ARTICLEOpen Access

Characteristics and Scoring Model of COVID-19 Severity Predictor in Obstetric and Gynecology Doctors in Indonesia

Sutrisno Sutrisno

Obstetric and Gynecology Department Faculty of Medicine Brawijaya University Indonesia

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Wening Hapsari

https://orcid.org/0000-0002-0024-2590

Brawijaya University Faculty of Medicine, Universitas Brawijaya Fakultas Kedokteran, Indonesia

E-mail Address: weninghapsari113@gmail.com

Corresponding author: Dr. Wening Hapsari, General Practitioner, Joyo Grand Street L106, Malang East Java Indonesia 65144.

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https://doi.org/10.1142/S2661318222500025Cited by:0 (Source: Crossref)

Abstract

Background: Obstetrician and gynecologist are one of the contributors in patient care who are susceptible to contracting coronavirus-19 infection. Emergency measures for maternal field are high, while gold standard examination for COVID-19 takes long time with false negative rate. The case fatality rate of COVID-19 among health workers in Indonesia is reported to be high. We want to know epidemiological, clinical, and occupational characteristics of various degrees of COVID-19 severity and create scoring model to predict COVID-19 severity in ob/gyn doctors in Indonesia.

Method: This is a descriptive analytic study using a cross-sectional approach. Consecutive sampling was taken from ob/gyn doctors infected with COVID-19 and analyses used were Chi-Square and Mann-Whitney U tests. A scoring model is created and using receiver operating characteristic (ROC) curves, to determine the predictive ability of the scoring model and the cutoff value to COVID-19 severity, then tested for sensitivity and specificity.

Result: The mean age of the respondents was 38.2 ± 9.8 and 48.7% were male. Sixty-one percent respondents experienced mild symptoms, infected while on duty (46.1%), and 59% had nuclear family member infected with COVID-19. Age group ( $p$ = 0.000), number of infection ( $p$ = 0.000), vaccination status ( $p$ = 0.010), comorbidities ( $p$ = 0.023), and working hours ( $p$ = 0.002) were significantly different on the COVID-19 severity. Area-under-curve of scoring model was 75.2% and 93.4%. The cutoff value was 10.5 points for between asymptomatic and mild degree (sensitivity 54.2% and specificity 77.8%) and 12.5 points between mild and moderate degree (sensitivity 83.3% and specificity 95.8%) respectively.

Conclusion: The developed scoring model can facilitate prediction of COVID-19 severity in ob/gyn doctors, with asymptomatic (score of < 10.5 points), mild degree (score of 10.5–12.5 points), and moderate degree (score of > 12.5 points).

Keywords:

INTRODUCTION

COVID-19 is a disease caused by a new type of coronavirus, namely SARS-CoV-2, which was first discovered in Wuhan, China, at the end of 2019 (Wang et al., 2020b). This RNA virus has a positive single strain, is encapsulated, and unsegmented (Wang et al., 2020b; Xu et al., 2019). The incubation period of this virus is 2–14 days (4 days on average) (Peretto et al., 2020). This virus can cause acute respiratory symptoms such as fever, cough, shortness of breath, and can be accompanied by weakness, muscle aches, and diarrhea.

COVID-19 has spread to various countries such as Thailand, Japan, Republic of Korea, Vietnam, Germany, United States, Singapore, and Indonesia. By August 13, 2020, 20,162,474 cases were reported with 737,417 deaths (World Health Organization, 2021). In Indonesia, confirmed cases have reached 130,718 with 5,903 deaths (World Health Organization, 2021).

In the United States, a country with high rates of COVID-19 infection, there is relatively low prevalence of SARS-CoV-2 infection in pregnant women undergoing universal screening on admission to hospital for delivery (Sutton et al., 2020). Universal screening was performed by nasopharyngeal swab and quantitative polymerase chain reaction (PCR) assays to detect SARS-CoV-2 infection. Most patients who tested positive for SARS-CoV-2 during delivery were asymptomatic (Sutton et al., 2020). This underlines the risk of COVID-19 among asymptomatic obstetric patients. The actual prevalence of COVID-19 infection in pregnant women may go unreported due to a high number of false negatives (Strunk et al., 2014). Considering that there are so many emergency measures in obstetrics and gynecology, diagnosing COVID-19 is a huge challenge and of course this becomes a concern as we do not want to put health workers at risk of exposure.

More than 22,000 health workers in the world have been infected with COVID-19 (World Health Organization, 2021). This number may not represent the actual number of COVID-19 cases among health workers due to the absence of a systematic reporting system to WHO. COVID-19 infections in health workers that have been reported in China and Italy reached 4.4% and 11%, respectively (World Health Organization, 2021). The Centers for Disease Control and Prevention (CDC) reports that 19% of COVID-19 patients in the United States are health workers (Burrer et al., 2020). The findings in Saudi Arabia show that the risk of COVID-19 infection is 10 times higher in health workers at tertiary hospitals, compared to patients in the same hospitals (Misra-Hebert et al., 2020). A meta-analysis found that the risk of COVID-19 infection in health workers was 1.4 to 12 times higher (Misra-Hebert et al., 2020).

Protecting health workers to minimize the risk of infection is fundamental. Various policies should be considered to control the spread of infection to health workers. The initial step is to identify the factors associated with severity (Zhang et al., 2020). There is not enough published data regarding epidemiological, clinical, and occupational characteristics, or factors associated with COVID-19 severity in ob/gyn doctors in Indonesia.

The purpose of this study was to know the epidemiological, clinical, and occupational characteristics of various degrees of COVID-19 severity and to create a scoring model of related characteristics to predict COVID-19 severity.

METHODS

Study setting and participants

This research is a descriptive analytic study using cross-sectional approach conducted in Malang, Indonesia, a developing country with the highest number of case fatality rates in health workers in Southeast Asia according to the Indonesian Doctors Association. We used consecutive sampling method via online questionnaire to ob/gyn doctors diagnosed with COVID-19 from January to July 2021 who had consented their participation for this research. The diagnosis of COVID-19 was made by RT-PCR test from nasopharyngeal/oropharyngeal swabs. The severity of COVID-19 is based on the WHO COVID-19 guidelines (asymptomatic, mild, moderate, severe, critical). The flow chart of this research is presented in Fig. 1.

Statistical analysis

Data were analyzed using SPSS version 26. Numerical data was presented using mean and standard deviation. Nominal data is presented in frequency and percentage. Comparative statistical analyses used were Chi-Square and Mann-Whitney tests to assess variables that are significantly different among various degree of COVID-19 severity. A predictor scoring model was created and its predictive ability was measured by ROC curves. A two-sided $P < 0.05$ was considered statistically significant. Determination of the cutoff value from the scoring model to various degrees of COVID-19 severity in this study was carried out, then tested for sensitivity and specificity.

RESULTS

Epidemiological, clinical, and work related characteristics of respondents

Out of the 40 respondents, 39 respondents were eligible for inclusion in this study. Characteristics of the respondents are presented in Table 1. The mean age of all respondents is $38.2 \pm 9.8$ years old. Twenty respondents (51.3%) were female and 19 respondents (48.7%) were male. Twenty-five respondents (64.1%) have completed COVID-19 vaccination, 12 respondents (30.8%) have not received COVID-19 vaccine, two other respondents (5.1%) have taken 3rd vaccine booster, and no respondent received single dose of COVID-19 vaccine in our study when questionnaire were taken. The majority of respondents (84.6%) in this study had their first COVID-19 infection. Twenty-three respondents (59.0%) also had family members infected with COVID-19. Eighteen respondents (46.2%) were infected while on duty (in outpatient clinic, ward, labor and delivery room, and operating room), 10 respondents (25.6%) were infected outside the hospital, and 11 respondents (28.2%) did not know for sure the source of the infection.

**Table 1. Epidemiological, clinical, and occupational characteristics.**

Twenty-two respondents (56.4%) were board-certified Obstetrician & Gynecologist and 17 respondents (43.6%) were ob/gyn residents. The majority of respondents (74.4%) worked in the COVID-19 isolation hospital. Seven respondents (17.9%) worked less than 20 hours per week, 22 respondents (56%) worked 20–40 hours per week, and 10 respondents (25.6%) work more than 40 hours/week. In this study, some respondents might perform delivery more than one kind of medical procedure; 92% of all respondents performed Cesarean section, 82.1% of all respondents assisted at vaginal, and 35.9% of all respondents performed laparotomy procedure. Respondents’ perception on the hospital they worked at were that they were good at fulfilling daily personal protective equipment (PPE) demands (97.4%), there were adequate COVID-19 facilities (71.8%) and there were clear and well-implemented protocols for handling COVID-19 (87.2%).

Comparison between personal characteristics and clinical COVID-19 severity

Table 2 illustrates comparison between respondents’ characteristics and clinical COVID-19. Age group ( $p = 0.000$ ), COVID-19 vaccination status ( $p = 0.010$ ), times of infection ( $p = 0.000$ ), comorbidities ( $p = 0.023$ ), and working hours ( $p = 0.002$ ) were associated with clinical COVID-19 severity.

**Table 2. Comparison of respondents’ characteristics with clinical COVID-19 severity.**
	Clinical severity
	Asymptomatic-mild		Moderate-severe
	Number	%	Number	%	p-value
Age groups (years)
21–30 years	8	20.5%	0	0%	0.000*
31–40 years	18	46.2%	1	2,60%
41–50 years	6	15.4%	0	0%
51–60 years	1	2.6%	4	10.3%
$> 60$ years	0	0%	1	2.6%
Sex
Male	18	46.2%	2	5.1%	0,235
Female	15	38.2%	4	10.3%
Blood type
O	12	30.8%	2	5.1%	0,143
B	9	23.1%	4	10.3%
A	9	23.1%	0	0%
AB	3	7.7%	0	0%
Rhesus
Negative (−)	1	2.6%	0	0%	0,462
Positive ( $+$ )	32	82.1%	6	15.4%
COVID-19 vaccination status
Booster ( $3 \times$ )	2	5.1%	0	0%	0.010*
Fully vaccinated ( $2 \times$ )	24	61.5%	1	2.6%
Not vaccinated	7	17.9%	5	12.8%
Times infected
$2 \times$	2	5.1%	4	10.3%	0.000*
$1 \times$	31	79.5%	2	5.1%
Comorbid
Absent	26	84,80%	2	5.1%	0.023*
Present	7	17.9%	4	10.3%
Working hours
$< 20$ hours/week	7	17.9%	0	0%	0.002*
20–40 hours/week	21	53.8%	1	2.6%
$> 40$ hours/week	5	12.8%	5	12.8%
Occupation
Resident Ob/Gyn	18	46.2%	4	10.3%	0,404
Obstetrician and Gynecologist	15	38.2%	2	5.1%
Work in isolation hospital
No	25	64.1%	4	10.3%	0,443
Yes	8	20.5%	2	5.1%
Perform laparotomy
No	21	53.8%	4	10.3%	0,615
Yes	12	30.8%	2	5.1%
Perform Cesarian section
No	3	7.7%	0	0%	0,306
Yes	30	76.9%	6	15.4%
Perform pervaginam labor
No	6	15.4%	1	2.6%	0,645
Yes	27	69.2%	5	12.8%

Meanwhile, there were no significant association between sex, blood type, blood rhesus, occupation, working in isolation hospital, and medical procedures performed with clinical COVID-19 severity ( $p > 0.05$ ). From this analysis, we created a simple scoring system model for the predictor factors for symptom severity in Table 3.

**Table 3. Scoring factor predictor of clinical severity of COVID-19.**
Variable	Categories	Score assigned
Age groups	21–30 yrs	1
	31–40 yrs	2
	41–50 yrs	3
	51–60 yrs	4
	$> 60$ yrs	5
Times infected	Twice	2
	Once	3
COVID-19 vaccination	Booster ( $3 \times$ )	1
	Fully vaccinated ( $2 \times$ )	2
	Not vaccinated	3
Comorbid	Absent	1
	Present	2
Working hours	$< 20$ hrs/week	1
	20–40 hrs/week	2
	$> 40$ hrs/week	3

We applied the scoring model to the 39 patients in this study. The ROC curve analysis in Fig. 2a shows an area under the curve (AUC) of 0.752 (95% CI 0.568–0.937 $p = 0.028$ ) indicating a useful discrimination between asymptomatic and mild group for our model. The second ROC curve analysis in Fig. 2b shows an AUC of 0.934 (95% CI 0.811–1.057) also indicating a useful discrimination between mild and moderate group. From statistical analysis, the cutoff value for asymptomatic and mild group is 10.5 points while for mild and moderate group is 12.5 points (see cutoff analysis in Fig. 3). We tested the scoring model for sensitivity and specificity with asymptomatic group ( $< 10.5$ points), mild group (10.5–12.5 points), and moderate group ( $> 12.5$ points) using cross-tabulation in Table 4.

Fig. 3. Determination of predictive severity score cutoff. (a) Cutoff score between asymptomatic and mild subjects (b) cutoff score between mild and moderate subjects.

**Table 4. Cross-tabulation predictive COVID-19 severity score with COVID-19 severity.**
Predictor COVID-19 severity score	COVID-19 severity
Predictor COVID-19 severity score	Mild	Asymptomatic	Total
$> 10.5$	13	2	15
$< 10.5$	11	7	18
Total	24	9	33
Sensitivity: 54.2%, Specificity: 77.8%, PPV: 88.67%, NPV: 38.9%, Odds ratio: 4.14, Accuracy: 60.6%
Predictor COVID-19 severity score	COVID-19 severity
Predictor COVID-19 severity score	Moderate	Mild	Total
$> 12.5$	5	2	6
$< 12.5$	1	23	24
Total	6	24	30
Sensitivity: 83.3%, Specificity: 95.8%, PPV: 83.33%, NPV: 95.8%, Odds ratio: 115.0, Accuracy: 93.3%

p value was obtained $\leq 0.05$ and statistically significant.

From Table 4 between asymptomatic and mild symptoms, it can be calculated that the sensitivity value is 54.2% and the specificity is 77.8%, while the PPV value is 88.67% and the NPV is 38.9%. The odds ratio value of this test is 4.14, so it can be seen that a score $> 10.5$ points is a predictor of mild COVID-19 occurrence. Meanwhile, between mild and moderate symptoms, the sensitivity value of 83.3% and specificity of 95.8% can be calculated, while the PPV value is 83.33% and the NPV is 95.8%. The odds ratio value of this test is 115, so it can be seen that a score $> 12.5$ points is a predictor of moderate COVID-19 occurrence.

DISCUSSION

Until now, there has not been enough published data on the epidemiological profile and the predictor score model for COVID-19 severity in general public, health workers, nor Obstetricians and Gynecologists in Indonesia.

In this study, the majority of patients with COVID-19 experienced asymptomatic to mild symptoms (84.6%). Lai et al. also reported that the majority of COVID-19 patients experienced mild to asymptomatic symptoms (Lai et al., 2020). This could be due to the relatively large proportion of young subjects in the study, while young age was associated with mild symptoms (Lai et al., 2020). Young healthcare workers with asymptomatic and mild degrees can be easily detected from tracing so they could get early treatment (Lai et al., 2020). Patients with moderate to critical symptoms are usually older, and more often have comorbidities (Ghweil et al., 2020).

In this study, the majority of respondents, Obstetricians and Gynecologists infected with COVID-19 did not have comorbidities (84.80%), but 66.6% of respondents in the moderate to severe symptom group had comorbidities. In this study comorbidity was associated with COVID-19 severity with p-value of 0.023. Wang et al. reported findings from 138 cases of COVID-19; showed that 64 COVID-19 cases (46.4%) had comorbidities and subjects admitted to the ICU had a higher number of comorbidities (72.2%) compared to those not admitted to the ICU (37.3%) (Wang et al., 2020a). This suggests that comorbidity may be a risk factor for poor outcome (Wang et al., 2020a). Assessing the prevalence of chronic disease is the basis for reducing complications in patients infected with SARS-CoV-2.

Vaccines can protect the public and health workers from contracting the COVID-19 virus. In this study, 83.3% of obstetricians with moderate-severe COVID-19 symptoms were not vaccinated against COVID-19. There is an association between vaccination status and severity of COVID-19 in our study with a p-value of 0.010. A number of SARS-CoV-2 vaccines have shown efficacy in large-scale phase 3 trials. Most vaccines use the SARS-CoV-2 surface spike glycoprotein as the primary antigenic target for the generation of binding and neutralizing antibodies and T cells, and use an antigen-coding sequence based on the originally identified Wuhan lineage virus (GenBank access number M908947). Vaccination is a key component of future disease control.

In our study, it was found that long working hours (more than 40 hours/week) were associated with a higher degree of severity of COVID-19 symptoms. Ran et al. (2020) and Mhango et al. (2020) reported similar findings. This can be possible due to lack of rest time, length of contact with infected patients, gathering with colleagues without PPE to eat or chat, as well as difficulties in properly wearing full PPE for long periods of time. Changes in the daily schedule to shorten shift duration and reduce daily working hours may be necessary (Schwartz et al., 2020).

The application of this scoring model can facilitate the screening/evaluation of ob/gyn doctors for risk stratification of the clinical manifestations of COVID-19. AUC of scoring model was 75.2% and 93.4%. The cutoff value was 10.5 points for between asymptomatic and mild degree (sensitivity 54.2% and specificity 77.8%) and 12.5 points between mild and moderate degree (sensitivity 83.3% and specificity 95.8%) respectively. Currently, there is no specific scoring system for this.

CONCLUSION

This report determines the factors associated with the severity of COVID-19 in Obstetricians and Gynecologists in Indonesia and possibly several other countries. Nine (23.1%) obstetricians and gynecologists had asymptomatic COVID-19, 24 (61.5%) mild symptoms, and 6 (15.4%) moderate symptoms. Age, vaccination status, reinfection, comorbidities, and working hours are factors that differ significantly in varying degrees of COVID-19 severity.

The developed scoring model can facilitate prediction of COVID-19 severity in ob/gyn doctors, with asymptomatic (score of $< 10.5$ points), mild degree (score of 10.5–12.5 points) and moderate degree (score of $> 12.5$ points). Overall, this scoring system is acceptable, showing moderate discriminatory power and is a tool that can potentially be used as a predictor of COVID-19 severity in ob/gyn doctors.

Certain measures should be followed to protect ob/gyn doctors from infection and higher COVID-19 severity by excluding ob/gyn doctors with older age and comorbidities from working in high risk areas and making sure all ob/gyn doctors are vaccinated when there is no contraindication. The working hours of ob/gyn doctors in isolation hospitals should also be reduced.

LIMITATION

Given that this was a retrospective and single-center study with a small sample, we included all subjects in the data analysis without calculating the sample size first. The ordinal variables between the asymptomatic-mild group and the moderate group were compared with the Chi-Square and Mann-Whitney U tests so as to reduce the power of statistical analysis.

We did not have subjects with severe-critical symptoms, because the sampling was done by self-reporting via questionnaire. We could not include doctors who died from COVID-19, so this study is not representative for all types of COVID-19 severity.

A more in-depth analysis is needed regarding the scoring model made, especially with its accuracy. There is a high possibility of overfitting in our COVID-19 severity prediction scoring model, so a prospective cohort study is needed to further confirm the reliability of this scoring model, as well as to create a new predictive scoring model for its future application.

CONFLICT OF INTEREST

The authors declare that there is no conflict of interest.

ACKNOWLEDGEMENT

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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Vol. 04, No. 01

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Received 27 October 2021

Accepted 25 January 2022

Published: 8 April 2022

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This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 (CC BY-NC-ND) License which permits use, distribution and reproduction, provided that the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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