key: cord-0934025-j35tviyo authors: Murillo-Zamora, E.; HERNANDEZ-SUAREZ, C. M. title: Survival in adult inpatients with COVID-19 date: 2020-05-26 journal: nan DOI: 10.1101/2020.05.25.20110684 sha: 7ae5f870aa119594a7ee9f82b883ccc78973641e doc_id: 934025 cord_uid: j35tviyo We conducted a nationwide and retrospective cohort study to assess the survival experience and determining factors in adult inpatients with laboratory-confirmed COVID-19. Data from 5,393 individuals were analyzed using the Kaplan-Meier method and a multivariate Cox proportional hazard regression model was fitted. The 7-day survival was 0.822 and went to 0.482, 0.280, and 0.145 on days 15, 21, and 30 of hospital stay, respectively. In the multiple analysis, factors associated with an increased risk of dying were: male gender, age, longer disease evolution before hospital entry, exposure to mechanical ventilator support, and personal history of chronic noncommunicable diseases (namely obesity, type-2 diabetes mellitus, and chronic kidney disease). To the best of our knowledge, this is the first study analyzing the survival probability in a large subset of Latin-American adults with COVID-19 and our results contribute to achieving a better understanding of disease evolution. Worldwide, the coronavirus disease 2019 (COVID-19) by severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) pandemic represents unprecedented health and social crisis. The clinical spectrum of SARS-COV-2 infection is wide and includes asymptomatic contagion, mild upper and unspecific res-5 piratory tract symptoms, and severe viral pneumonia [1] . Most of COVID-19 cases have a good prognosis but a subset of patients develop a critical condition and even die [2] . On May 21, 2020, the observed COVID-19 mortality in Mexico has been high and over 6.5 thousand deaths were registered [3] and, among Latin-American 10 countries, is only overcome by Brazil (nearly 18 thousand deaths) [4] . Published data regarding the clinical course of COVID-19 inpatients is scarce. The computed 14-day survival rate in a study that took place in the city of New York (U.S.), and where 2,773 inpatients were analyzed, was around 50% [5] . The evaluation of clinical outcomes in hospitalized patients with SARS-15 COV-2 infection may help clinicians and epidemiologists better appreciate the disease evolution, and lead to a more efficient allocation of healthcare resources [6] . This study aimed to assess the survival experience and associated factors in a large cohort of hospitalized adult inpatients with laboratory-confirmed COVID-19. 20 We conducted a nationwide and retrospective dynamic cohort study focusing on the survival of hospitalized adult patients with laboratory-confirmed (reverse transcription polymerase chain reaction, qRT-PCR) COVID-19. Eligi-25 ble subjects were identified from the nominal records of a normative and webbased system for the epidemiological surveillance of viral respiratory diseases, which belongs to the Mexican Institute of Social Security (IMSS, the Spanish acronym). . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 26, 2020. . https://doi.org/10.1101/2020.05.25.20110684 doi: medRxiv preprint Individuals aged 18 years or above at acute illness onset and with conclusive evidence of COVID-19 by SARS-COV-2 were potentially eligible. Children and teenagers were not enrolled since current data suggest that severe illness is a rare event among them [7] . Subjects with hospital admission date later than May 5, 2020, were excluded, as well as those with missing clinical or epidemi-35 ological data of interest. A total of 341 inpatients were excluded (voluntary hospital discharge, 6.5%; aged under 18 years, 6.7%; referred to another health institution, 33.1%; missing information, 53.7%). Clinical and epidemiological data of interest were collected from the au-40 dited database and included demographic characteristics, illness severity (mildmoderate/severe) [8] at hospital admission, the personal history of chronic noncommunicable diseases (no/yes; obesity, arterial hypertension, type 2 diabetes mellitus, asthma, chronic obstructive pulmonary disease, and chronic kidney disease). Dates from illness onset, hospital admission, and discharge (if appli-45 cable), as well as the exposure to invasive mechanical ventilation during stay (no/yes), were also obtained from the analyzed surveillance system. The analyzed variables are summarized in Table 1. Medical files from the patients and death certificates represent the primary data source of the surveillance system which data base was employed. We analyzed the survival time of hospitalized COVID-19 adult patients measured as the time elapsed from the date of hospital entry (starting event) to the date of in-hospital death (final event). The censored variable was defined as the patients who did not present the interest event (did not die) during the follow-55 up period and the date of hospital discharge was used to compute the time-at risk. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 26, 2020. . https://doi.org/10.1101/2020.05.25.20110684 doi: medRxiv preprint Nasopharyngeal and deep nasal swabs were collected from all analyzed patients in order to perform qRT-PCR (SuperScript™ III Platinum™ One-Step 60 qRT-PCR Kits) analysis. Summary statistics were computed. The Kaplan-Meier method [9] was employed to estimate the probability of survival from the date of hospital entry. We Data from 5,393 participants (admitted to hospital in a period of 62 days from March 4, to May 5, 2020) were analyzed for a total follow-up of 48,568 75 person-days. The overall COVID-19 in-hospital lethality rate (n= 1,735) was 35.7 per 1,000 person-days. The mean hospital stay (± standard deviation) was 8.4 ± 6.4 vs. 9.3 ± 4.0 days in cases with fatal and nonfatal outcome, respectively (p< 0.001). Table 1 shows the characteristics of participants for selected variables. Most 80 of them were male (63.6%) and 3 out of 4 were aged 45 years or above at hospital admission. Severe illness at entry was documented in 80.5% of participants. In general and as is also shown in Table 1 , enrolled patients had a high prevalence of analyzed chronic noncommunicable illnesses. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. Table 2 . The 7-day survival rate was 0.808 (95% CI 0.791-0.824). After 2 weeks from admission, the survival was below 50% (0.482, 95% CI 0.450-0.513). In the multiple model ( COVID-19 inpatients requiring ventilatory mechanical support during the 100 stay was also associated with the risk of dying (HR= 1.91, 95%, CI 1.70-2.15). High-risk comorbidities included obesity, type-2 diabetes mellitus, and chronic kidney disease (Table 3 ). The results of this study describe the survival experience of hospitalized 105 adults with COVID-19 and several factors associated with disease outcomes were evaluated. To the best of our knowledge, this is the first study evaluating illness outcomes in a large subset of Latin-American COVID-19 inpatients. The related burden of SARS-COV-2 in Mexico has been high and obesity and chronic noncommunicable diseases (mainly type-2 diabetes mellitus), both . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . https://doi.org/10.1101/2020.05.25.20110684 doi: medRxiv preprint The prevalence of type-2 diabetes mellitus and arterial hypertension in our study sample was significantly higher than national means (diabetes, 31.1% Gender-related differences have been documented in the severity of SARS-120 COV-2 symptomatic infection and diseases outcomes. In our study, a shorter survival was observed in males (log-rank test, p< 0.001) and, for example, the Kaplan-Meier estimator after one week of hospitalization was 0.840 (95% 0.823-0.856) and 0.810 (95% 0.797-0.824) in women and men, respectively. A protective role of estrogen signaling seems to be involved [14] . Elderly has been consistently associated with death risk among COVID-19 patients and this association is independent from gender and other diseases which frequency also increases with age. In our study, the adjusted HR per In our study, longer waiting time between symptoms onset and admission was also associated with survival; participants with longer delay (≥ 4 days), and when compared with those with recent symptoms (<1 day from disease onset to 135 admission), had a 70% increase in the risk of dying (HR= 1.68, 95% 1.51-1.87). Similar findings were described in Hubei, China [16] , however the mean elapsed days in our study sample was lower (3.1 vs. 5.7). Patients requiring mechanical ventilator support during stay had a nearly 2-fold (HR= 1.96, 95%, CI 1.75-2.21) in death risk. This seems to be an effect 140 of the illness severity rather than a cause, since ventilator support was needed in 10.4% vs.4.5% (p< 0.001) of severe and mild-moderate cases, respectively. However, and despite the use of these mechanical devices, COVID-19 patients commonly complicate with organ failure or shock [17] . In addition, bacterial co-6 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . https://doi.org/10.1101/2020.05.25.20110684 doi: medRxiv preprint role in disease outcomes [18] . The inclusion of only laboratory-positive cases, together with the large sample size and national representativeness, are major strengths of this study. However, potential limitations must be cited. First, we were unable to assess a gradient between body mass and survival functions, since anthropometric registers None to declare. The data that support the findings of this study are available on request from the corresponding author. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . https://doi.org/10.1101/2020.05.25.20110684 doi: medRxiv preprint CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . Personal history of: . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. 16 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 26, 2020. . https://doi.org/10.1101/2020.05.25.20110684 doi: medRxiv preprint Table 2 continued from previous page 2) Variables listed in the table were used to compute adjusted HR. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 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