Introduction

In late December 2019, coronavirus disease – 2019 (COVID-19) emerged in Wuhan and spread to most parts of China [1–3]. There was rapid spread of this virus to the whole world with high mortality rate and thus, it was declared a pandemic by WHOM. The clinical spectrum of patients with COVID-19 appears to be varied, like asymptomatic infection, mild upper respiratory tract illness, and severe viral pneumonia with respiratory failure and even death [4–7]. Although there are case series and research articles that have been published, yet information about COVID-19 is still unfolding with the rapidly mutating COVID-19 virus [8]. The present study aims at exploring the clinical characteristics of patients with different outcomes that might provide evidence for risk stratification and help to improve clinical practices and reduce fatality. Both wave 1 and wave 2 data were also compared and presented here.

Method

We conducted a retrospective study focusing on patients who were diagnosed with COVID-19 admitted between July 2020 to August 2021 at our centre. All patients were RT-PCR positive and were hospitalised at our centre. Improvement of clinical profile was the major determinant for discharge of the patients. The study was approved by our hospital’s ethics committee in the month of July 2020 and it was conducted in accordance with the Declaration of Helsinki. Informed consent from patients were taken.

exclusion criteria: patients below 18 years old, patients with negative RT-PCR results, discharge to another centre,

Inclusion criteria: Patients above 18 years old, with HRCT scan, RT-PCR positive for COVID, inpatient department (IPD) patients.

A total of 1763 adult patients were diagnosed COVID positive out of which 804 patients were admitted between June 2020 and June 2021 wherein, from June 2020 to February 2021 were considered to be in the first wave and from March 2021 to June 2021 in the second wave. Patient’s demographics and clinical characteristics such as age, gender, symptoms, hospital stay, CT score, O2 requirement and treatment outcome were tabulated and analysed. All patients were categorised age-wise in five groups viz., ≤ 30, 31-40, 41-50, 51-60 and >60. Comorbidities, duration of hospital stay and mortality were considered as risk factors. list of various medications and mode of O2 given to patients were noted down. Risk of hospital stay and mortality associated with different factors were compared and analysed.

CT score of all the patient was tabulated and its severity was categorized into three types viz., mild (1-5), moderate (6-14) and severe (15-25)

The data was analysed by statistical package for the social sciences (SPSS) version 26.0 of IBM Corporation, Armonk USA. Multiple regression analysis, Pearson’s Chi-square test, t-test for independent samples, and One-way analysis of variance were done for different analysis. p Values < 0.05 indicate that the difference was statistically significant. We used descriptive statistics to report patient demographic characteristics, including mean ± standard deviation age, proportion of male and female patients, and individuals with COVID infection detected during the first wave and second wave of the pandemic. Comparisons of outcomes (i.e., hospitalization, O2 requirement and death) between first and second COVID wave were statistically analysed.

Results

The mean age of the 804 total hospitalised total patients was 53.83 with standard deviation (SD) 15.27 years. Percentage of male patients were greater than females. Mean age of males was 53.82 ±14.86 years and that of females was 53.84 ± 16.07 years. Maximum number of patients were elderly (> 60). At the time of admission patients showed specific symptoms with reference to COVID. Weakness was noted among maximum number of patients whereas, headache was the least. Hypertension (HT) was found in 37.6% patients while Diabetes mellitus (DM in 26.7%. Proportion of Patients with both the conditions was 16.17%. Computed Tomography (CT) was done in 75.4% cases, while in rest it was not performed as these patients were critically ill and could not be shifted to radiology department. 78.35% patients required oxygen support which was provided by Nasal canula to maximum number of patients followed by Ventilator bilevel positive airway pressure (BiPAP), High-flow nasal oxygen (HFNO), face mask (FM) and Invasive. Patients were treated majorly with Remdesivir (78.7%), and Solumedrol (78.0%). 92% patients got recovered and were subsequently discharged.

Table 1

The proportion of death in all age groups and gender wise death rate was statistically analysed using Pearson’s Chi-square test wherein < 50 years category were significantly higher (p value is < 0.0001) than > 50 years category. it was found that the mortality in males was significant and statistically higher than that of females (p value = 0.044). Descriptive statistics for hospital stay according to outcome was performed using t-tests for independent samples. The mean hospital stay of patients with mortality was significantly higher (p value = 0.003) than those who survived. Comparison of CT score categorisation with patient outcome was done using Pearson’s Chi-square test. The association of CT score category at presentation and outcome was statistically significant (p < 0.0001). The proportion of mortality in severe category was significantly higher. Comparison of oxygen requirement and patient outcome done using Pearson’s Chi-square test showed statistically significant result. The mortality in patients requiring oxygen support was significantly higher than those not requiring the support (p = 0.002)

Hospital stay was defined dichotomously as: ≤ 6 days and >6 days, considering the median hospital stay of 6 days. Table 2 provides the unadjusted risk of event, associated with levels of different factors. As regards age, the risk of event associated with 51-60 years and > 60 years were 2.34 [95% confidence interval (CI): 1.56-5.09; p=0.018] and 2.97 [95% CI: 1.49 – 6.38; p=0.002] respectively, as compared to baseline age category ≤30 years, suggesting significantly higher risk of hospital stay > 6 days for these age groups, as compared to reference age group. The presence of only DM and only HT had associated risk levels of 1.63 [95% CI: 0.99-2.66; p=0.046] and 1.59 [95% CI: 1.10- 2.30; p=0.012] respectively, as compared to those without these comorbidities. Those with presence of both DM and HT had significantly increased risk of hospital stay > 6 days with odds ratio (OR) of 2.07 [95% CI: 1.39-3.07; p=0.0002], as compared to those without any comorbidity. Regarding CT score at admission, those in moderate CT category had 1.27 [95% CI: 0.87-1.86; p < 0.0001] times higher risk of hospital stay > 6 days, as compared to mild category patients. Further, for patients in severe category, the risk of event was 7.12 [95% CI: 4.39-11.88; p< 0.0001] times higher than the mild patients.

Also, the adjusted risk associated with different levels of factors was obtained using multiple logistic regression, as shown in the table 2. It shows that presence of both DM and HT significantly increases the risk of hospital stay more than 6 days by OR of 1.73 [95% CI: 1.08-2.74; p=0.021], as compared to those without any comorbidities. Moreover, for patients with severe CT category at admission had 7.32 [95% CI: 4.41-12.14; p< 0.0001] times higher risk of event as compared to patients with mild category.

Table 2

Table 3 provides the unadjusted risk of event, associated with levels of different factors. As regards age, the risk of event associated with 51-60 years and > 60 years were 4.75 [95% CI: 0.58-167.0; p=0.03] and 7.37 [95% CI: 0.91 – 250.5; p=0.007] respectively, as compared to baseline age category ≤30 years, suggesting significantly higher risk of mortality corresponding to these age groups, as compared to reference age group. The risk of event associated with females i.e., 0.53 [95% CI: 0.27-0.97; p=0.044] was significantly lower than that of males. The presence of only DM and only HT had associated risk levels of 1.44 [95% CI: 0.46- 3.75; p=0.049] and 1.79 [95% CI: 0.84-3.72; p=0.011] respectively, as compared to those without these comorbidities. Those with presence of both DM and HT had significantly increased risk of mortality with OR of 4.33 [95% CI: 2.27-8.36; p< 0.0001], as compared to those without any comorbidity. Regarding CT score at admission, those in moderate CT category had 2.87 [95% CI: 1.12-8.38; p=0.024] times higher risk of mortality, as compared to mild category patients. Further, for patients in severe category, the risk of event was 8.73 [95% CI: 3.59-24.7; p< 0.0001] times higher than the mild patients.

Also, the adjusted risk associated with different levels of factors was obtained using multiple logistic regression, as shown in the table 3. Females were at significantly lower risk of mortality with OR of 0.49 [95% CI: 0.25-0.97; p=0.04] as compared to males. Those with presence of both DM and HT had significantly higher risk of mortality with OR 2.14 [95% CI: 1.06-4.31; p=0.034], as compared to those without any morbidities. Moreover, for patients with moderate and severe CT category at admission had 3.17 [95% CI: 1.17-8.60; p=0.023] and 9.59 [95% CI: 3.66-25.1; p< 0.0001] times higher risk of event as compared to patients with mild category, respectively.

Table 3

Table 4 shows statistically significant difference in the gender wise distribution of first and second wave. A higher proportion of females were admitted to IPD in second wave as compared to first wave (p=0.006). Age and hospital stay showed insignificant difference between two waves.

Table 4

At the time of presentation patients’ symptoms were compared and statistically analysed using Chi-square test. Cough (p =0.001), Cough productive (p =0.019), running nose (p =0.009), sore throat (p =0.004), fever (p < 0.0001), weakness (p =0.003), body ache (p < 0.0001) and fatigue (p =0.0002 showed statistically significant difference of proportions between two waves (Table 5).

Comorbidities like HT (p =0.008), ischemic heart disease (IHD) (p=0.02), Chronic Obstructive Pulmonary Disease (COPD) (p =0.019) and Percutaneous transluminal coronary angioplasty PTCA (p =0.007) showed statistically significant difference between two waves (Table 6).

Table 5

Table 6

As shown in Table 7, significantly higher proportion of patients required oxygen support in second wave as compared to first wave. The mortality occurrence was insignificantly different between two waves.

Table 7

Discussion

We have done clinical and demographic studies of COVID patients admitted at our hospital.

Among these patients, cumulatively more males were admitted than females. Several studies have reported that male patients are more susceptible to COVID as well as they experience severe course of disease followed by fatal outcome.¹⁰ In our study population, females were at significantly lower risk of mortality with OR of 0.49 [95% CI: 0.25-0.97; p =0.04] as compared to males. Even though the number of females admitted to our centre increased in wave 2 than wave 1 but in comparison to males it was far less (in both waves). In one study of 5319 patients, a very high mortality risk for seniors, was reported [11]. In another study, about 81% deaths occurred among above 60 years old patients [12]. The association of age and COVID prognosis is widely studied worldwide and it was evident that its severity and mortality were profoundly increased in older patients [13]. Similar findings have been reciprocated in our study.

COVID has an estimated incubation period [14] of 5.1 days and within 11.5 days of its onset the patients start developing its symptoms. Major symptoms present in COVID patients are cough, fever, shortness of breath and less common symptoms are anosmia, nausea, sore throat, diarrhoea, myalgias, malaise, anorexia, headache [15]. As reported by stokes et al, [16] in US, out of 373,883 confirmed symptomatic patients, 70% showed cough, fever and shortness of breath, hence are major symptoms. On the other hand, minor symptoms were headache and myalgia. In our study, at the time of admission, weakness, cough, breathlessness, fever, body ache (myalgia), loss of appetite, sputum production, and headache were the common symptoms. Our results are similar to the studies reported by other centres [17]. Loss of smell and taste was present in only few patients. This is contrary to the earlier reports and World Health Organisation (WHO) released information regarding common symptoms of COVID patients [18, 19].

Coronavirus mainly enters the humans through respiratory tract and it in turn leads to respiratory distress, severe pneumonia, fibrosis and respiratory failure too [20-22].CT severity score plays major role in diagnosis and management of COVID-19 disease [23]. HRCT findings are of major importance in predicting the progression of the disease and severity was is categorised into mild, moderate and severe groups [24] Even though mild and moderate CT score of our patients were more in number than severe group, the demand for oxygen requirement was much higher in these patients. The association of CT score category at presentation and outcome was statistically significant (p < 0.0001) as the proportion of mortality in severe category was significantly higher. In severe cases, the alveoli get damaged [25] due to inflammatory response caused by the viral infection that progressively increase the oxygen demand. As there is limited oxygen exchange, it leads to acute respiratory distress leading to respiratory failure and in worst conditions death depending upon the severity of the disease. Autopsy reports of COVID patients by different study groups have revealed pulmonary thromboembolic effects causing death of the patients [26-30]. One of the most important factors is monitoring of oxygen requirement among COVID patients. In our study groups, 78.35% patients required oxygen support. It was provided by nasal canula in nearly 90% cases. The association of oxygen requirement and outcome was statistically significant in our study. The mortality in patients requiring oxygen support was significantly higher than those not requiring the support. Also, the length of hospital stay was longer in oxygen requiring group since those patients were critically ill. Decreased blood oxygen saturation is one of the typical findings of COVID, [31] and it is associated with poor prognosis. In severe patients, the oxygen saturation was less than 94% and thus giving oxygen support is one of the key requirements.

HT and DM were the most prevalent comorbidities present in patients admitted to our centre. we have found a statistically significant result and correlation between history of DM and HT among COVID-19 patients with that of CT severity score.

Comparison of age, sex, hospital stay, CT score categorisation, and oxygen requirement was done with outcome (death). Statistically significant relationship was observed between variation of age, gender, incidence of DM and HT when compared to mortality. The results demonstrated that old age, male gender, and existence of DM and HT among COVID-19 patients were more among expired patients. Similar reports were in line with these findings that HT and DM were the most predominant comorbidities in COVID patients [32-36]. There is a meta-analysis which exhibited an increased mortality rate in males [37]. According to one of the studies, COVID mortality in diabetic patients were more than non-diabetic patients as it exponentially worsens the prognosis [38]. Interestingly, in our study, we have found that COVID patients suffering from both DM and HT, the outcome worsened leading to increased mortality rate. There are elevated cases of hospitalisation of patients suffering from these comorbidities. ^{[39, 40]} It is now evident from our findings that DM and HT either alone or together plays a pivotal role in making the patient critically ill and their subsequent death. This condition indicates to an important prospect that clinicians have to keep in mind. Extra care and keen observation are needed while treating these COVID patients in this specific group.

We observed distinct differences in characteristics and outcomes between wave 1 and wave 2 of the pandemic. In wave 2, higher number of female populations were hospitalised at our centre, however, there was insignificant difference when compared for age and hospital stay. The percentage of total patients admitted to our centre in both wave 1 (50.25%) and wave 2 (49.75%) were almost same. Age distribution of the patients has shown that there is increase in patients < 50 years of age by 17.2% and decrease in >50 years age group by 9.8%. We can state that number of younger patients were affected more in wave 2 than wave 1 while there was a small decline in the hospitalization of elderly. This could be attributed to the fact that older patients were vaccinated for COVID and there was awareness among common people to protect them by following the guidelines and effective treatments were available on the basis of wave 1 experience. ^[41] The incidence of cough, running nose, fever, weakness, body ache and fatigue has increased in the second wave as compared to first wave and the differences are statistically significant too. There was a drop in certain symptoms like sputum production, sore throat and fever with chills in wave 2. Fever, fatigue and body ache were remarkably more in wave 2 patients. The number of patients admitted to our centre in wave 2 has shown lowered HT cases and the difference was found statistically significant. Similarly, lesser number of DM patients were admitted in wave 2 than wave 1. Significantly higher proportion of patients required oxygen support in second wave as compared to first wave. The recovery rate of patients was 91.8 and 93.3 percentage in wave 1 and wave 2 respectively. This is to mention that our centre being a referral centre had to handle and manage severe COVID patients. As the severity and distress was chronic, recovery was delayed. Recovery rate would have been better if patients were referred earlier to our centre. At the end, in lieu of our findings, it was observed that effective management of severe COVID cases is possible by providing quick diagnosis and rendering correct treatment regime which varies with patient’s clinical conditions.

Conclusion

This retrospective analysis COVID patients with different severity demonstrated that older age, male gender, moderate and severe CT score, comorbidities like DM and HT alone and both in an individual are prominent factors associated with hospital stay and mortality. Thus, patients with comorbidities should be given prompt treatment to avoid complications and mortality. The clinicians and physicians should keep on monitoring clinical conditions time to time to regulate and escalate treatment strategies to mitigate the number of fatalities in the COVID pandemic.

Supplementary Table

Table 8

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