Assessing Predictive Factors of COVID-19 Outcomes: A Retrospective Cohort Study in the Metropolitan Region of São Paulo (Brazil)
Abstract
:1. Introduction
2. Materials and Methods
2.1. Ethics and Study Design
2.2. Patients and Primary Data Collection
2.3. Secondary Socioeconomic Data Extraction
2.4. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Secondary Data (n = 1036) | Death Outcome (n = 459) | Non-Death Outcome (n = 577) | |
---|---|---|---|
Individual data | |||
Age (years) | mean (SD) | 69.02 (18.5) | 50.86 |
range | 17–99 | 3–95 | |
Hospitalization (yes) | % | 93.46 | 88.21 |
Time between COVID-19 symptom onset and health care system admission | mean (SD) | 6.80 (6.20) | 7.79 (6.18) |
Sociodemographic data | |||
Schooling (>8 years) | % | 53.06 | 55.80 |
Private health plan | % | 21.37 | 20.99 |
Electricity | % | 99.08 | 99.03 |
Water supply | % | 99.71 | 99.73 |
Sewage network | % | 99.27 | 99.13 |
Garbage collection | % | 99.92 | 99.91 |
Income (up to 1 minimum wage) | % | 33.82 | 33.84 |
Unemployment | % | 10.95 | 10.82 |
Homeownership | % | 58.48 | 58.31 |
Urban area | % | 99.37 | 99.38 |
Primary Data (n = 515) | Death Outcome (n = 251) | Non-Death Outcome (n = 264) | |
Individual data | |||
Age (years) | mean (SD) | 69.59 (18.5) | 52.44 (17.94) |
Range | 17–99 | 3–95 | |
Schooling (>8 years) | % | 55.77 | 55.26 |
Hospitalization (yes) | % | 93.23 | 88.26 |
Time between COVID-19 symptom onset and health care system admission | mean (SD) | 6.38 (6.34) | 8.16 (6.33) |
Diabetes | % | 40.64 | 23.1 |
Hypertension | % | 50.77 | 36.36 |
Obesity | % | 6.77 | 6.44 |
Component | |||
---|---|---|---|
1 | 2 | ||
Environmental Aspects | Social Aspects | ||
% | Variance explained | 34.9% | 28.8% |
Schooling (>8 years) | −0.883 | ||
Use of private health services | 0.403 | ||
Electricity | |||
Water supply | 0.783 | ||
Sewage network | 0.952 | ||
Garbage collection | 0.941 | ||
Income (up to 1 minimum wage) | 0.923 | ||
Unemployment | 0.885 |
Independent Variable | B | Exp (B) | CI (95%) Exp (B) | Wald Chi-Square | p-Value |
---|---|---|---|---|---|
Intercept | 2.083 | 8.030 | 7.402–8.710 | 2518.81 | 0.000 |
Age | −0.002 | 0.998 | 0.997–0.999 | 7.744 | 0.005 |
Sex | 0.027 | 1.027 | 0.981–1.075 | 1.302 | 0.254 |
Component 1 (environmental aspects) | −0.040 | 0.961 | 0.942–0.981 | 14.103 | 0.000 |
Component 2 (social aspects) | −0.002 | 0.998 | 0.976–1.022 | 0.020 | 0.887 |
Dependent Variable | Independent Variable | B | Exp (B) | CI (95%) Exp(B) | Wald Chi-Square | p-Value |
---|---|---|---|---|---|---|
Death outcome | Constant | −4.861 | - | - | 53.006 | 0.000 |
Age | 0.076 | 1.079 | 1.057–1.101 | 55.319 | 0.000 | |
Obesity | 1.060 | 2.885 | 1.092–7.620 | 4.573 | 0.032 | |
Diabetes | 0.647 | 1.909 | 1.088–3.350 | 5.077 | 0.024 |
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Amato, J.N.; Castelo, P.M.; Cirino, F.M.S.B.; Meyer, G.; Pereira, L.J.; Sartori, L.C.; Aderaldo, N.S.; Silva, F.C.e. Assessing Predictive Factors of COVID-19 Outcomes: A Retrospective Cohort Study in the Metropolitan Region of São Paulo (Brazil). Medicina 2021, 57, 1068. https://doi.org/10.3390/medicina57101068
Amato JN, Castelo PM, Cirino FMSB, Meyer G, Pereira LJ, Sartori LC, Aderaldo NS, Silva FCe. Assessing Predictive Factors of COVID-19 Outcomes: A Retrospective Cohort Study in the Metropolitan Region of São Paulo (Brazil). Medicina. 2021; 57(10):1068. https://doi.org/10.3390/medicina57101068
Chicago/Turabian StyleAmato, Juliana Neide, Paula Midori Castelo, Ferla Maria Simas Bastos Cirino, Guilherme Meyer, Luciano José Pereira, Luís Cláudio Sartori, Natália Simões Aderaldo, and Fernando Capela e Silva. 2021. "Assessing Predictive Factors of COVID-19 Outcomes: A Retrospective Cohort Study in the Metropolitan Region of São Paulo (Brazil)" Medicina 57, no. 10: 1068. https://doi.org/10.3390/medicina57101068