Covid-19 e saúde baseada em evidências: diretrizes clínicas, laboratoriais, terapêuticas e de prognóstico
Bibliographic record
Abstract
Introduction: The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has been increasing and has become a public health emergency. There is limited evidence on the outcomes of COVID-19 in patients when associated with other clinical conditions. Objective: To detect clinical, laboratory, therapeutic and prognostic guidelines, through evidence-based medicine, in situations involving patients infected with SARV-COV-2 associated with other clinical conditions. Methods: These are seven systematic reviews and meta-analyses, which followed the guidelines of PRISMA and MORSE, being registered in PROSPERO. PubMed, Web of Science, Embase, CINAHAL, LILACS, clinictrials.gov, SCOPUS, Google Scholar, and Cochrane, was the study bases used for articles published from December 2019 to February 2021. The primary outcomes were morbidity and mortality. Three independent reviewers selected the studies and extracted data from the original publications. The risk of bias was assessed using the Newcastle-Ottawa Scale for observational studies and RoB 2 for a randomized clinical trial. To assess the strength of evidence of the data included, the Assessment, Development, and Assessment of Classification of Recommendation (GRADE) method were used. Data synthesis was performed qualitatively. To assess heterogeneity, he calculated I2 (Higgins test). When applicable, quantitative synthesis was performed using R statistical software. Result: COVID-19 and Pregnancy: 70 articles were included involving 10047 pregnant women with COVID-19. The most common symptoms were: fever, cough, chest pain, dyspnea, nasal congestion, sore throat, headache, myalgia, anosmia, ageusia, nausea, vomiting, diarrhea, tachypnea, tachycardia, fatigue and oxygen desaturation. The main type of delivery was cesarean (42% [CI 95%; 0.38; 0.47]; I2 = 92%). There were 108 deaths (2% [CI 95%, 0.01; 0.03]; I2 = 46%) and 50 abortions (15% [CI 95%; 0.11; 0.21]; I2 = 73%] Ventilatory support, ICU admission, and pneumonia were unfavorable outcomes. Lymphopenia, increased CRP, and liver were complications during pregnancy. Of the neonatal outcomes: fetal distress (11% [CI 95%; 0.06; 0.19; I2 = 91 %], birth weight (15% [CI 95%; 0.10; 0.21; I2 = 76%]; APGAR less than 7 (9% [CI 96%; 0.03; 0.27; I2 = 26%], admission to the NICU (25% [CI 95%; 0.15; 0.39; I2 = 90%] and fetal stress (11% [CI 95%; 0.06; 0.19; I2 = 91 %] were more prevalent. There is no evidence of COVID-19 in placenta, breast milk, umbilical cord, and amniotic fluid. COVID-19 and HIV/AIDS: Chest CT has been observed in patients with SARS-CoV-2 pneumonia with findings of multiple ground-glass opacities (GGO) in the lungs, requiring supplemental oxygenation. One patient developed complicated encephalopathy and tonic-clonic seizures; four patients were transplanted (two liver; two kidneys), one patient developed severe SARS-CoV-2 pneumonia, and 30 patients died (mortality rate, 11%). COVID-19 and Guillain Bare Syndrome (GBS): The main manifestations were fever, cough, dyspnea, sore throat, ageusia, anosmia, and respiratory failure, in addition to upper and lower limb anesthesia, tetraparesis, facial diplegia, coldness, asthenia, mastoid pain, back pain, dizziness and back pain. Conclusion: The outcomes of COVID-19 in patients when associated with other clinical conditions (Pregnancy, HIV, and GBS) are similar to healthy individuals. However, there are relevant differences in morbidity and mortality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.149 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".