Back

Prognosis and hematological findings in patients with COVID-19 in an Amazonian population of Peru

Iglesias-Osores, S.; Rafael-Heredia, A.; Rojas-Tello, E. R.; Ortiz-Uribe, W. A.; Leveau-Bartra, W.; Leveau-Bartra, O. A.; Alcantara-Mimbela, M.; Cordova-Rojas, L. M.; Lopez-Lopez, E.; Failoc-Rojas, V. E.

2021-02-01 hematology
10.1101/2021.01.31.21250859 medRxiv
Show abstract

ObjectiveThis study examined the laboratory results of COVID-19 patients from a hospital in the Peruvian Amazon and their clinical prognosis. MethodsAn analytical cross-sectional study was carried out whose purpose was to identify the laboratory tests of patients with COVID-19 and mortality in a hospital in Ucayali, Peru during the period from March 13 to May 9, 2020, selecting a total of 127 with Covid-19. Mean and the standard deviation was described for age, leukocytes, neutrophils, platelets, RDW-SD; median and interquartile range for the variables lymphocyte, RN / L, fibrinogen, CRP, D-dimer, DHL, hematocrit, monocytes, eosinophils. ResultsNo differences were observed in this population regarding death and sex (OR: 1.31; 95% CI 0.92 to 1.87), however, it was observed that, for each one-year increase, the probability of death increased by 4% (PR: 1.04, 95% CI 1.03 to 1.05). The IRR (Incidence Risk Ratio) analysis for the numerical variables showed results strongly associated with hematological values such as Leukocytes (scaled by 2500 units) (IRR: 1.08, 95% CI 1.03 to 1.13), neutrophils (scaled by 2500 units) (IRR: 1.08; 95% CI 1.03 to 1.13), on the contrary, it is observed that the increase of 1000 units in lymphocytes, the probability of dying decreased by 48% (IRR: 0.52; 95% CI 0.38 to 071). ConclusionParameters such as leukocytes and neutrophils were statistically much higher in patients who died.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.