ORIGINAL ARTICLE
Bali Medical Journal (Bali MedJ) 2026.
Volume 15.
Number 1: 67-73 P-ISSN.
E-ISSN: 2302-2914
Clinical and laboratory findings in type 2 diabetes mellitus with COVID-19 infection: a single centre study Abdulrahman Saad Alfaiz1* ABSTRACT Introduction: The coexistence of type 2 diabetes mellitus (T2DM) with coronavirus disease 2019 (COVID-.
poses a major global healthcare concern.
Even though both have become significant worldwide health issues, little is still known about how they interact in this region of the world.
The purpose of this study is to examine the laboratory markers and clinical features of COVID-19-infected individuals with T2DM.
Methods: The medical records of hospitalized T2DM patients with proven COVID-19 infection at the Prince Mohammed Bin Abdulaziz Hospital (PMAH) in Riyadh.
Saudi Arabia, between March 15, 2020, and July 15, 2020, were examined in this single-center retrospective analysis.
Laboratory, clinical, and demographic data were collected and examined.
The relationships between different demographic traits and T2DM with COVID-19 infection were evaluated using the Fisher Exact test, binary logistic regression, and odds ratio (OR).
The quantitative factors between individuals with type 2 diabetes and those without the disease were compared using the Mann-Whitney U test.
A P value of less than 0.
05 was deemed significant.
Results: About 142 .
4%) of the 239 patients had type 2 diabetes, and they were substantially older .
A P < 0.
than those without the disease.
Among T2DM patients, cough (P = 0.
, tachypnea (P = 0.
and dyspnea (P = 0.
were significant symptoms.
Among T2DM patients, hypertension (P = 0.
and hyperlipidemia (P = 0.
were common comorbidities.
Patients with type 2 diabetes had substantially higher levels of creatinine (P = 0.
, blood urea nitrogen (P = 0.
LDH (P = 0.
CRP (P = 0.
, and fibrinogen (P = 0.
Tachypnea .
OR = 3.
P = 0.
and dyspnea .
OR = 3.
P = 0.
demonstrated statistical significance on binary logistic regression analysis.
In both bivariate analysis and logistic regression, hypertension .
OR = 2.
P = 0.
and dyslipidemia .
OR = 12.
P =
maintained statistical significance.
Conclusion: Significantly higher laboratory and inflammatory values are seen in T2DM with COVID-19, underscoring the significance of targeted treatment approaches and resource allocation.
Department of Internal Medicine.
College of Medicine.
Shaqra University.
Riyadh.
Saudi Arabia *Corresponding email:
Abdulrahman Saad Alfaiz.
Department of Internal Medicine.
College of Medicine.
Shaqra University.
Riyadh.
Saudi Arabia.
alfaizas@su.
Received: 2025-12-10 Accepted: 2026-02-28 Published: 2026-03-18 Keywords: clinical.
COVID-19, laboratory, markers.
T2DM.
Cite This Article: Alfaiz.
Clinical and laboratory findings in type 2 diabetes mellitus with COVID-19 infection: a single centre study.
Bali Medical Journal 15.
: 67-73.
DOI: 10.
15562/bmj.
INTRODUCTION
Coronavirus disease 2019 (COVID-.
, caused by the severe acute respiratory (SARSCoV-.
, has emerged as one of the most significant global public health crises of the 21st century.
1 Since its declaration as a pandemic by the World Health Organization (WHO) in March 2020.
COVID-19 has resulted in substantial morbidity and mortality worldwide.
Although the clinical spectrum of COVID-19 ranges from asymptomatic infection to severe respiratory failure and multi-organ dysfunction, disease severity is strongly influenced by underlying comorbid conditions.
Among these, type 2 diabetes mellitus (T2DM) has consistently been identified as one of the most important risk factors associated with poor outcomes in COVID-19 patients.
4 The T2DM is characterized by chronic hyperglycemia, insulin resistance, and a persistent low-grade inflammatory state.
5 These pathophysiological alterations contribute Open access:Journal Bali Medical 15.
: 67-73 | doi: 10.
15562/bmj.
to immune system dysfunction, including impaired neutrophil chemotaxis, reduced T-cell response, and abnormal cytokine As a result, patients with T2DM are more susceptible to infections and often experience more severe disease The reciprocal link between COVID-19 and T2DM has been explained by a number of processes.
Hyperglycemia may weaken antiviral immune responses and promote viral multiplication.
7 Additionally.
SARSCoV-2 binds to angiotensin-converting ORIGINAL ARTICLE enzyme 2 (ACE.
receptors, which are expressed in multiple tissues, including the lungs, pancreas, kidneys, and vascular 8 COVID-19 severity may be further increased by endothelial dysfunction, a pro-thrombotic condition frequently observed in diabetes, and dysregulation of the renin-angiotensinaldosterone (RAAS).
The exaggerated inflammatory response, often described as a Aucytokine storm,Ay is also more pronounced in diabetic individuals, potentially leading to acute respiratory distress syndrome (ARDS), multi-organ failure, and increased mortality.
The Kingdom of Saudi Arabia (KSA) is a crucial location for researching the relationship between diabetes and COVID-19 since it has one of the highest prevalence rates of type 2 diabetes Rapid urbanization, sedentary lifestyle patterns, and dietary transitions have contributed to the growing burden of metabolic disorders in the region.
Managing patients with numerous comorbidities, such as diabetes and cardiovascular disease, was a major issue for KSAAos healthcare systems during the early stages of the COVID-19 epidemic.
However, despite the high prevalence of T2DM, limited region-specific data exist describing the clinical characteristics, comorbidity patterns, and laboratory profiles of hospitalized COVID-19 patients with diabetes in Saudi Arabia.
Understanding these characteristics is essential for several reasons.
First, early identification of high-risk features can facilitate timely intervention and risk stratification.
Second, laboratory organ dysfunction, and coagulation abnormalities may help guide clinical decision-making and resource allocation.
Third, regional data are crucial, as disease patterns, genetic background, healthcare access, and comorbidity profiles may differ from those reported in Western or Asian Thus, the purpose of this study was to examine and contrast the clinical presentation, laboratory inflammatory markers, comorbidities, and demographic characteristics of hospitalized COVID-19 patients with and without type 2 diabetes in a tertiary care hospital in Riyadh.
Saudi Arabia.
By identifying distinctive characteristics associated with T2DM in COVID-19, this study seeks to contribute to improved clinical management strategies and better outcomes for this high-risk population.
METHODS
Design and setting The medical records of T2DM patients with proven COVID-19 infection who were hospitalized at Prince Mohammed Bin Abdulaziz Hospital (PMAH) in Riyadh.
Saudi Arabia, between March 15, 2020, and July 15, 2020, were examined in this retrospective cross-sectional Participants This study comprised the records of 239 hospitalized patients who had a confirmed COVID-19 infection.
Children, pregnant women, and those with impaired mental capacity were not included.
Because pregnancy is linked to distinct physiological, immunological, and metabolic changes that may independently affect COVID-19 severity and laboratory markers, thereby complicating the relationship between T2DM and COVID-19 results, pregnant patients were excluded.
Children were not included since their COVID-19 clinical course, immunological response, and illness presentation differed from those of adults.
Because accurate symptom reporting .
uch as chest discomfort or shortness of breat.
and clinical history documentation may be inconsistent in this population, patients with impaired mental ability were excluded.
Furthermore, these individuals frequently have complicated co-occurring neurological disorders that might independently affect inflammatory indicators and clinical outcomes, thus creating confounding.
SARS-CoV-2 infection was diagnosed using the criteria established by the Saudi Center for Disease Prevention and Control.
Anti-diabetic medicine or recorded medical records served as the basis for the studyAos definition of a diabetic patient.
Additionally, a fasting glucose level of at least 7.
0 mmol/L upon admission and a HbA1c value of at least 5 were regarded as diagnostic of diabetes Non-diabetics were defined as those without a history of diabetes, antidiabetic drug usage.
HbA1c < 6.
5, and fasting glucose < 7.
0 mmol/L.
Data collection Demographic information, such as gender, age, and nationality, was collected.
Shortness of breath (SoB), tachypnea, fever, cough, chest discomfort, blood pressure, heart rate (HR), respiratory rate (RR), oxygen saturation, length of stay, and admission to the intensive care unit (ICU) were among the clinical indicators noted.
Along with test results on inflammatory markers, including fibrinogen.
D-dimer, and C-reactive protein (CRP), information was also gathered on comorbidities like hypertension, dyslipidemia, congestive heart failure, and ischemic heart disease.
Data analysis SPSS version 21.
0 (IBM Corp.
Chicago.
IL.
USA) was used to analyze the data.
While continuous data were first evaluated for normality using the Shapiro-Wilk test and visual examination of histograms, categorical variables were summarized as frequencies and percentages.
Nonparametric statistical tests were used since the majority of continuous laboratory data showed a non-normal distribution.
Because the Mann-Whitney U test is suitable for skewed data and does not presume a normal distribution, it was utilized to evaluate continuous variables between T2DM and non-diabetic groups.
When anticipated cell counts were sufficient, the Chi-square test was used to evaluate correlations between T2DM status and clinical features for categorical However.
FisherAos Exact test was employed when anticipated frequencies in contingency tables were less than five in more than 20% of cells, since it offers a more precise estimate for sparse data and small sample sizes.
Bivariate logistic regression was used to compute crude odds ratios (COR) with 95% confidence intervals (CI).
To calculate adjusted odds ratios (AOR) while accounting for possible confounders, variables that were statistically significant in bivariate analysis were included in a multivariable binary logistic regression model.
Statistical significance was defined as a two-tailed P-value of less than 0.
Bali Medical Journal 2026.
: 67-73 | doi: 10.
15562/bmj.
ORIGINAL ARTICLE
RESULTS
Baseline demographic and clinical About 142 .
4%) of the 239 individuals examined had type 2 diabetes (Table Patients with type 2 diabetes were considerably older than those without the disease .
A 13.
1 vs.
47 A 15.
2 years.
P < In terms of clinical presentation.
T2DM patients had substantially higher rates of cough (P = 0.
, tachypnea (P = .
, and shortness of breath (P = 0.
There were no statistically significant differences between the groups in terms of fever or chest discomfort.
In terms of comorbidities.
T2DM patients had considerably higher rates of dyslipidemia (P = 0.
and hypertension (P = 0.
Furthermore.
T2DM patients were more likely than non-diabetic patients to be admitted to the intensive care unit (P = Laboratory and inflammatory markers Creatinine (P = 0.
, blood urea nitrogen (P = 0.
, lactate dehydrogenase (P = .
C-reactive protein (P = 0.
and fibrinogen (P = 0.
were all considerably higher in T2DM patients.
The levels of total bilirubin.
ALP.
ALT.
AST, and D-dimer did not differ significantly between the two groups.
These results point to increased organ failure and systemic inflammation in COVID-19affected diabetic individuals (Table .
Logistic regression analysis The crude and adjusted risk ratios for variables linked to type 2 diabetes in hospitalized COVID-19 patients are shown in Table 3.
T2DM was shown to be substantially correlated with cough, tachypnea, shortness of breath, hypertension, and dyslipidemia in bivariate analysis.
Nevertheless, tachypnea .
OR = 3.
95% CI: 1.
65Ae7.
P =
and dyspnea .
OR = 3.
CI: 1.
49Ae7.
P = 0.
continued to be independently related with multivariable logistic regression correction.
After correction, the comorbidities dyslipidemia .
OR = 12.
95% CI: 2.
63Ae57.
P =
and hypertension .
OR = 2.
CI: 1.
03Ae4.
P = 0.
continued to be statistically significant.
Table 1.
Baseline characteristics of the research subjects Characteristics Gender
Male
Female Age
Nationality Non-Saudi Saudi Cough
Yes
Fever
Yes
Tachypnea
Yes
Chest pain
Yes
Shortness of breath
Yes
Hypertension Yes
Chronic kidney disease Yes
Dyslipidaemia
Yes
Bronchial asthma
Yes
Ischemic heart disease Yes
Congestive cardiac failure Yes
Intensive care unit admission Yes
T2DM
P-value Yes 47 A 15.
56 A 13.
<0.
Note: aFisherAos Exact Test.
bMann-Whitney U test.
*significant (P<0.
DISCUSSION