ABSTRACT Objective: This study aimed to evaluate the incidence of acute kidney injury in hospitalized Brazilian patients with COVID-19 and identify the risk factors associated with its development and prognosis during the two waves of the disease. Methods: We performed a prospective cohort study of hospitalized patients with COVID-19 at a public university hospital in São Paulo from March 2020 to May 2021. Results: Of 887 patients hospitalized with COVID-19, 54.6% were admitted to the intensive care unit. The incidence of acute kidney injury was 48.1%, and the overall mortality rate was 38.9%. Acute kidney replacement therapy was indicated for 58.8% of the patients. The factors associated with acute kidney injury were diuretic use (odds ratio [OR] 2.2, 95%CI= 1.2-4.1, p=0.01), mechanical ventilation (OR= 12.9, 95%CI= 4.3-38.2, p<0.0001), hematuria(OR= 2.02, 95%CI= 1.1-3.5, p<0.0001), chronic kidney disease (OR= 2.6, 95%CI= 1.2-5.5, p=0.009), age (OR= 1.03, 95%CI= 1.01-1.07, p=0.02), and elevated creatine phosphokinase (OR= 1.02, 95%CI= 1.01-1.07, p=0.02) and D-dimer levels (OR= 1.01, 95%CI= 1.01-1.09, p<0.0001). Mortality was higher among those with acute kidney injury (OR= 1.12, 95%CI= 1.02-2.05, p=0.01), elevated Sequential Organ Failure Assessment Scores (OR= 1.35, 95%CI= 1.1-1.6, p=0.007), elevated Acute Tubular Necrosis-Injury Severity Score (ATN-ISS; (OR= 96.4, 95%CI= 4.8-203.1, p<0.0001), and who received mechanical ventilation (OR= 12.9, 95%CI= 4.3-38.2, p<0.0001). During the second wave, the number of cases requiring mechanical ventilation (OR= 1.57, 95%CI= 1.01-2.3, p=0.026), with proteinuria (OR= 1.44, 95%CI= 1.01-2.1, p=0.04), and with higher ATN-ISS Scores (OR= 40.9, 95%CI= 1.7-48.1, p=0.04) was higher than that during the first wave. Conclusion: Acute kidney injury was frequent in hospitalized patients with COVID-19, and the second wave was associated with greater severity. However, mortality rates were similar between the two periods, which may reflect both the effectiveness of vaccines and the constant learning that frontline professionals gained throughout the pandemic to provide greater support to their patients. Registry of Clinical Trials: RBR-62y3h7 Objective COVID19 COVID 19 COVID-1 Methods 202 2021 Results 88 COVID19, 19, 546 54 6 54.6 unit 481 48 1 48.1% 389 38 9 38.9% 588 58 8 58.8 odds OR [OR 22 2 2.2 95CI CI 95 95%CI 1.24.1, 1241 1.2 4.1, 4 1.2-4.1 p=0.01, p001 p p=0.01 , 0 01 p=0.01) OR= (OR 129 12 12.9 4.338.2, 43382 4.3 38.2, 3 4.3-38.2 p<0.0001, p00001 p<0.0001 0001 p<0.0001) hematuriaOR= hematuriaOR hematuria hematuria(OR 02 2.02 1.13.5, 1135 1.1 3.5, 5 1.1-3.5 26 2.6 1.25.5, 1255 5.5, 1.2-5.5 p=0.009, p0009 p=0.009 009 p=0.009) 103 03 1.03 1.011.07, 101107 1.01 1.07, 07 1.01-1.07 p=0.02, p002 p=0.02 102 1.02 Ddimer D dimer 101 1.011.09, 101109 1.09, 09 1.01-1.09 p<0.0001. . 112 1.12 1.022.05, 102205 2.05, 05 1.02-2.05 135 35 1.35 1.11.6, 1116 1.6, 1.1-1.6 p=0.007, p0007 p=0.007 007 p=0.007) NecrosisInjury Necrosis Injury ATNISS ATN ISS (ATN-ISS 964 96 96.4 4.8203.1, 482031 4.8 203.1, 203 4.8-203.1 157 57 1.57 1.012.3, 10123 2.3, 1.01-2.3 p=0.026, p0026 p=0.026 026 p=0.026) 144 44 1.44 1.012.1, 10121 2.1, 1.01-2.1 p=0.04, p004 p=0.04 04 409 40 40.9 1.748.1, 17481 1.7 48.1, 7 1.7-48.1 Conclusion severity However periods Trials RBR62y3h7 RBRyh RBR 62y3h7 y h RBR-62y3h COVID1 COVID- 20 54. 48.1 38.9 58. 2. 24 1.24.1 124 1. 41 4.1 1.2-4. p00 p=0.0 12. 338 4.338.2 4338 43 4. 382 38.2 4.3-38. p0000 p<0.000 000 2.0 13 1.13.5 113 11 3.5 1.1-3. 25 1.25.5 125 55 5.5 1.2-5. p000 p=0.00 00 10 1.0 011 1.011.07 10110 107 1.07 1.01-1.0 1.011.09 109 1.09 022 1.022.05 10220 205 2.05 1.02-2.0 1.3 1.11.6 111 16 1.6 1.1-1. 96. 8203 4.8203.1 48203 2031 203.1 4.8-203. 15 1.5 012 1.012.3 1012 23 2.3 1.01-2. 14 1.4 1.012.1 21 2.1 40. 748 1.748.1 1748 17 1.7-48. RBR62y3h yh 62y3h 48. 38. 1.24. 1.2-4 p0 p=0. 33 4.338. 433 4.3-38 p<0.00 1.13. 3. 1.1-3 1.25. 5. 1.2-5 1.011.0 1011 1.01-1. 1.022.0 1022 1.02-2. 1.11. 1.1-1 820 4.8203. 4820 203. 4.8-203 1.012. 1.01-2 74 1.748. 174 1.7-48 1.24 1.2- p=0 4.338 4.3-3 p<0.0 1.13 1.1- 1.25 1.011. 1.01-1 1.022. 1.02-2 1.11 82 4.8203 482 4.8-20 1.012 1.01- 1.748 1.7-4 p= 4.33 4.3- p<0. 1.011 1.022 1.02- 4.820 4.8-2 1.74 1.7- p<0 4.82 4.8- p<

Resumo Objetivou-se analisar a frequência de nascimentos pré-termo, identificar fatores de risco e a evolução destes em uma década (2001-20052010) em município paulista. Estudo de série temporal realizado com dados do Sistema de Informações de Nascidos Vivos. Utilizou-se a regressão logística univariada e múltipla para identificar fatores associados ao nascimento pré-termo e a regressão linear para avaliar a tendência temporal destes no período. Para evitar subestimação, às frequências de nascimento pré-termo obtidas aplicou-se fator de correção. Houve discreto aumento da taxa de nascimento pré-termo: 12,5%, 12,0% e 13,2%. Após ajuste para confundidores, associaram-se com maior chance desse desfecho e aumentaram na década: idade materna igual ou superior a 35 anos e parto cesárea; diminuíram no período: nascimento em hospital de alto risco e menos de sete consultas pré-natais, permanecendo estável a gemelaridade. Comparando ao parto vaginal, nascer de cesariana dobrou a chance de nascimento pré-termo. Dentre os cinco fatores associados à prematuridade, três (parto cesárea, nascimento em hospital de alto risco e menos de sete consultas de pré-natais) são modificáveis por ações no âmbito dos serviços de saúde.

Abstract This study sought to analyze the frequency of preterm births and identify the respective risk factors and their evolution over a decade (2001-2005-2010) in a city in São Paulo state. It is a time-series study using data from the Live Birth Information System. Univariate and multiple logistic regression were used to identify factors associated with preterm births, and linear regression was used to evaluate the time-series tendency of such factors in the period. To avoid underestimation, a correction factor was applied to the preterm frequencies obtained. A discrete increase in preterm birth was observed: 12.5%, 12% and 13.2%. After adjusting for confounding factors, maternal age equal to or higher than 35 years and cesarean sections were associated with higher chances for preterm births and increased over the decade. The number of births in high-risk hospitals and of women with fewer than seven prenatal consultations decreased during the period, while multiple pregnancies remained stable. Compared to vaginal births, cesarean sections doubled the chance of preterm birth. Among the five factors associated with preterm birth, three (cesarean sections, births in high-risk hospitals and fewer than seven prenatal consultations) can be modified by actions taken by health care services.

Resumo Objetivou-se analisar a frequência de nascimentos pré-termo, identificar fatores de risco e a evolução destes em uma década (2001-20052010) em município paulista. Estudo de série temporal realizado com dados do Sistema de Informações de Nascidos Vivos. Utilizou-se a regressão logística univariada e múltipla para identificar fatores associados ao nascimento pré-termo e a regressão linear para avaliar a tendência temporal destes no período. Para evitar subestimação, às frequências de nascimento pré-termo obtidas aplicou-se fator de correção. Houve discreto aumento da taxa de nascimento pré-termo: 12,5%, 12,0% e 13,2%. Após ajuste para confundidores, associaram-se com maior chance desse desfecho e aumentaram na década: idade materna igual ou superior a 35 anos e parto cesárea; diminuíram no período: nascimento em hospital de alto risco e menos de sete consultas pré-natais, permanecendo estável a gemelaridade. Comparando ao parto vaginal, nascer de cesariana dobrou a chance de nascimento pré-termo. Dentre os cinco fatores associados à prematuridade, três (parto cesárea, nascimento em hospital de alto risco e menos de sete consultas de pré-natais) são modificáveis por ações no âmbito dos serviços de saúde.

Abstract This study sought to analyze the frequency of preterm births and identify the respective risk factors and their evolution over a decade (2001-2005-2010) in a city in São Paulo state. It is a time-series study using data from the Live Birth Information System. Univariate and multiple logistic regression were used to identify factors associated with preterm births, and linear regression was used to evaluate the time-series tendency of such factors in the period. To avoid underestimation, a correction factor was applied to the preterm frequencies obtained. A discrete increase in preterm birth was observed: 12.5%, 12% and 13.2%. After adjusting for confounding factors, maternal age equal to or higher than 35 years and cesarean sections were associated with higher chances for preterm births and increased over the decade. The number of births in high-risk hospitals and of women with fewer than seven prenatal consultations decreased during the period, while multiple pregnancies remained stable. Compared to vaginal births, cesarean sections doubled the chance of preterm birth. Among the five factors associated with preterm birth, three (cesarean sections, births in high-risk hospitals and fewer than seven prenatal consultations) can be modified by actions taken by health care services.