NCCR 2020: Conference Of Very Important Disease (COVID-19) | 24 - 26 August 2020 Young Investigator Awards Presentation Wan Shakira Bt Rodzlan Hasani (Institute for Public Health, NIH) https://doi.org/10.5281/zenodo.4004583

1. Comorbidities and Clinical
Features Related to Invasive
Ventilatory Support among COVID-
19 cases in Selangor, Malaysia
Wan Shakira Bt Rodzlan Hasani
(Institute for Public Health, NIH)
Poster No: P16

2. INTRODUCTION
• Coronavirus disease 2019 (COVID-19) is an infectious disease
caused by a Severe Acute Respiratory Syndrome Coronavirus 2
(SARS-CoV-2).
• COVID-19 is the third coronavirus infection that spread
extensively after Severe Acute Respiratory Syndrome (SARS)
and Middle East Respiratory Syndrome (MERS)(1)
• On March 11, 2020, the World Health Organization declared
COVID-19 a pandemic (2).
• Malaysia has also not been spared from the pandemic with a
total of 4,987 infected people and 82 deaths up to April 14,
2020 (3).

3. INTRODUCTION
• With the increasing number of confirmed cases and escalating
number of fatalities owing to COVID-19, the underlying
comorbidities have generated considerable concern.
• A number of studies have shown that underlying comorbidities are
predictors of severe disease outcome and greatly affect the
prognosis of the COVID-19 patients (4-6).
• COVID-19 causes severe acute respiratory syndrome and is often
associated with intensive care unit (ICU) admission and subsequent
mortality.
• In China, about 15% of the patients developed severe pneumonia,
and about 6% needed non-invasive or invasive ventilatory support
(7).
• Identifying the risk factors that predicts severity and outcome of
COVID-19 patients early in the presentation would be extremely
helpful for clinicians in managing the patients.

4. OBJECTIVE
• This study aimed to describe the proportion of
non-communicable disease (NCD) comorbidities
and clinical presentations, and to determine
their risk with the need for invasive mechanical
ventilator support (intubation) among COVID-19
positive cases in Selangor, Malaysia.

5. METHODOLOGY
• Study design
• This is a retrospective study using data collected during COVID-19
outbreak in Selangor, Malaysia.
• Study population
• We recruited all laboratory confirmed positive COVID-19 cases
reported in the state of Selangor, Malaysia.
• The case that were notified up to 13th April 2020 were included
into this study.
• A positive case of COVID-19 is confirmed based on positive
Nasopharyngeal Swab and Reverse Transcriptase-Polymerase
Chain Reaction (RT-PCR) testing.

6. METHODOLOGY
• Measures
• The outcome variable was ICU admission that required intubation
with mechanical ventilatory support.
• Predictor variables included socio demographic characteristic,
commorbidities such as history of having hypertension, diabetes,
heart disease, chronic respiratory disease, cancer, and kidney disease
and also main symptoms of COVID-19.
• Data collection technique
• Positive cases are informed to the District Health Office. Case
investigation was carried out by the officers in the District Health
Office, with all case details informed to the State Health Department
in the form of a standard linelist and case investigation report.
• During this COVID-19 outbreak, the Selangor State Health
Department was assisted by officers from the National Institutes of
Health Malaysia on data management and analysis.
• All cases and data reported were cleaned, and any discrepancy
verified with the ground staff from the district health offices, to
ensure data accuracy and quality data was captured.

7. METHODOLOGY
• Data analysis
• All categorical data was reported in frequency and
percentage and continuous data was presented in
mean and SD
• Multiple logistic regression analysis was performed to
identify the factors associated with intubation among
COVID-19 cases
• Multicollinearity problems and all possible two way
interaction terms were checked one by one together
with main effect. Model fitness using Goodness of fit
statistics was used to assess the fit of the regression
model against the actual outcomes.

8. Results
• A total of 1,287 COVID-19 positive cases were included in the
analysis.

9. Table 1: Socio-demographic, Comorbidities and clinical presentation characteristics of
COVID-19 Positive Cases in Selangor (N=1287)
Characteristics COVID-19 Positive Cases
Sex, n (%)
Male 750 (58.3)
Female 537(41.7)
Age (years)
Median (IQR) 36.0 (30.0)
Mean (SD) 38.8 (18.2)
Age groups, n (%)
<18 years 116 (9.0)
18-29 years 366 (28.4)
30-39 years 239 (18.6)
40-49 years 151 (11.7)
50-59 years 214 (16.6)
60 years and above 201 (15.6)
Ethnicity, n (%)
Malay 952 (74.0)
Chinese 118 (9.2)
Indian 43 (3.3)
Others 174 (13.5)

10. Characteristics COVID-19 Positive Cases
Nationality, n (%)
Malaysian 1122 (87.2)
Non Malaysian 165 (12.8)
Comorbidities, n (%)
Hypertension 200 (15.5)
Diabetes 141 (11.0)
Heart disease /problem 50 (3.9)
Chronic respiratory disease 40 (3.1)
Chronic kidney disease 18 (1.4)
Cancer 7 (0.5)
Current smoker 57 (4.4)
Symptoms, n (%)
Fever 564 (43.8)
Cough 477 (37.1)
Lethargy 78 (6.1)
Dyspnoea 71 (5.5)
Headache 71 (5.5)
Myalgia 53 (4.1)
Diarrhoea 41 (3.3)
Arthralgia 31 (2.4)
Status Hospital Admission, n (%)
Intubated (Invasive ventilator support) 25 (1.9)
Non Intubated 1262 (98.1)

11. Table2:ProportionofIntubatedcasesofCOVID-19bysociodemographic,NCDcomorbidities
andclinicalpresentation
Variables
Intubated (Invasive
Mechanical Ventilation)
(n=25)
Not Intubated
(n=1262)
Sex, n (%)
Male 18 (72.9) 732 (58.0)
Female 7 (28.0) 530 (42.0)
Age groups, n (%)
<60 years 11 (44.0) 1075 (85.2)
60 years and above 14 (56.0) 187 (14.8)
Comorbidities, n (%)
Hypertension 17 (68.0) 183 (14.5)
Diabetes 10 (40.0) 131 (10.4)
Heart disease 4 (16.0) 46 (3.6)
Chronic respiratory
disease
0 (0.0) 40 (3.2)
Chronic kidney disease 3 (12.0) 15 (1.2)
Cancer 0 (0.0) 7 (0.6)
Current smoker 1 (4.0) 56 (4.4)

12. Variables
Intubated (Invasive
Mechanical Ventilation)
(n=25)
Not Intubated
(n=1262)
Symptoms, n (%)
Fever 22 (88.0) 542 (42.9)
Cough 14 (56.0) 463 (36.7)
Lethargy 11 (44.0) 67 (5.3)
Dyspnoea 10 (40.0) 61 (4.8)
Diarrhoea 3 (12.0) 38 (3.0)
Arthralgia 1 (4.0) 30 (2.4)
Myalgia 1 (4.0) 52 (4.1)
Headache 0 (0.0) 71 (5.6)
Table2:ProportionofIntubatedcasesofCOVID-19bysociodemographic,NCDcomorbidities
andclinicalpresentation

13. Table3:FactorsassociatedwithintubationamongpositivecaseCOVID-19casesusingbinary
logisticregressionmodel(n=1287)
Risk factors
Simple Logistic Regression (SLR) Multiple Logistic regression (MLR)
b
Crude OR
(95 % CI)
p-Value b
Adjusted OR*
(95 % CI)
p-Value
Sex
Male 1 1
Female -0.62 0.54 (0.22, 1.30) 0.166 -0.21 0.82 (0.30, 2.22) 0.689
Age group
< 60 years 1 1
≥ 60 years 1.99 7.32 (3.27, 16. 36) <0.001 1.36 3.90 (1.41, 10.80) 0.009
Hypertension
No 1 1
Yes 2.53 12.53 (5.33, 29.46) <0.001 1.74 5.72 (1.99, 16.45) 0.001
Diabetes
No 1 1
Yes 1.75 5.76 (2.53, 13.07) <0.001 0.06 1.06 (0.35, 3.23) 0.914

14. Risk factors
Simple Logistic Regression (SLR) Multiple Logistic regression (MLR)
b
Crude OR
(95 % CI)
p-Value b
Adjusted OR*
(95 % CI)
p-
Value
Heart Disease
No 1 1
Yes 1.62 5.04 (1.66, 15.26) 0.004 -0.18 0.84 (0.22, 3.23) 0.796
Chronic Kidney
Disease
No 1 1
Yes 2.43
11.34 (3.06,
41.99)
<0.001 1.19 3.30 (0.62, 17.50) 0.161
Current
smoker
No 1 1
Yes -0.11 0.90 (0.12, 6.75) 0.916 -1.32 0.27 (0.02, 3.34) 0.307
Fever at
presentation
No 1 1
Yes 2.28 9.74 (2.90, 32.72) <0.001 2.29 9.83 (2.48, 38.95) 0.001
Cough at
presentation
No 1 1 -
Yes 0.787 2.20 (0.99, 4.88) 0.053 -0.21 0.81 (0.31, 2.13) 0.672

15. *Backward LR Multiple Logistic regression was applied. Multicollinearity and interactions were checked
and not found. Hosmer Lameshow test P value = 0.951, Classification Table (overall correcly classified
percentage = 98.2%) and ROC curve (area under ROC curve=94.6 %) were accepted to check model
fitness.
Risk factors
Simple Logistic Regression (SLR) Multiple Logistic regression (MLR)
b
Crude OR
(95 % CI)
p-Value b
Adjusted OR*
(95 % CI)
p-Value
Dyspnoea at
presentation
No 1 1
Yes 2.58 13.13 (5.66, 30.42) <0.001 2.26 9.61 (3.31, 27.96) <0.001
Lethargy at
presentation
No 1 1
Yes 2.64 14.01 (6.13, 32.05) <0.001 2.07 7.92 (2.84, 22.09) <0.001
Diarrhoea at
presentation
No 1 1
Yes 1.48 4.39 (1.26, 15.31) 0.020 0.15 1.16 (0.24, 5.51) 0.853

16. Discussion
• Comorbidities and clinical presentation of COVID-19 patients
• Our study demonstrated that underlying hypertension and diabetes
were the most common comorbidities among COVID-19 cases and it
was consistent with the finding on the clinical features of COVID-19 in
Wuhan(4).
• Bornstein et al., (2020) also reported that hypertension and types II
diabetes were the most common comorbidities in patients with
coronavirus infection (8).
• In addition, diabetes and hypertension have also been reported as the
most common comorbidities for other coronavirus infections such as
SARS and MERS-CoV (9).
• Consistent with other studies, the most common presenting symptoms
in this study were fever followed by cough, dyspnoea and lethargy (10-
14).

17. Discussion
Factor associated with intubation
• Older Age
• Older age with underlying comorbidities has been predictors of poor
outcome in viral infections (15-16).
• Our regression model showed that the odds of being intubated was
3.9 times higher among older adults aged 60 years and above.
• Similar to the reports from China & Italy, the risk for poor prognosis
is higher in older age groups (17-18).
• Hypertension
• Patients with underlying hypertension also had 5.7 times the odds
of being intubated.
• Systematic review and meta-analysis done by Jing Yang et al. (2020)
showed that the pool odds of hypertension in severe patients
compared to non-severe patients was 2.36 (95% CI: 1.46-3.83) (19).

18. Discussion
• Clinical presentation (symptoms)
• Our finding indicates that symptomatic COVID-19 patients with fever,
dyspnoea and lethargy had strong significant associations with the
risk for intubation.
• A study done by Li et al., (2020) demonstrated significant differences
in clinical symptoms between patients with or without severe/critical
COVID-19 after controlling for age and comorbidities (20)
• This finding is very important for clinicians in risk-stratifying their
patients based on presenting symptoms

19. Conclusion
• COVID-19 patients >=60 years old, who had hypertension, or
who presented with fever, dyspnoea, or lethargy, were more
likely to be intubated and ventilated.
• These patients need to be screened for COVID-19 when
presented to any healthcare facility and monitored closely by
clinicians upon diagnosis and admission.
• In addition, public health interventions should aim to provide
additional protection to older population or people with
comorbidity such as hypertension found to be more
vulnerable to severe disease progression if infected with
COVID-19.

20. References
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