{"id":40007,"date":"2021-09-30T10:42:35","date_gmt":"2021-09-30T10:42:35","guid":{"rendered":"https:\/\/biomedpharmajournal.org\/?p=40007"},"modified":"2021-10-11T10:03:35","modified_gmt":"2021-10-11T10:03:35","slug":"to-study-demographics-as-risk-factor-for-mortality-associated-with-covid-19-a-retrospective-cohort-study","status":"publish","type":"post","link":"https:\/\/biomedpharmajournal.org\/staging\/vol14no3\/to-study-demographics-as-risk-factor-for-mortality-associated-with-covid-19-a-retrospective-cohort-study\/","title":{"rendered":"To Study Demographics as Risk Factor for Mortality Associated with COVID-19 : A retrospective cohort study"},"content":{"rendered":"

Introduction<\/strong><\/p>\n

Novel corona virus disease COVID-19\u00a0 has emerged as a pandemic, claiming over 1,431,513\u00a0 lives ( till Nov. 27,2020 ) worldwide involving 191 countries .[1]<\/sup> More than 1,35,715 deaths( till Nov. 27,2020 )\u00a0 have been reported from India . Out of these 4,710 deaths ( till Nov.\u00a0 27,2020 )\u00a0 have been reported from Punjab.[2]<\/sup><\/p>\n

Corona viruses are a family of enveloped, single stranded, zoonotic\u00a0 RNA viruses which can rapidly mutate and recombine, leading to novel viruses that can spread from animals to\u00a0humans[3]<\/sup> These RNA viruses have\u00a0 glycoprotein spikes that give them a crown like appearance.[4]<\/sup><\/p>\n

The mode of disease spread is by droplets generated by infected people during sneezing and coughing. [5,6] <\/sup>Incubation period varies from 2-14 days with a median of 5 days. The severity\u00a0and fatality are higher in the elderly, especially above the age of 60 and those with comorbidities like heart disease, hypertension, diabetes etc. [7]<\/sup><\/p>\n

In this study, we will investigate the associations between various \u00a0factors like age and gender as risk factors for\u00a0 COVID-19-related mortality in patients admitted to the hospital. However, little data on the prognostic factors of COVID-19 have been reported. This is the first\u00a0regional study evaluating the role of age and gender in mortality of COVID infection by comparing huge data set of thousands of people with two outcome groups namely ,death and discharged groups.<\/p>\n

Material and Methods<\/strong><\/p>\n

Study\u00a0 Design<\/strong><\/p>\n

It is a record based retrospective cohort study .For the COVID-19 cohort in this study, database of Covid hospital, Rajindra hospital Patiala for COVID-19 ,from july 1 to November 30, 2020, was assessed . The information used in this study is anonymous\u00a0and covers only age and gender data. In the first group named Death group data of COVID positive patients who died was analysed and in the second group named\u00a0Discharged group , the data of COVID positive patients who recovered and were discharged from the hospital was included. The study protocol was approved by the Institutional Ethics Committee.<\/p>\n

Sample size<\/strong><\/p>\n

Database of COVID-19 positive patients\u00a0 hospitalized between the months of July 2020 and November 2020 was included for analysis in this study. Sample size for age analysis was data of 2,142 indoor covid positive patients out of which 705 died\u00a0 and 1437\u00a0recovered and discharged from the hospital\u00a0 . Sample size for various variables analysis differed by \u00b1 25 because of some missing values in the database.<\/p>\n

Statistical analysis<\/strong><\/p>\n

Continuous variables were described using mean\u2009\u00b1\u2009standard deviation and categorical variables were presented as frequency rates and percentages. We used independent group\u00a0t<\/em>\u00a0tests to compare means for continuous variables when the data were normally distributed.In the case\u00a0of age group analysis Levene’s test was significant (p < .05), suggesting a violation of the equal variance assumption,but seeing the sample size of thousands instead of using another option of Mann Whitney U test the results of students t test with highly significant difference were found\u00a0permissible in this case . For categorical variables, we used the\u00a0Chi square\u00a0test, to compare differences between the dead and discharged\u00a0 patients groups where appropriate. The two sided\u00a0 p value of <0.05 was considered statistically significant and p value of <0.01 was considered as\u00a0statistically highly significant . The data was subjected to statistical analysis using JASP software 0.14 version of the license.<\/p>\n

Results<\/strong><\/p>\n

A database of 2308 COVID-19 positive\u00a0 patients who were hospitalised between July 1 and Nov 30, 2020,was screened for inclusion in this retrospective cohort study . Out of this, data of 161(6.98%) indoor COVID-19 positive patients was excluded due to various reasons of referral to other hospital (n=129) , brought dead (n=1) and missing values of the variables(n=36) .Data of total of 2142\u00a0 patients hospitalized for COVID -19 was included in the analysis in this study.[Table 1]\n\n\n\n
\"Vol14No3_stu_Ama_tab1\"<\/a><\/td>\nTable 1: Flow Chart of Data Disposition in tha study.<\/strong><\/p>\n

Click here to view figure<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

The data analysis\u00a0 of patients hospitalised for COVID-19 for the\u00a0 age comparison between two groups based on the outcome showed a median age of 60 years (IQR 50-70) for patients who died because of COVID-19\u00a0 and 52 years (IQR 36\u201362) for the patients who recovered from\u00a0COVID and were discharged from the hospital (p value-<0.001).[Table 2] There were 9 (0.65%) pediatric patients (<12 yrs) in the group of patients who recovered and were discharged from hospital.<\/p>\n

Table 2: Analysis of data for age as risk factor for COVID -19 related mortality.<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n
Comparison of age in death and discharged group<\/strong><\/td>\n<\/tr>\n
<\/td>\nDeath<\/strong><\/td>\nDischarged<\/strong><\/td>\n<\/tr>\n
Valid<\/strong><\/td>\n705<\/td>\n1437<\/td>\n<\/tr>\n
Missing<\/strong><\/td>\n0<\/td>\n0<\/td>\n<\/tr>\n
Mean<\/strong><\/td>\n58.511<\/td>\n49.848<\/td>\n<\/tr>\n
Std. Deviation<\/strong><\/td>\n14.348<\/td>\n16.615<\/td>\n<\/tr>\n
Median<\/strong><\/td>\n60.000<\/td>\n52.000<\/td>\n<\/tr>\n
25th percentile<\/strong><\/td>\n50.000<\/td>\n36.000<\/td>\n<\/tr>\n
50th percentile<\/strong><\/td>\n60.000<\/td>\n52.000<\/td>\n<\/tr>\n
75th percentile<\/strong><\/td>\n70.000<\/td>\n62.000<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

For gender analysis (n=2129), COVID patients who died were 32.5%( n=692) ,out of which 63.6%(n=440) were males and 36.4%(n=252) were females. COVID positive patients who recovered and were discharged from the hospital were 67.5%(n=1437),out of which\u00a061.2%(n=880) were males and 38.8%(n=557) were females.On comparing the two outcome groups for gender males were more affected with COVID in death and discharged both groups . Mean age of males and females in the death group was 57.9\u00b114.7 and 59.5\u00b113.7 respectively. Mean age of males and females in the discharged group was 50.4\u00b115.6 and 49.0\u00b118.1 respectively. Ages were comparable between men and women in both patients who deceased and survived.[Table 3]Of the 692 \u00a0patients in the death group,63.6% were men and\u00a036.4 % were women. The number of men was 1.74 times that of women in the death group.It was evident from the results where\u00a0 male gender is showing clear cut predilection for COVID infection compared to females in both death and discharged group. There was no statistical\u00a0difference between the two groups for mortality risk based on gender for COVID -19 infection (chi square value of 1.09, p value=.296).[Table 4] The relative risk of death in males and females in death group was 1.052 (95% CI=0.92-1.204). as this confidence interval includes value of 1,\u00a0so the risk ratio shows that incidence of risk of death in\u00a0 death group amongst males and females is same.<\/p>\n

Table 3: Independent Samples T-Test.<\/strong><\/p>\n\n\n\n\n
<\/td>\nt<\/strong><\/td>\ndf<\/strong><\/td>\np-value<\/strong><\/td>\n<\/tr>\n
Age<\/strong><\/td>\n11.845<\/td>\n2140<\/td>\n<0.001<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Note:Student’s t-test.Levene’s test is significant (p < .05), suggesting a violation of the equal variance assumption<\/p>\n

Table 4: Analysis of data for Gender as risk factor for COVID -19 related mortality.<\/strong><\/p>\n\n\n\n\n\n\n
<\/td>\nDeath<\/td>\nDischarged<\/td>\nRow Total<\/td>\nChi square<\/p>\n

\u00a0\u00a0\u00a0\u00a0 ( \u03c72 )<\/sup><\/td>\n

p-value<\/td>\n<\/tr>\n
Male<\/td>\n440<\/td>\n880<\/td>\n1320<\/td>\n1.0903<\/td>\n0.296404<\/td>\n<\/tr>\n
Female<\/td>\n252<\/td>\n557<\/td>\n809<\/td>\n<\/td>\n<\/tr>\n
Total<\/td>\n692<\/td>\n1437<\/td>\n2129<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Discussion<\/strong><\/p>\n

As the novel corona virus continues to evolve, there are still many lacunae \u00a0to our knowledge regarding the risk factors affecting the mortality caused by this deadly virus. Older \u00a0age adults are more affected by this disease. However, little data on the prognostic factors of\u00a0COVID-19 have been reported. This is the first regional study evaluating the role of age and gender in mortality of COVID infection by comparing huge data set of thousands of people with two outcome groups namely ,death and discharged groups.In the first group named Death group\u00a0data of COVID positive patients who died was analysed and in the second group named Discharged group , the data of COVID positive patients who recovered and were discharged from the hospital was included.<\/p>\n

In this study\u00a0 of COVID-19, consistent with previous studies older age patients of median age 60 years (IQR 50-70) were died compared to median age 52 years (IQR 36\u201362) in the patients who recovered from COVID. According to the CDC, 8 out of 10 deaths reported in the\u00a0USA occurred in adults 65 years old and above.[8]<\/sup>The age-dependent defects in T-cell and B-cell function, and the excess production of type 2 cytokines could lead to a viral replication control deficiency and more prolonged pro-inflammatory responses, potentially causing poor\u00a0outcomes.[9]<\/sup><\/p>\n

On comparing the two outcome groups (Death vs Discharged) for gender, males were more affected than females with COVID in death and discharged both groups( 63.6% vs 36.4% ;61.2% vs 38.8%) . Mean age of males and females in the death group was 57.9\u00b114.7 and\u00a059.5\u00b113.7 respectively .Mean age of males and females in the discharged group was 50.4\u00b115.6 and 49.0\u00b118.1 respectively.<\/p>\n

Ages were comparable between men and women within the group in both patients who deceased and survived while higher age people were more prone\u00a0 to succumb to death by COVID-19 infection showing that age is an independent risk factor for mortality leaving aside\u00a0the gender. That means both males and females of higher age are at the risk \u00a0of increased mortality independent of their gender( chi square ,p value=0.296).Both males and females are equally susceptible to the risk of death in death group (RR=1.053; 95%CI=0.92-1.204).The\u00a0 risk\u00a0ratio shows that incidence of risk of death in\u00a0 death group amongst males and females is same enclosing value of 1 .<\/p>\n

In a study done by Jian-Min Jin et al in china Gender Differences in Patients With COVID-19 with the Focus on Severity and Mortality they concluded that Age was comparable between men and women in all data sets . In the case series, however, men\u2019s cases\u00a0tended to be more serious than women\u2019s (P <\/em>= 0.035)while in the public data set, the number of men who died from COVID-19 was 2.4 times that of women (70.3 vs. 29.7%, P <\/em>= 0.016).[10]<\/sup> Thereby showing that\u00a0 the gender role in mortality was also observed. The percentage of males\u00a0were higher in the deceased group than in the survived group (P <\/em>= 0.015).Nevertheless, in our study based on Indian patients although COVID-19 infection is showing predilection for male gender in both death and discharged group ( 63.6% vs 36.4% ;61.2% vs 38.8%) but the males\u00a0and females are equally susceptible to the risk of death in death group (RR=1.053; 95%CI=0.92-1.204).<\/p>\n

Conclusion<\/strong><\/p>\n

The patients with COVID-19 infection requiring hospitalization are showing predilection for male gender in both death and discharged group.<\/strong> Ages were comparable between men and women within the group in both patients who deceased and survived while higher age people\u00a0were more prone\u00a0 to succumb to death by COVID-19 infection showing that age is an independent risk factor for mortality leaving aside the gender.That means both males and females of higher age are at the risk\u00a0 of increased mortality independent of their gender.<\/strong><\/p>\n

Labour force surveys conducted by National Sample Survey Office (NSSO), Ministry of Statistics and Programme Implementation ,Government of Indiathe estimated female Worker Population Ratio (%) on usual status basis in the country during 2009-10 and 2011-12 are 26.6%\u00a0and 23.7% respectively.[11]<\/sup> The male predilection of COVID-19 infection could be due to more outdoor exposure compared to females.<\/p>\n

Conflict of interest<\/strong><\/p>\n

None<\/p>\n

Funding source<\/strong><\/p>\n

None<\/p>\n

References<\/strong><\/p>\n

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