Authors summary
Why was this study done?
The study emerged from the concern of the epidemiological surveillance service in observing that many individuals were notified as suspects for COVID-19 and did not undergo the diagnostic test. Although the diagnostic test was available in health services, many cases were not closed because they did not have diagnostic criteria. In view of this scenario, it was decided to carry out a study to analyze the factors associated with not carrying out the diagnostic test for COVID-19.
What did the researchers do and find?
Using public data available on the COVID-19 Monitoring Panel in the state of Espírito Santo, we performed a hierarchical analysis to identify which factors were associated with not performing the molecular test for COVID-19. We describe that male individuals, black skin color, residing in the northern health region of the state of Espírito Santo and the homeless population were those who had the lowest chances of performing molecular diagnostic tests for COVID-19.
What do these findings mean?
Social, economic, contextual factors and the risk of worsening the disease were associated with carrying out the molecular test for COVID-19 in the state of Espírito Santo. Regardless of the presence of signs and symptoms, comorbidities and other risk factors, social factors are associated with not performing the molecular test for COVID-19. Actions that guarantee access to molecular testing in the SUS for all suspects of COVID-19 are necessary, especially for the most vulnerable population.
We used a hierarchical analysis to identify which factors were associated with not performing the molecular test for COVID-19. We describe that male individuals, black skin color, residing in the northern health region of the state of Espírito Santo and the homeless population were those who had the lowest chances of performing molecular diagnostic tests for COVID-19.
INTRODUCTION
Brazil registered the first confirmed case for COVID-19 in February 2020 where there was a shortage of diagnostic tests for the disease1. With reference to the epidemiological week 12 of the year 2022, Brazil has already registered 29,832,179 cases of COVID-19, being the third country with the highest number of confirmed cases in the world. Among the Brazilian states, Espírito Santo had the highest cumulative incidence rate, 13,201.7 cases per 100,000 inhabitants1 , 2 .
As the pandemic progressed, new diagnostic tests were introduced into clinical practice, which expanded access to diagnostic tests for the Brazilian population3 - 5 . The tests available for the laboratory diagnosis of COVID-19 are divided into three simplified categories3 - 5 . Serological tests for the detection of IgM and/or IgG antibodies with rapid results, but their results cannot be used as absolute evidence due to heterogeneity in sensitivity values and a population with high vaccination coverage3 , 5 . The rapid antigen diagnostic test, which consists of detecting the viral antigen in just a few minutes, has been widely used in Brazil1 , 5 .
Two meta-analysis studies, published in 2020, describe that immunological and antigen research tests should be used as an aid in the diagnosis of the disease, in addition to other tests3 , 4 . The reverse transcription polymerase chain reaction molecular test (RTq-PCR) detects the presence of the SARS-CoV-2 viral RNA and is the gold standard for having high sensitivity and specificity compared to other methods4 , 5 .
Until the epidemiological week 12 of the year 2022, Brazil carried out 29,224,15 RTq-PCR tests 1. In this scenario, the state of Espírito Santo is the tenth in carrying out the molecular test for COVID-19, registering 1,160,206 tests. However, Brazil was slow to implement an expanded testing policy1 , 2 . At the beginning of the pandemic, the Ministry of Health offered diagnostic tests for specific populations such as the elderly and people with risk factors with characteristic symptoms of COVID-19, which ended up restricting the access of a portion of the population to the molecular test for the diagnosis of COVID-196 .
This restriction of the population to testing at the beginning of the pandemic, the low number of tests made available by the unified health system network and the limitations of the municipalities regarding the specific structure and logistics to carry out the molecular test may have affected the access of the most vulnerable population. vulnerable to testing services1 , 6 . The black population, with low economic power, living on the streets and living in unhealthy places have difficulties in accessing diagnostic tests for COVID-197 - 9 . However, to improve our knowledge, no studies were found in Brazil and in other countries in a similar socioeconomic development process. Thus, the objective is to evaluate the factors associated with carrying out the molecular test for COVID-19.
METHODS
Study design and context
This is a cross-sectional study based on secondary data from the COVID-19 PANEL of the Secretary of State for Health of Espírito Santo, fed daily through notifications of suspected cases of COVID-19 carried out by health services through the electronic notification system e- SUS VS10 .
In 2019, the state of Espírito Santo had 4,018,650 inhabitants distributed in 78 municipalities, divided into four health regions, North, South, Central and Metropolitan, in which the only State Central Laboratory of Public Health is located that performs molecular tests for the diagnosis of COVID-19 in the Unified Health System, located in the capital, Vitória11 .
The selected period was determined by the technical notes published by the Secretary of State for Health of Espírito Santo. We included the forms from September 11, 2020 to March 2, 2021, which corresponds to the date of publication of Technical Note 073/2020 on September 11, 2020, which determined the testing of all suspects of COVID-19 by the method and Technical Note 02/2021 on March 2, 2021, which guides the performance of the specific antigen capture test with the first-choice method12 , 13 .
Participants
Notifications with municipality of residence in the state of Espírito Santo were included. Those that contained information about having performed other diagnostic methods such as serology and rapid tests were excluded.
Variables
Performing the test using the molecular method was considered the dependent variable of the study. A variable “Performed molecular diagnosis for COVID-19” (yes; no) was created. The sheets that had the molecular test collection date were classified as “Yes” and the sheets without collection date were classified as “No”.
The explanatory variables were grouped in a model of hierarchical levels adapted from the model of tuberculosis determinants14 :
Sociodemographic variables - Level I:
Gender (female; male);
Skin color (self-declared according to IBGE: white, black, brown, yellow, indigenous);
Age (in life cycles: children (0 to 9 years old), adolescents (10 to 19 years old), adults (20 to 59 years old) and elderly (≥ 60 years old);
Education (in years: 0; 1-4; 5-8; 9-12; >12).
Contextual Variables – Level II:
Health region (metropolitan; south; central; north);
Homeless population (no; yes);
Health professional (no; yes);
Disabled person (no; yes).
Variables of associated diseases/comorbidities - Level III:
Chronic cardiovascular disease (no; yes);
Chronic lung disease (no; yes);
Chronic kidney disease (no; yes);
Diabetes mellitus (no; yes);
Smoking (no; yes);
Obesity (no; yes).
Variables of the current clinical situation related to COVID-19 – Level IV:
Data source and measurement
Data were obtained from the COVID-19 public panel, available daily by the Secretary of State for Health of Espírito Santo at the electronic address: https://coronavirus.es.gov.br/painel-covid-19-es, accessed on 19 May 202110 .
Statistical methods
For the description of the variables, absolute and relative frequencies were used. In the bivariate analysis, logistic regression was used to obtain the measures of association between the variables and having performed a molecular diagnosis for COVID-19.
Variables with a p-value <0.20 in the bivariate analysis were introduced into the regression model according to the hierarchical levels: level I (sociodemographic), level II (contextual), level III (associated diseases/comorbidities) and level IV (current clinical situation related to COVID-19)15. Variables were maintained at the following levels as an adjustment if p value < 0.05. The association of each factor with having performed the molecular test is interpreted as adjusted for the variables of the hierarchical levels above it and also of the same level.
Results were expressed by the measure of association odds ratio (OR) and 95% confidence intervals (95%CI). Statistical analyzes were performed in Stata v. 14.0 (StataCorp, CollegeStation, TX, USA).
RESULTS
A total of 664,301 suspected COVID-19 notification forms were identified during the study period, of which 340,678 (51.2%) contained information on carrying out the molecular test for COVID-19, 244,530 (36.9%) had performed other laboratory methods and in 79,093 (11.9%) there were no diagnostic tests. The total study sample was 419,771 notification forms. The overall prevalence of molecular testing for COVID-19 in the sample was 81.1% (95%CI 81.0%;81.2%).
In the hierarchical analysis, sociodemographic variables, level I, male gender (OR=0.96 – 95%CI 0.94-0.98), black skin color (OR=0.75 – 95%CI 0.73- 0.78), brown (OR=0.81 – 95%CI 0.79-0.83) and yellow (OR=0.74 – 95%CI 0.71-0.77) when compared to white skin color, had the lowest chance of performing the molecular test for COVID-19. Elderly aged ≥ 60 years (OR=2.70 – 95%CI 2.56-3.85), when compared to children aged 0 to 9 years, had a greater chance of undergoing the molecular test for COVID-19, as well as individuals with more than 12 years of schooling (OR=1.83 – 95%CI 1.73;1.93) when compared with illiterates. In level II, contextual variables, living in the northern health region (OR=0.37 – 95%CI 0.36-0.39) had the lowest chance of performing the molecular test when compared to the metropolitan health region. Health professionals had the highest chance (OR=1.43 – 95%CI 1.36-1.50), whereas the homeless population (OR=0.76 – 95%CI 0.67-0.85) had the lowest chance of performing the molecular test ( table 3 ).
Table 3 : Odds ratio (OR) of performing molecular diagnosis for COVID-19 by study variables, Espírito Santo, September 11, 2020 to March 2, 2021
Variables | OR without ajustment (IC95%) | p-value b | OR ajusted (IC95%) | p-value b |
---|---|---|---|---|
Sociodemographic - Level I | ||||
Sex | <0.001 | 0.001 | ||
Feminine | 1.00 | 1.00 | ||
Masculine | 0.93 (0.91-0.94) | 0.96 (0.94-0.98) | ||
skin color | <0.001 | <0.001 | ||
White | 1.00 | 1.00 | ||
black | 0.72 (0.69-0.74) | 0.75 (0.73-0.78) | ||
brown | 0.72 (0.71-0.74) | 0.81 (0.79-0.83) | ||
Yellow | 0.62 (0.60-0.64) | 0.74 (0.71-0.77) | ||
Indigenous | 0.17 (0.15-0.19) | 0.97 (0.68-1.37) | ||
Age (Lifecycle) | <0.001 | <0.001 | ||
Child | 1.00 | 1.00 | ||
Adolescent | 1.78 (1.72-1.84) | 1.46 (1.29-1.64) | ||
Adult | 2.62 (2.55-2.68) | 2.13 (2.03-2.24) | ||
Elderly | 3.04 (2.94-3.15) | 2.70 (2.56-2.85) | ||
Education (years) | <0.001 | <0.001 | ||
0 | 1.00 | 1.00 | ||
1-4 | 1.53 (1.46-1.59) | 1.22 (1.16-1.28) | ||
5-8 | 1.60 (1.54-1.66) | 1.19 (1.13-1.26) | ||
9-12 | 1.92 (1.86-1.99) | 1.37 (1.31-1.44) | ||
> 12 | 2.62 (2.53-2.72) | 1.83 (1.73-1.93) | ||
Contextual - Level II | ||||
health region | <0.001 | <0.001 | ||
metropolitan | 1.00 | 1.00 | ||
South | 1.45 (1.41-1.49) | 0.99 (0.96-1.02) | ||
Central | 0.51 (0.50-0.52) | 0.56 (0.54-0.58) | ||
North | 0.38 (0.37-0.39) | 0.37 (0.36-0.39) | ||
Street population | <0.001 | <0.001 | ||
No | 1.00 | 1.00 | ||
Yes | 0.78 (0.71-0.86) | 0.76 (0.67-0.85) | ||
Health professional | <0.001 | <0.001 | ||
No | 1.00 | 1.00 | ||
Yes | 1.59 (1.52-1.65) | 1.43 (1.36-1.50) | ||
disabled person | 0.279 | - | ||
No | 1.00 | - | - | |
Yes | 0.96 (0.89-1.03) | - | - | |
Associated diseases/comorbidities - Level III | ||||
chronic cardiovascular disease | <0.001 | <0.001 | ||
No | 1.00 | 1.00 | ||
Yes | 1.22 (1.19-1.25) | 1.13 (1.09-1.17) | ||
chronic lung disease | <0.001 | 0.220 | ||
No | 1.00 | 1.00 | ||
Yes | 0.84 (0.81-0.88) | 0.96 (0.91-1.02) | ||
chronic kidney disease | 0.002 | 0.057 | ||
No | 1.00 | 1.00 | ||
Yes | 1.26 (1.08-1.46) | 1.22 (0.99-1.49) | ||
diabetes mellitus | <0.001 | 0.016 | ||
No | 1.00 | 1.00 | ||
Yes | 1.23 (1.18-1.29) | 1.07 (1.01-1.14) | ||
smoking | <0.001 | <0.001 | ||
No | 1.00 | 1.00 | ||
Yes | 0.79 (0.76-0.83) | 0.71 (0.67-0.75) | ||
Obesity | 0.256 | - | ||
No | 1.00 | - | ||
Yes | 0.96 (0.91-1.02) | - | ||
Current clinical situation related to COVID-19 - Level IV | ||||
Fever | <0.001 | 0.022 | ||
No | 1.00 | 1.00 | ||
Yes | 0.92 (0.91-0.94) | 1.02 (1.00-1.04) | ||
Cough | <0.001 | <0.001 | ||
No | 1.00 | 1.00 | ||
Yes | 0.96 (0.95-0.98) | 0.95 (0.92-0.97) | ||
breathing difficulty | 0.329 | 0.279 | ||
No | 1.00 | 1.00 | ||
Yes | 1.01 (0.98-1.03) | 0.98 (0.95-1.01) | ||
runny nose | 0.001 | 0.279 | ||
No | 1.00 | 1.00 | ||
Yes | 0.96 (0.95-0.98) | 1.01 (0.99-1.01) | ||
Sore throat | <0.001 | 0.143 | ||
No | 1.00 | 1.00 | ||
Yes | 1.04 (1.02-1.05) | 1.01 (0.99-1.03) | ||
Diarrhea | 0.796 | 0.576 | ||
No | 1.00 | 1.00 | ||
Yes | 0.99 (0.97-1.01) | 1.00 (0.99-1.03) | ||
headache | <0.001 | <0.001 | ||
No | 1.00 | 1.00 | ||
Yes | 1.02 (1.01-1.04) | 0.90 (0.88-0.92) | ||
Hospital internment | <0.001 | <0.001 | ||
No | 1.00 | 1.00 | ||
Yes | 4.99 (4.25-5.88) | 5.93 (4.51-7.79) |
Adjusted for variables belonging to hierarchical levels above with p-value <0.05, as well as for variables at the same level. Wald test.
Among comorbidities, level III variables, chronic cardiovascular disease (OR=1.13 – 95%CI 1.09-1.17) and diabetes mellitus (OR=1.07 – 95%CI 1.01-1.14) were more likely to perform the molecular test. Smoking, on the other hand, had the lowest chance of performing the test (OR=0.71 – 95%CI 0.67-0.75). At level IV, the variables of the clinical situation related to COVID-19, it is observed that characteristic symptoms of COVID-19 such as fever, difficulty breathing, runny nose, sore throat did not show statistical significance for performing the molecular test. Cough (OR=0.95 – 95%CI 0.92-0.97) and headache (OR=0.90 – 95%CI 0.88;0.92) had the lowest odds of having already been hospitalized for COVID-19. 19 (OR=1.50 – 95%CI 1.43;1.58) had the highest chance of having performed the molecular test for the diagnosis of the disease ( table 3 ).
DISCUSSION
Social, economic, contextual factors and the risk of disease aggravation were associated with carrying out the molecular test for COVID-19 in the state of Espírito Santo. Elderly, more than 12 years of study, health professional, chronic cardiovascular disease, diabetes mellitus and hospitalization were positively associated with the performance of the molecular test. Black and yellow skin color, residing in the northern health region and the homeless population were negatively associated with carrying out the molecular test. Therefore, the data found in this study demonstrate that the social determinants of health are not only associated with transmission, hospitalization and deaths from COVID-19, as well as with access to and performance of tests for diagnosing the disease16 - 19 .
The research was based on secondary data, subject to filling errors, despite the availability of guidelines for filling in the notification forms. The exclusion of the population that performed other diagnostic methods from the study was due to the study period. Between September 11, 2020 and March 2, 2021, the state of Espírito Santo determined that all COVID-19 suspects should be tested using the molecular method, with no other diagnostic test methods provided by the Unified Health System12 , 13 .
To minimize these occurrences, hierarchical logistic regression analysis was performed only with individuals with full completeness of all variables. The exclusion of incomplete forms may have generated information and sample selection bias. This fact may have increased the decrease or increase in the prediction of some variables in the model. As the notification sheets were not identified, it was not possible to identify duplicate sheets.
Older individuals were more likely to undergo the molecular test for COVID-19 and this result may be linked to the prioritization of access to care and laboratory diagnoses. This prioritization can be a measure to reduce the rates of hospitalizations and deaths in this group. Adults and the elderly have the highest risk of worsening and death, as demonstrated in cross-sectional studies carried out in Europe and Brazil16 , 19 , 20 . A cross-sectional study carried out in 2020 in Italy describes that aging is a risk factor for the development of morbidities and thus greater susceptibility and less resistance to infectious diseases such as COVID-19, particularly individuals over 65 years of age17 .
Regarding the skin color variable, it is believed that the result found in our study may be related to this self-declared black/brown population having less access to health services conditioned to low economic power and education in Brazil18 , 21 , 22 .
In several countries, black skin color was associated with a higher risk of transmission, hospitalization and death from COVID-1922 . A study carried out in the United States described that the transmission rate is three times higher in predominantly black counties, while the mortality rate is six times higher in these counties7 . In England, the black population had a 3.35 higher risk of being infected with the COVID-19 virus and being the most likely to be hospitalized9 . Therefore, other culturally structured factors may contribute to the vulnerability of the black race to COVID-19 outcomes.
The homeless population was less likely to perform the molecular test for COVID-19. The homeless population is more vulnerable to COVID-19 infection and difficulties in accessing diagnostic tests in developed and developing countries7 - 9 . This result is linked to socioeconomic factors, since homeless individuals are exposed to extreme poverty and have difficulty accessing the public health system. Living on the streets puts the individual in front of different circumstances that can lead to illness, being more frequent in the pandemic period, in addition to prejudice and social exclusion22 , 23 .
People residing in the metropolitan health region of the state of Espírito Santo had greater access to the molecular test when compared to residents of other regions. This data may be related to the fact that the first cases appeared in large centers and after some period the virus internalized24 . Large regions and metropolises have income concentration and more complex and specialized health services that can provide a greater supply of laboratories that perform molecular tests and logistical support for sample collection to perform the test25 .
An ecological study carried out in 2020 with secondary data from 50 countries observed that regions with low and medium income have greater difficulty in carrying out tests because they do not have logistics and specialized laboratories for this, having a low testing rate26 . Therefore, the northern region of the state of Espírito Santo is justified for presenting the lowest chance, since it is located far from the reference laboratory, as well as little infrastructure and logistics for carrying out the test.
Health professionals were more likely to perform the test. During the pandemic, it is health professionals who are directly exposed to individuals positive for COVID-19. Therefore, there is a need to make adequate tests available for timely diagnosis in order to interrupt the virus transmission chain27 , 28 .
In the state of Espírito Santo, in a cross-sectional study that analyzed the factors associated with hospitalization and death due to COVID-19 between February 28, 2020 and September 1, 2020, a prevalence of comorbidity was 2.66 times higher among hospitalized patients. and 3.63 times higher among deaths29 . Individuals with comorbidities were the majority among those admitted in March 2020 to a hospital in Saudi Arabia30 . Although comorbidities increase the chances of worsening and death of the disease, our study only cardiovascular diseases and diabetes mellitus showed differences in whether or not to perform the molecular test for COVID-19.
Hospital environments had to resort to adaptations and adaptations due to the COVID-19 pandemic and its demands, such as mass testing. The high percentage of patients with comorbidities and the elderly admitted to hospitals require frequent testing because this group has a higher risk of severe respiratory disease and the risk of local transmission29 , 31 . Because of this, these environments have more access for sample acquisition, device preparation and operation, and thus, greater chances of performing the molecular test.
Several social determinants have effects on the outcomes of the COVID-19 pandemic. Thus, the theme should be one of the research priorities in the pandemic. Studies with the objective of minimizing health inequalities, with efforts to guarantee access to diagnosis for the entire population and to implement policies for access to diagnostic tests aimed at the most vulnerable population, can reduce the negative effects of the pandemic in Brazil.
One of the strong points of the study is the sample size, allowing statistical power to capture the differences between the groups. In addition, data were extracted from the electronic panel for COVID 19, which provides open data in real time and with the quality of data already evaluated in other previously published studies32 .
To the best of our knowledge, this is the only Brazilian study that studied the factors associated with carrying out molecular tests for the diagnosis of COVID-19, in the context of a single health system, in a country with great social inequalities. The data obtained expose the most vulnerable groups that found it difficult to access laboratory diagnosis.
CONCLUSION
White skin color, higher education, elderly, residing in regions with greater structure and logistics for molecular test collection, health professionals, patients with chronic cardiovascular disease, diabetes mellitus and hospitalization were more likely to undergo molecular testing. Actions that guarantee access to molecular testing in the SUS for all suspects of COVID-19 are necessary, especially for the most vulnerable population.
Table 1 : Distribution of the frequency of molecular diagnosis for COVID-19 by sociodemographic variables, Espírito Santo, September 11, 2020 to March 2, 2021
Variables | Performance of molecular diagnosis for COVID-19 | |
---|---|---|
Yes N (%) | No N (%) | |
Sex | ||
Feminine | 195.219 (57.55) | 43.810 (55.87) |
Masculine | 143.968 (42.45) | 34.606 (44.13) |
Skin color | ||
White | 103.083 (39.47) | 19.783 (31.52) |
black | 20.244 (7.75) | 5.383 (8.58) |
brown | 119.138 (45.62) | 31.451 (50.11) |
Yellow | 18.262 (6.99) | 5.644 (8.99) |
Indigenous | 452 (0.17) | 507 (0.81) |
Age (Lifecycle) | ||
Child | 18.556 (5.47) | 10.152 (12.94) |
Adolescent | 25.838 (7.62) | 7.914 (10.09) |
Adult | 254.616 (75.05) | 53.151 (67.76) |
Elderly | 40.482 (11.87) | 7.226 (9.21) |
Education (years) | ||
0 | 15.432 (6.96) | 6.681 (12.71) |
1-4 | 18.900 (8.52) | 5.343 (10.16) |
5-8 | 36.325 (16.38) | 9.789 (18.62) |
9-12 | 97.947 (44.18) | 22.002 (41.85) |
> 12 | 53.120 (23.96) | 8.762 (16.67) |
Health Region | ||
Metropolitan | 244.930 (72.19) | 50.993 (65.00) |
South | 49.158 (14.49) | 7.024 (8.95) |
Central | 29.975 (8.83) | 12.133 (15.47) |
North | 15.215 (4.48) | 8.301 (10.58) |
Street population | ||
No | 337.354 (99.43) | 77.888 (99.28) |
Yes | 1.924 (0.57) | 563 (0.72) |
Health professional | ||
No | 294.173 (93.84) | 70.216 (96.04) |
Yes | 2.895 (3.96) | 19.294 (6.16) |
Disabled person | ||
No | 335.475 (98.88) | 77.536 (98.83) |
Yes | 3.803 (1.12) | 915 (1.17) |
Table 2 Distribution of frequency of carrying out molecular diagnosis for COVID-19 by clinical variables, Espírito Santo, September 11, 2020 to March 2, 2021
Variables | Performance of molecular diagnosis for COVID-19 | |
---|---|---|
Yes N (%) | No N (%) | |
chronic cardiovascular disease | ||
No | 298.642 (88.04) | 70.601 (90.00) |
Yes | 40.576 (11.96) | 7.845 (10.00) |
chronic lung disease | ||
No | 328.254 (96.77) | 75.456 (96.21) |
Yes | 10.954 (3.23) | 2.970 (3.79) |
chronic kidney disease | ||
No | 338.149 (99.68) | 78.248 (99.75) |
Yes | 1.085 (0.32) | 199 (0.25) |
diabetes mellitus | ||
No | 325.186 (95.86) | 75.802 (96.63) |
Yes | 14.034 (4.14) | 2.643 (3.37) |
Smoking | ||
No | 331.380 (97.69) | 76.190 (97.13) |
Yes | 7.840 (2.31) | 2.255 (2.87) |
Obesity | ||
No | 332.543 (98.11) | 76.902 (98.04) |
Yes | 6.420 (1.89) | 1.534 (1.96) |
Fever | ||
No | 212.936 (62.77) | 47.868 (61.02) |
Yes | 126.276 (37.23) | 30.574 (38.98) |
Cough | ||
No | 150.714 (44.43) | 34.203 (43.60) |
Yes | 188.526 (55.57) | 44.244 (56.40) |
breathing difficulty | ||
No | 290.109 (85.52) | 67.191 (85.65) |
Yes | 49.137 (14.48) | 11.256 (14.35) |
runny nose | ||
No | 193.454 (57.03) | 44.121 (56.24) |
Yes | 145.783 (42.97) | 34.327 (43.76) |
Sore throat | ||
No | 215.024 (63.39) | 50.430 (64.30) |
Yes | 124.187 (36.61) | 27.997 (35.70) |
Diarrhea | ||
No | 282.636 (83.32) | 65.329 (83.28) |
Yes | 56.598 (16.68) | 13.118 (16.72) |
Headache | ||
No | 157.396 (46.40) | 36.931 (47.09) |
Yes | 181.813 (53.60) | 41.497 (52.91) |
Hospital internment | ||
No | 335.995 (99.03) | 78.298 (99.80) |
Yes | 3.283 (0.97) | 153 (0.20) |