Mechanical ventilation and death in pregnant patients admitted for COVID-19: a prognostic analysis from the Brazilian COVID-19 registry score.

BACKGROUND: The assessment of clinical prognosis of pregnant COVID-19 patients at hospital presentation is challenging, due to physiological adaptations during pregnancy. Our aim was to assess the performance of the ABC2-SPH score to predict in-hospital mortality and mechanical ventilation support in pregnant patients with COVID-19, to assess the frequency of adverse pregnancy outcomes, and characteristics of pregnant women who died. METHODS: This multicenter cohort included consecutive pregnant patients with COVID-19 admitted to the participating hospitals, from April/2020 to March/2022. Primary outcomes were in-hospital mortality and the composite outcome of mechanical ventilation support and in-hospital mortality. Secondary endpoints were pregnancy outcomes. The overall discrimination of the model was presented as the area under the receiver operating characteristic curve (AUROC). Overall performance was assessed using the Brier score. RESULTS: From 350 pregnant patients (median age 30 [interquartile range (25.2, 35.0)] years-old]), 11.1% had hypertensive disorders, 19.7% required mechanical ventilation support and 6.0% died. The AUROC for in-hospital mortality and for the composite outcome were 0.809 (95% IC: 0.641-0.944) and 0.704 (95% IC: 0.617-0.792), respectively, with good overall performance (Brier = 0.0384 and 0.1610, respectively). Calibration was good for the prediction of in-hospital mortality, but poor for the composite outcome. Women who died had a median age 4 years-old higher, higher frequency of hypertensive disorders (38.1% vs. 9.4%, p < 0.001) and obesity (28.6% vs. 10.6%, p = 0.025) than those who were discharged alive, and their newborns had lower birth weight (2000 vs. 2813, p = 0.001) and five-minute Apgar score (3.0 vs. 8.0, p < 0.001). CONCLUSIONS: The ABC2-SPH score had good overall performance for in-hospital mortality and the composite outcome mechanical ventilation and in-hospital mortality. Calibration was good for the prediction of in-hospital mortality, but it was poor for the composite outcome. Therefore, the score may be useful to predict in-hospital mortality in pregnant patients with COVID-19, in addition to clinical judgment. Newborns from women who died had lower birth weight and Apgar score than those who were discharged alive.

Predictors of venous thromboembolism in COVID-19 patients: results of the COVID-19 Brazilian Registry.

Previous studies that assessed risk factors for venous thromboembolism (VTE) in COVID-19 patients have shown inconsistent results. Our aim was to investigate VTE predictors by both logistic regression (LR) and machine learning (ML) approaches, due to their potential complementarity. This cohort study of a large Brazilian COVID-19 Registry included 4120 COVID-19 adult patients from 16 hospitals. Symptomatic VTE was confirmed by objective imaging. LR analysis, tree-based boosting, and bagging were used to investigate the association of variables upon hospital presentation with VTE. Among 4,120 patients (55.5% men, 39.3% critical patients), VTE was confirmed in 6.7%. In multivariate LR analysis, obesity (OR 1.50, 95% CI 1.11-2.02); being an ex-smoker (OR 1.44, 95% CI 1.03-2.01); surgery ≤ 90 days (OR 2.20, 95% CI 1.14-4.23); axillary temperature (OR 1.41, 95% CI 1.22-1.63); D-dimer ≥ 4 times above the upper limit of reference value (OR 2.16, 95% CI 1.26-3.67), lactate (OR 1.10, 95% CI 1.02-1.19), C-reactive protein levels (CRP, OR 1.09, 95% CI 1.01-1.18); and neutrophil count (OR 1.04, 95% CI 1.005-1.075) were independent predictors of VTE. Atrial fibrillation, peripheral oxygen saturation/inspired oxygen fraction (SF) ratio and prophylactic use of anticoagulants were protective. Temperature at admission, SF ratio, neutrophil count, D-dimer, CRP and lactate levels were also identified as predictors by ML methods. By using ML and LR analyses, we showed that D-dimer, axillary temperature, neutrophil count, CRP and lactate levels are risk factors for VTE in COVID-19 patients.

Diagnostic accuracy of a SARS-CoV-2 rapid test and optimal time for seropositivity according to the onset of symptoms.

Point-of-care serological tests for SARS-CoV-2 have been used for COVID-19 diagnosis. However, their accuracy over time regarding the onset of symptoms is not fully understood. We aimed to assess the accuracy of a point-of-care lateral flow immunoassay (LFI). Subjects, aged over 18 years, presenting clinical symptoms suggestive of acute SARS-CoV-2 infection were tested once by both nasopharyngeal and oropharyngeal RT-PCR and LFI. The accuracy of LFI was assessed in periodic intervals of three days in relation to the onset of symptoms. The optimal cut-off point was defined as the number of days required to achieve the best sensitivity and specificity. This cut-off point was also used to compare LFI accuracy according to participants' status: outpatient or hospitalized. In total, 959 patients were included, 379 (39.52%) tested positive for SARS-CoV-2 with RT-PCR, and 272 (28.36%) tested positive with LFI. LFI best performance was achieved after 10 days of the onset of symptoms, with sensitivity and specificity of 84.9% (95%CI: 79.8-89.1) and 94.4% (95%CI: 91.0-96.8), respectively. Although the specificity was similar (94.6% vs. 88.9%, p = 0.051), the sensitivity was higher in hospitalized patients than in outpatients (91.7% vs. 82.1%, p = 0.032) after 10 days of the onset of symptoms. Best sensitivity of point-of-care LFI was found 10 days after the onset of symptoms which may limit its use in acute care. Specificity remained high regardless of the number of days since the onset of symptoms.

Clinical characteristics and predictors of mechanical ventilation in patients with COVID-19 hospitalized in Southern Brazil. / Características clínicas e preditores de ventilação mecânica em pacientes com COVID-19 hospitalizados no sul do país.

OBJECTIVE: This study aims to describe the clinical characteristics and predictors of mechanical ventilation of adult inpatients with COVID-19 in a single center. METHODS: A retrospective cohort study was performed and included adult inpatients hospitalized from March 17th to May 3rd, 2020, who were diagnosed with SARS-CoV-2 infection. Clinical and demographic characteristics were extracted from electronic medical records. RESULTS: Overall, 88 consecutive patients were included in this study. The median age of the patients was 63 years (IQR 49 - 71); 59 (67%) were male, 65 (86%) had a college degree and 67 (76%) had at least one comorbidity. Twenty-nine (33%) patients were admitted to the intensive care unit, 18 (20%) patients needed mechanical ventilation, and 9 (10.2%) died during hospitalization. The median length of stay in the intensive care unit and the median duration of mechanical ventilation was 23 and 29.5 days, respectively. An age ≥ 65 years was an independent risk factor for mechanical ventilation (OR 8.4 95%CI 1.3 - 55.6 p = 0.02). CONCLUSION: Our findings describe the first wave of Brazilian patients hospitalized for COVID-19. Age was the strongest predictor of respiratory insufficiency and the need for mechanical ventilation in our population.

OBJETIVO: Descrever as características clínicas e os preditores de ventilação mecânica em pacientes adultos internados com COVID-19. MÉTODOS: Conduziu-se um estudo de coorte retrospectiva com inclusão de pacientes hospitalizados entre 17 de março e 3 de maio de 2020, que tiveram o diagnóstico de infecção pelo SARS-CoV-2. As características clínicas e demográficas foram extraídas de registros em prontuário eletrônico. RESULTADOS: Incluíram-se no estudo 88 pacientes consecutivos. A mediana da idade dos pacientes foi de 63 anos (IQR: 49 - 71); 59 (67%) pacientes eram do sexo masculino, 65 (86%) tinham educação universitária e 67 (76%) tinham, no mínimo, uma comorbidade. Dentre eles, 29 (33%) pacientes foram admitidos à unidade de terapia intensiva, 18 (20%) necessitaram de ventilação mecânica e nove (10,2%) morreram durante a hospitalização. O tempo mediano de permanência na unidade de terapia intensiva e o tempo mediano de ventilação mecânica foram, respectivamente, de 23 e 29,5 dias. Idade acima ou igual a 65 anos foi fator de risco independente para ventilação mecânica (RC: 8,4; IC95% de 1,3 - 55,6; valor de p = 0,02). CONCLUSÃO: Nossos achados descrevem a primeira onda de pacientes brasileiros hospitalizados por COVID-19. Em nossa população, idade foi o maior preditor de insuficiência respiratória e necessidade de ventilação mecânica.