Generic selectors
Exact matches only
Search in title
Search in content
Post Type Selectors
Search in posts
Search in pages
Filter by Categories
Abstracts
Cardiovascular, Case Report
Cardiovascular, Commentary
Cardiovascular, Editorial
Cardiovascular, Guest Editorial
Cardiovascular, Images in Cardiology
Cardiovascular, Interventional Round
Cardiovascular, Original Article
Cardiovascular, Perspective Review
Cardiovascular, Preface
Cardiovascular, Review Article
Cardiovascular, Student’s Corner
Case Report
Case Report, Cardiovascular
Case Reports
Case Series, Cardiovascular
Clinical Discussion
Clinical Rounds
CPC
Current Issue
Debate
Dedication
Editorial
Editorial Cardiovascular
Editorial, From the Publisher’s Desk
Expert Comments
Expert's Opinion
Genetic Autopsy
Genetics Autopsy
Guest Editorial, Cardiovascular
Image in Cardiology
Images in Cardiology
Images in Cardiology, Cardiovascular
Interventional Round
Interventional Round, Cardiovascular
Interventional Rounds
Letter to Editor
Letter to Editor, Clinical Cardiology
Letter to the Editor
Media and news
Original Article
Original Article, Cardiovascular
Original Article, Cardiovascular Health
Practice in Medicine
Preface
Review Article
Review Article, Cardiovascular
Scientific Paper
Short Communication
Student's Corner
Supplementary
Supplemetary
WINCARS Activities
Generic selectors
Exact matches only
Search in title
Search in content
Post Type Selectors
Search in posts
Search in pages
Filter by Categories
Abstracts
Cardiovascular, Case Report
Cardiovascular, Commentary
Cardiovascular, Editorial
Cardiovascular, Guest Editorial
Cardiovascular, Images in Cardiology
Cardiovascular, Interventional Round
Cardiovascular, Original Article
Cardiovascular, Perspective Review
Cardiovascular, Preface
Cardiovascular, Review Article
Cardiovascular, Student’s Corner
Case Report
Case Report, Cardiovascular
Case Reports
Case Series, Cardiovascular
Clinical Discussion
Clinical Rounds
CPC
Current Issue
Debate
Dedication
Editorial
Editorial Cardiovascular
Editorial, From the Publisher’s Desk
Expert Comments
Expert's Opinion
Genetic Autopsy
Genetics Autopsy
Guest Editorial, Cardiovascular
Image in Cardiology
Images in Cardiology
Images in Cardiology, Cardiovascular
Interventional Round
Interventional Round, Cardiovascular
Interventional Rounds
Letter to Editor
Letter to Editor, Clinical Cardiology
Letter to the Editor
Media and news
Original Article
Original Article, Cardiovascular
Original Article, Cardiovascular Health
Practice in Medicine
Preface
Review Article
Review Article, Cardiovascular
Scientific Paper
Short Communication
Student's Corner
Supplementary
Supplemetary
WINCARS Activities
Generic selectors
Exact matches only
Search in title
Search in content
Post Type Selectors
Search in posts
Search in pages
Filter by Categories
Abstracts
Cardiovascular, Case Report
Cardiovascular, Commentary
Cardiovascular, Editorial
Cardiovascular, Guest Editorial
Cardiovascular, Images in Cardiology
Cardiovascular, Interventional Round
Cardiovascular, Original Article
Cardiovascular, Perspective Review
Cardiovascular, Preface
Cardiovascular, Review Article
Cardiovascular, Student’s Corner
Case Report
Case Report, Cardiovascular
Case Reports
Case Series, Cardiovascular
Clinical Discussion
Clinical Rounds
CPC
Current Issue
Debate
Dedication
Editorial
Editorial Cardiovascular
Editorial, From the Publisher’s Desk
Expert Comments
Expert's Opinion
Genetic Autopsy
Genetics Autopsy
Guest Editorial, Cardiovascular
Image in Cardiology
Images in Cardiology
Images in Cardiology, Cardiovascular
Interventional Round
Interventional Round, Cardiovascular
Interventional Rounds
Letter to Editor
Letter to Editor, Clinical Cardiology
Letter to the Editor
Media and news
Original Article
Original Article, Cardiovascular
Original Article, Cardiovascular Health
Practice in Medicine
Preface
Review Article
Review Article, Cardiovascular
Scientific Paper
Short Communication
Student's Corner
Supplementary
Supplemetary
WINCARS Activities
View/Download PDF

Translate this page into:

Cardiovascular
Original Article
ARTICLE IN PRESS
doi:
10.25259/IJCDW_16_2023

Gender Specific Difference and Clinical Spectrum of COVID-19 Patients Admitted in Tertiary Care Hospital of Northern India

Department of Cardiology, Dayanand Medical College and Hospital, Ludhiana, Punjab, India.
Department of Community Medicine, Dayanand Medical College and Hospital, Ludhiana, Punjab, India.

*Corresponding author: Shibba Chhabra, Department of Cardiology, Dayanand Medical College and Hospital, Ludhiana, Punjab, India. shibbachhabra@yahoo.com

Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

How to cite this article: Chhabra S, Kamboj S, Sharma P, Luthra S, Goyal M, Gupta A, et al. Gender specific difference and clinical spectrum of COVID-19 patients admitted in tertiary care hospital of Northern India. Indian J Cardiovasc Dis Women, doi: 10.25259/IJCDW_16_2023

Abstract

Objectives:

In a tertiary care hospital in Northern India, we examined the demographic, biochemical, and clinical risk factors related to gender differences in COVID-19 patients who were hospitalized.

Materials and Methods:

The study was carried out in a hospital with tertiary care. In this retrospective comparative observational study the data was collected from march 2020 to end of COVID pandemic. Analyses were done on the n = 1068 individuals who were hospitalized during the study period.

Results:

There were 1068 individuals evaluated in the trial, with a male-to-female ratio of 2.3:1. Males and females had similar mean ages (55.84 vs. 55.44 years). Difference was found to be statistically significant in asthmatic boys and females (P = 0.01). In our study, a novel severity score (NSS) was utilized to forecast inpatient mortality in COVID-19 patients. NSS scores were higher for men (2.95) than for women (2.65), with P = 006. Under the categories “Expired,” “discharged against medical advice (DAMA),” and “Discharged,” all the criteria that have been previously analyzed were compared. Based on the number of comorbidities, there was a clear, significant difference between patients who were discharged, expired, and under DAMA, with a P = 0.001. Majority of patients with comorbidities that most frequently impacted the cardiovascular and respiratory outcomes.

Conclusion:

Studies conducted globally found that men experienced a higher rate of mortality. Our study also indicates that when the number of comorbidities rises, the death rate rises. Therefore, individuals with a larger number of comorbidities, such as hypertension, diabetes, coronary artery disease, and peripheral vascular disease, should exercise particular vigilance.

Keywords

Coronavirus disease-19
Outpatients
Hospital

ABSTRACT IMAGE

INTRODUCTION

Since the start of the global coronavirus disease (COVID-19) pandemic in December 2019, every aspect of people’s existence has been impacted. The World Health Organization designated the current coronavirus disease (Severe acute respiratory syndrome coronavirus 2 [SARSCoV-2] infection) a global pandemic on March 11, 2020. The first verified COVID-19 case and death occurred in India on January 27, 2020, and March 12, 2020, respectively. For health-care professionals looking to better patient outcomes, it is critical to comprehend how COVID-19 evolves among hospitalized patients. Estimates of the mortality rates among COVID-19 patients are especially crucial for monitoring the caliber and efficacy of hospital care. Men with the 2019 novel COVID-19 have a more severe illness and a greater mortality rate than women.

According to reports from China, males made up 60% of COVID-19 patients, and men died from the disease at a rate of 2.8% compared to 1.7% for women. In Italy, males accounted for 70% of the fatalities. These findings suggest that COVID-19 may have a gender component, with older males dying at higher rates and men more likely to be severely affected.[1-4] To comprehend the effects of this public health emergency on various people, families, and communities and to develop equitable and sustainable interventions, we also need to identify the phenotypical differences in severe case manifestations of COVID-19 in males and women. This study aimed to examine the demographic, biochemical, and clinical risk factors associated with outcomes within hospitalized COVID-19 patients in a tertiary care hospital of Northern India.

MATERIALS AND METHODS

The study was carried out in a specialized care facility. Retrospective comparative observational research the (retrospective data March 2020 to the end of the COVID pandemic). Analyses were done on the n = 1068 patients who were hospitalized during the study time. The information was divided into categories A (females) and B (males) (males). With a male-to-female ratio of 2.3:1, n = 320 of these belonged to Group A (females), and n = 748 to Group B (males). All patients admitted to a hospital in a large healthcare network who tested positive for SARS-CoV-2 RNA using real-time reverse transcriptase-polymerase chain reaction (RT-PCR) assay testing, either carried out inside the hospital system or documented at an outside system before transfer, were considered to meet the inclusion criteria. The research excluded patients who were hospitalized but later found to be RT-PCR negative and RT-PCR positive patients treated as outpatients (home isolation).

Age, sex, and length of hospital stay were among the data examined. Comorbidities of all kinds, including diabetes, hypertension (HT), coronary artery disease (CAD), heart failure (HF), peripheral vascular disease (PVD), prosthetic valves, chronic kidney disease (CKD), renal disease, chronic liver disease (CLD), hepatitis C virus (HCV), HIV, drug addiction, obesity, asthma, chronic obstructive pulmonary disease, interstitial lung disease (ILD), cancer, and hepatitis B surface antigen, were observed. Clinical parameters such as respiratory rate, sulfur dioxide (SO2), mean blood pressure, systolic blood pressure, and diastolic blood pressure were recorded.

There were records of hematological variables such as international normalized ratio (INR), C-reactive protein (CRP), D-dimer, and blood urea nitrogen (BUN). In addition, the ultimate result for each patient – discharge or mortality – was established. The aforementioned factors were combined to create a COVID-19 severity value, which ranges from 0 to 10. The in-hospital mortality index was created using these inputs. The patient was discharged, expired, and discharged against medical advise as a result of his or her final hospital outcome (discharged against medical advice [DAMA]).

Range, mean, standard deviation (SD), frequencies (number of cases), and relative frequencies (percentages), as applicable, were used to characterize the data. Kolmogorov–Smirnov test was used to assess whether the data were normally distributed.

Using independent samples for parametric and non-parametric data, respectively, the Student t-test and Mann– Whitney U-test were used to compare quantitative variables between the research groups. Analysis of variance was used to compare quantitative variables between the research groups. Chi-square[2] and exact tests were used to compare categorical data when the anticipated frequency was <5. Statistical significance was defined as a chance value P < 0.05. The statistical program for Microsoft Windows (Statistical Package for the Social Science; SPSS Inc., Chicago, IL, USA) was used for all statistical computations.

RESULTS

Total number of study participants was 1068 COVID-19 patients. All of them were treated at DMC&H, Ludhiana, that is, tertiary level hospital, from which n = 320 belong to Group A (Female patients) and n = 748 were Group B (Males) with a male: female = 2.3:1. Among cohort of 1068 study subjects, 723 were discharged, 246 were deceased, and 78 were DAMA. In the present study, there were more males than females (70% vs. 30%). Age group of <60 years was most common among males and females. Mean age was comparable among males and females (55.84 ± years vs. 55.44 ± years). In asthmatic males and females, difference was found to be statistically significant (P = 0.01). A novel severity score (NSS) to predict inpatient mortality in COVID-19 patients was used in this study [Table 1].

Table 1: Score factor of patients.
Scoring factors Score assigned
Age
  ≥60 years 1
  ≥70 years 2
  ≥80 years 3
Oxygen saturation
  ≤94% 1
MAP
  ≤80 mmHg 1
  ≤70 mmHg 2
  ≤60 mmHg 3
BUN
  >30 mg/dL 1
CRP
  >10 mg/dL
INR
  >1.2 1
Total score 10

MAP: Mean arterial pressure, BUN: Blood urea nitrogen, CRP: C-reactive protein, INR: International normalized ratio

NSS was graded into low-risk patients (0–3 points), moderate-risk patients (4–7 points), and high-risk patients (>7 points). Total six parameters were used to calculate NSS which include age group, BUN, CRP, INR, mean arterial pressure, and SO2. Out of which INR, CRP, and BUN showed significant difference between males and females, INR (P = 0.00), CRP, and BUN (P = 0.001). Males had higher score of NSS (2.95) in comparison to females (2.65) with P = 006. Among deceased study, subjects mostly were males (72%).

All the parameters studied so far were compared under three headings, expired, DAMA, and discharged. There was no significant difference among discharged, expired, and DAMA patients on basis of gender. There was marked significant difference between discharged, expired, and DAMA patients on basis of no of comorbidities with P = 0.001, as shown in [Table 2].

Table 2: Number of comorbidities.
Number of comorbidities Discharge (n=723) (%) Expired (n=246) (%) DAMA (n=78) (%) Total P-value
0 292 (40) 64 (26) 24 (31) 380 0.0001
1 180 (25) 58 (24) 16 (21) 254
2 198 (27) 64 (26) 27 (35) 289
3 45 (6) 45 (18) 8 (10) 98
4 8 (1) 12 (5) 3 (4) 23
5 0 (0) 3 (1) 0 (0) 3

DAMA: Discharged against medical advice

Out of 18 comorbidities taken in this study, eight comorbidities (diabetes mellitus, HT, CAD, PVD, CKD, CLD, HCV, and ILD) presented with significant difference among discharged, DAMA, and expired patients, as given in [Table 3].

Table 3: Comparison of comorbidity.
Comorbidity P-value
DM 0.001
HT 0.003
CAD 0.0001
HF 0.205
PVD 0.038
Prosthetic valve 0.653
CKD 0.0001
Renal Tx 0.051
CLD 0.0001
HCV 0.042
HBsAg 0.196
HIV 0.196
Drug addict 0.205
Obesity 0.272
COAD 0.099
Asthma 0.538
ILD 0.038

DM: Diabetes mellitus, HT: Hypertension, CAD: Coronary artery disease, HF: Heart failure, PVD: Peripheral vascular disease, CKD: Chronic kidney disease, CLD: Chronic liver disease, HCV: Hepatitis C virus, HBsAg: Hepatitis B surface antigen, HIV: Human immunodeficiency virus, COAD: Chronic obstructive pulmonary disease, ILD: Interstitial lung disease

In most cases, it was found that females had more burden comorbidities than their counterparts, but the result was not significant.

DISCUSSION

A wide range of viruses known as the coronavirus family can cause illnesses such as the common cold, serious pneumonia, SARS,[2] and Middle east respiratory syndrome. Clinical and epidemiological characteristics of COVID-19 patients have recently been described. At our tertiary care facility, a retrospective comparative analysis of COVID-19 patients was conducted. Different variables for mortality and morbidity were compared between both genders. In addition, clinical parameters for DAMA, expired, and discharged patients were examined. To forecast inpatient mortality for patients who presented with SARS-Co-V-2 infection to hospital emergency rooms, we used a novel severity scoring method. In our research, a NSS with a ratio of 2.3:1 was used on 1068 subjects, 320 of whom were female and 748 of whom were male.

Patients from Groups A and B presented with comparable severity, we discovered. However, mortality rates were higher among men than women, which was consistent with numerous studies conducted around the globe. When comparing the numbers of comorbidities under discharged, expired, and DAMA, the study showed a huge disparity.

One of the first studies to look into how gender affects the morbidity and mortality of SARS-COV-2 transmission was conducted by Jin et al.[5] Men with COVID-19 are more likely to experience worse outcomes and pass away, regardless of age, according to this research, which compared the severity and mortality of male and female patients with COVID-19.

While there is no difference in the proportion of male and female patients with confirmed COVID-19, Gruijter et al.’s[6] meta-analysis of 3,111,714 COVID-19 patients found that male patients have nearly 3 times the odds of needing intensive treatment unit (ITU) admission (odds ratio [OR] = 2.84; 95% confidence interval [CI] = 2.06, 3.92) and higher odds of dying (OR = 1.39; 95% CI = 1.31, 1.47) compared to female patients. About 72% of the deceased study subjects in our study were discovered to be men.

Males, when compared to a matched cohort of females of a similar age, have a greater risk of mortality, hospitalization, and mechanical ventilation, according to Singh et al.[7]

This gender-based risk of poor outcomes is more evident in older patients with COVID-19. Men with COVID-19 infection have a >50% higher chance of all-cause death, severe COVID-19 infection, or ICU admission than women, according to Kragholm et al.[8] Age-adjusted relative mortality risk ratio for men in the Hong Kong SARS-CoV-1 epidemic was 1.62 (95% CI = 1.21, 2.16) [Table 1]. Male sex was linked to an odds ratio of 3.10 (95% CI = 1.64, 5.87; P = 0.001) for ITU admission or mortality during the same outbreak in Singapore.[9]

According to these findings, the substantial sex bias seen in the COVID-19 pandemic is likely caused by fundamental differences in the immune response between males and females, even though socioeconomic factors may be influencing some aspects of the pandemic.[5] There are differences in the expression of angiotensin-converting enzyme 2 (ACE2) receptors between the sexes, which promote the entry of the SARS-CoV-2 virus and human-to-human transmission. Because the ACE2 gene is situated on the X-chromosome and may be affected by estradiol, it may be able to avoid X-inactivation in females.[5] High protein expression of the ACE2 receptor in particular organs has previously been linked to specific organ failures, as shown by matching clinical parameters in SARS patients.

It has been demonstrated that patients with diabetes or cardiovascular diseases as well as males as compared to women have higher levels of circulating ACE2.[10] The advantage of females in COVID-19 may be explained by sex variations in the innate and adaptive immune systems. Comparatively to men, females have more CD4+ T-cells, stronger CD8+ T-cell cytotoxic activity, and higher B-cell immunoglobulin production within the adaptive immune system. In a research by Elezkurtaj et al.,[10] clinical records revealed that respiratory insufficiency predominated in the majority of cases, but that sepsis, an infection-related condition, was the most common clinical cause of death.

In their research, the majority of patients who passed away had been identified with comorbidities that most frequently impacted the cardiovascular and respiratory systems: arterial HT, chronic kidney or heart disease, and chronic pulmonary disease.

In the current research, we used patient characteristics and clinical parameters gathered on the first day of hospital presentation to compute a preexisting novel scoring system that could aid in predicting the severity of COVID-19 infection.

The fact that our research was conducted in a tertiary hospital means that its findings cannot be generalized to the general population. The findings may be skewed toward higher mortality because the data were collected at the peak of the pandemic, when hospitals were under a lot of strain.

CONCLUSION

Our study, men presented with higher rate of mortality, according to studies compared worldwide. Our study also suggests, there is higher rate of mortality as number of comorbidities increase. Hence, extraprecaution should be taken by person suffering from higher number of comorbidities, such as HT, diabetes, CAD, and PVD.

Declaration of patient consent

The authors certify that they have obtained all appropriate patient consent.

Conflicts of interest

There are no conflicts of interest.

Audio summary available at

https://doi.org/10.25259/IJCDW_16_2023

Financial support and sponsorship

Nil.

References

  1. , , , , , , et al. Novel coronavirus infection (COVID-19) in humans: A scoping review and meta-analysis. J Clin Med. 2020;9:941.
    [CrossRef] [PubMed] [Google Scholar]
  2. , , , , , , et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. Lancet. 2020;395:507-13.
    [CrossRef] [PubMed] [Google Scholar]
  3. , , , , , , et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020;323:1061-9.
    [CrossRef] [PubMed] [Google Scholar]
  4. , , , , , , et al. China medical treatment expert group for covid-19. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382:1708-20.
    [CrossRef] [PubMed] [Google Scholar]
  5. , , , , , , et al. Gender differences in patients with COVID-19: Focus on severity and mortality. Front Public Health. 2020;8:152.
    [CrossRef] [PubMed] [Google Scholar]
  6. , , , , , , et al. Male sex identified by global COVID-19 meta-analysis as a risk factor for death and ITU admission. Nat Commun. 2020;11:6317.
    [CrossRef] [PubMed] [Google Scholar]
  7. , , , . Gender-based disparities in covid-19 patient outcomes: A propensity-matched analysis. medRxiv doi: 10.1101/2020.04.24.20079046
    [CrossRef] [Google Scholar]
  8. , , , , , , et al. Association between male sex and outcomes of coronavirus disease 2019 (COVID-19)-a Danish nationwide, register-based study. Clin Infect Dis. 2021;73:e4025-30.
    [CrossRef] [PubMed] [Google Scholar]
  9. , , , , , , et al. Gender differences in patients with COVID-19: A narrative review. Monaldi Arch Chest Dis. 2020;90:318-24.
    [CrossRef] [PubMed] [Google Scholar]
  10. , , , , , , et al. Causes of death and comorbidities in hospitalized patients with COVID-19. Sci Rep. 2021;11:4263.
    [CrossRef] [PubMed] [Google Scholar]
Show Sections