19-positive patients (p = 0.00001, p = 0.0023, p = 0.00002, p = 0.0402, p = 0.0161, p = 0.0352, respectively). Preterm delivery was more prevalent in COVID-19-positive pregnant patients accompanied with a significantly lower birth weight (2894.37 (± 67.50) g compared with 3194.16 (± 50.61) g, p = 0.02) in COVID-19-negative pregnant patients. The COVID-19-Induced Immunity Response (CIIR) was defined as (WBC × neutrophil) / eosinophil; Apgar scores were significantly and inversely correlated with the CIIR index (r =—0.162). Interpretation: Pregnancy appears to give rise to an increased immune response to COVID-19 which appears to protect the mother, however may give rise to complications during labour as well as neonatal concerns. CIIR is a simple metric that predicts neonatal distress to aid clinicians in determining the prognosis of COVID-19 and help provide early intensive intervention to reduce complications

Impact of residual coronary artery disease on patients undergoing TAVI. A meta-analysis of adjusted observational studies

Degenerative aortic valve disease requiring transcatheter aortic valve implantation (TAVI) shares similar risk factors with atherosclerotic coronary artery disease (CAD). For TAVI patients, management of CAD remains unsettled, due to both challenging clinical and interventional features. We conducted a systematic review on the impact of residual CAD on TAVI outcomes, and found that residual or baseline CAD of mild to moderate severity (ie SYNTAX score equal or less than 10) was not significantly associated with adverse outcomes after TAV

Lung ultrasound for the early diagnosis of COVID-19 pneumonia: an international multicenter study

Purpose: To analyze the application of a lung ultrasound (LUS)-based diagnostic approach to patients suspected of COVID-19, combining the LUS likelihood of COVID-19 pneumonia with patient\u2019s symptoms and clinical history. Methods: This is an international multicenter observational study in 20 US and European hospitals. Patients suspected of COVID-19 were tested with reverse transcription-polymerase chain reaction (RT-PCR) swab test and had an LUS examination. We identified three clinical phenotypes based on pre-existing chronic diseases (mixed phenotype), and on the presence (severe phenotype) or absence (mild phenotype) of signs and/or symptoms of respiratory failure at presentation. We defined the LUS likelihood of COVID-19 pneumonia according to four different patterns: high (HighLUS), intermediate (IntLUS), alternative (AltLUS), and low (LowLUS) probability. The combination of patterns and phenotypes with RT-PCR results was described and analyzed. Results: We studied 1462 patients, classified in mild (n = 400), severe (n = 727), and mixed (n = 335) phenotypes. HighLUS and IntLUS showed an overall sensitivity of 90.2% (95% CI 88.23\u201391.97%) in identifying patients with positive RT-PCR, with higher values in the mixed (94.7%) and severe phenotype (97.1%), and even higher in those patients with objective respiratory failure (99.3%). The HighLUS showed a specificity of 88.8% (CI 85.55\u201391.65%) that was higher in the mild phenotype (94.4%; CI 90.0\u201397.0%). At multivariate analysis, the HighLUS was a strong independent predictor of RT-PCR positivity (odds ratio 4.2, confidence interval 2.6\u20136.7, p < 0.0001). Conclusion: Combining LUS patterns of probability with clinical phenotypes at presentation can rapidly identify those patients with or without COVID-19 pneumonia at bedside. This approach could support and expedite patients\u2019 management during a pandemic surge