Characteristics and Subgroup Analysis of Risk Factors Associated with In-Hospital Mortality among COVID-19 Patients: A Retrospective Cohort Study

doi:10.21203/rs.3.rs-1973057/v1

Since the COVID-19 pandemic originated in Wuhan, China in early December 2019, millions of lives have been lost. In an epidemic, it is necessary to explore the number of infections and deaths, identify the populations at risk, and determine the factors influencing disease death. The Retrospective cohort study used of 2110 hospitalized patients with COVID-19 data recorded in the Medical Care Monitoring Center information system from March 1, 2020, to February 7, 2021, in the city of Rafsanjan. Among a total of 2110 hospitalized patients (mean age: 56.11, SD: 19.37 years), there were 1125 (54.2%) females, 228 (10.8%) readmissions, and 318 (15.1%) deaths. The highest percentage (70.2%) of hospitalized patients with COVID-19 was infected during the third and early fourth waves. Mortality was high in elderly patients, males, patients with underlying diseases, and those who ‎received mechanical ventilation. The in-hospital mortality trend decreased from the first (19.2%) to the second wave (10.7%) and increased ‎significantly during the third and early fourth waves ‎‎ (16.3%) (P < 0.01).The median 43-day in-hospital survival time was 17 days. An adjusted Multivariable logistic regression showed the age as a strong risk factor for deaths due to COVID-19 while also indicating in both age sub-group analyses that cancer, CKD, neurologic disease, opium, and diabetes were associated with increased odds of death. Finally, patients aged ≥ 65 with CVD and COPD and patients aged < 65 with hypertension were associated with increased odds of death. The area under the ROC curve was 0.809 (95% CI: 0.76–0.83, P < 0.001) to discriminate between discharge and death on hospitalized patients with COVID-19. Our study showed that the effect of the pre-existing chronic diseases on the mortality of COVID-19 varied by age, Also opium was an independent risk factor for in-hospital mortality of COVID-19.

COVID-19

Mortality

Rafsanjan

Survival

Waves of SARS-CoV-2

Since the COVID-19 pandemic originated in Wuhan, China in early December 2019, millions of lives have been lost, leaving devastating effects on people’s health and well-being (1, 2). As of 20 September 2022, 609,848,852 confirmed cases of COVID-19, including 6,507,002 deaths have happened throughout the world (Refer to https://covid19.who.int/). Epidemiology contributes significantly to the investigation of any disease (3, 4). In an epidemic, it is necessary to explore the number of infections and deaths, identify the populations at risk, and determine factors influencing deaths due to the disease (3, 4) for epidemic preparedness and response in the future (4). So far, several variants of SARS-CoV-2 mutations have emerged over time (5–7)with higher transmissibility than the original strains (7) and higher case fatality rates (8, 9), making the control of the COVID-19 pandemic a challenge worldwide. Based on research evidence, age and sex mainly influence the outcomes of the COVID-19 disease (10, 11), with higher mortality rates among females than males (11–13) and higher severity and mortality of COVID-19 in older patients (11, 14). Patients with chronic comorbidities are at increased risk of severe COVID-19 or even death. Emerging evidence suggests that the effect of chronic comorbidities varies by age (15). Evidence also shows substantial factors such as social determinants of health, race, ethnicity, culture, and geographic location, (16–18) were associated with the COVID-19 infection and mortality rates, which varied across different countries (19). More than two years since reports began on the emergence of the new coronavirus and despite evidence of the increase in the emerging infections (20), we don't know when a new outbreaks will occur in the future. Hence, we need to prepare for effective prevention of and response to the next disease outbreak in the world. It is the task of the health research system to seek answers to the questions about the prevention, management, and control of the future epidemics for policymakers, doctors, and patients (21). Thus, this study aimed to determine clinical characteristics and risk factors for deaths across age groups in the whole dataset of patients with COVID-19 across the city of Rafsanjan, Iran.

2.1. Data, Study Design, and Population

This a retrospective cohort study included all 2110 hospitalized patients with PCR diagnosis of the COVID-19 infection based on WHO criteria (23), admitted to Ali-Ibn-Abi-Talib Hospital in the city of Rafsanjan from March 1, 2020 to February 7, 2021. Data used in this study were recorded in the Medical Care Monitoring Center information system in Ali-Ibn-Abi-Talib Hospital in Rafsanjan. From the population under study, 228 patients were readmitted to the hospital. The clinical data included each person’s age at diagnosis, sex, the result of PCR-confirmed diagnosis, history of exposure to people affected with COVID-19, medical comorbidities, date of symptom onset, symptoms and signs, treatment duration, general signs, date of hospitalization, date of discharge, and the date of death. The criterion for the discharge from the hospital was a significant improvement in respiratory symptoms and a decrease in normal body temperature.The first wave as the beginning of the COVID-19 pandemic was reported in Iran January 28, 2020 until June 3, 2020, followed by the second wave as that from starting on June 4, 2021 until Junary15, the third wave as that from starting on 2021 Junary16, and 27 days after the fourth wave as that from starting on 2021 Junary16 until February 7, 2021.

Analysis Statistical:

Characteristics of patients for continuous and categorical variables were expressed as means (SD) and percentage (%), respectively. We used the chi-squared test or Fisher exact test and the student t-test to compare differences in patients hospitalized with COVID-19 given the age, sex, and mortality. The primary event of the study was in-hospital mortality. In the study, time to death/discharge was considered the time between the date of admission and the date of death/discharge from the hospital. And if the desired event did not occur, the time of discharge of ‎censorship was considered. The length of hospitalization for the patients readmitted to the hospital was calculated by the sum of the times they were hospitalized. Survival curves were analyzed and estimated using the Kaplan–Meier (KM) methodology by age, sex, pandemic wave, and for non-hospitalized and hospitalized patients. Also, we used the log-rank test to compare the survival curves. Logistic regression models were fitted to determine the risk factors for the COVID-19 deaths in hospitalization in the two age groups of <65 and ≥ 65 years of age. According to research evidence, the age is known as the risk factor for death. In this study, we first examined the odds ratio of age with mortality using an agreement table. Then, the age was classified into two groups, including under 65 and over 65, to compare the odds ratio of underlying diseases with COVID-19 mortalities in each estimation(22). It was found that the odds ratios of the underlying diseases in the COVID-19 mortality were very close to each other in all classes. Therefore, age was considered a confounding factor, and two logistic regression models were estimated to investigate the effect of underlying diseases on the odds of COVID-19 mortality. The first model considered the effect of age while adjusting other variables and the second model focused on the age classification.

From the early pandemic of COVID-19 to February 6 2021, a total of 2110 patients with laboratory diagnosis of COVID-19 (Median age 57 years, mean age 56.11 with a standard deviation of 19.37, 54.2% female, 4.7% health personnel, 96.8% of Iranian nationality) were admitted to Ali-Ibn-Abi-Talib Hospital in Rafsanjan. Out of this population, 315 patients (15.1%) died, and 228 (10.8%) were readmitted after discharge. Overall, 78.9% of the patients were referred to the hospital in person, and 17.6% were transferred to the hospital by the emergency medical services system (Emergency 115). The majority of patients (64%) were admitted to the isolated ward.

Table 1 shows the clinical characteristics of hospitalized patients with COVID-19 based on age

Table 1

Clinical characteristics of hospitalized patients with COVID-19 based on age
Characteries	Total N = 2110 (%)	Age Group		P-Value
Characteries	Total N = 2110 (%)	< 65 (N = 1311)	≥ 65 (N = 799)	P-Value
Sex
Male	966(45.8)	620(47.3)	346(43.3)
Female	1144(54.2)	691(52.7)	453(56.7)	0.07
Hospitalization Length (days)	5.43 ± 5.1	4.48 ± 4.38	6.99 ± 5.79	**<0.001
Onset of Symptoms Length (days)	5.36 ± 3.88	9.48 ± 5.92	11.74 ± 6.7	**<0.001
exposure	1775(84.1)	1096(83.6)	679(85)	0.4
Fever	1116(55)	723(55.1)	438(54.8)	0.88
Cough	1120(53.1)	708(54)	412(51.6)	0.27
Respiratory ‎Distress	1718(81.4)	1019(77.7)	699(87.5)	**<0.001
Chest Pain	157(7.4)	111(8.5)	46(5.8)	*0.019
Stomach ache	75(3.6)	53(4.1)	22(2.8)	0.11
Vomiting	223(10.6)	135(10.4)	88(11)	0.64
Nausea	285(13.6)	171(13.1)	114(14.3)	0.46
Diarrhoea	146(6.9)	104(8)	42(5.3)	*0.017
loss appetite	243(11.6)	116(8.9)	127(15.9)	**<0.001
Muscular Pain	1146(54.3)	748(57.1)	398(49.8)	**0.001
Paresis	18(0.9)	6(0.5)	12(1.5)	*0.011
Plegia‎	3(0.1)	1(0.1)	2(0.3)	0.3
Headache	337(16)	240(18.4)	97(12.1)	**<0.001
Dizziness	91(4.3)	44(3.4)	47(5.9)	**<0.001
Unconsciousness	390(18.5)	130(9.9)	260(32.5)	**<0.001
Seizures	12(0.6)	11(0.8)	1(0.1)	*0.034
loss of smell	39(1.8)	34(2.6)	5(0.6)	**<0.001
Taste Loss	25(1.2)	22(1.7)	3(0.4)	**<0.001
Cardiovascular disease	345(16.4)	111(8.5)	234(29.3)	**<0.001
Hypertension	735(34.8)	267(20.4)	468(58.6)	**<0.001
Diabetes mellitus	644(30.5)	265(20.2)	379(47.4)	**<0.001
Cancer	46(2.3)	22(1.7)	24(3)	*0.043
Chronic Obstructive Pulmonary Disease	196(9.30)	74(5.6)	122(15.3)	**<0.001
Chronic Kidney Disease	103(4.9)	47(3.6)	56(7)	**<0.001
Asthma	35(1.7)	23(1.8)	12(1.5)	0.66
ChronicLiver Disease	26(1.2)	17(1.3)	9(1.1)	0.73
Blood Disorder	28(1.3)	18(1.4)	10(1.3)	0.81
Chronic Neurological Disease	149(7.1)	60(4.6)	89(11.1)	**<0.001
HIV	3(0.1)	2(0.3)	1(0.1)	0.87
Smoke	28(1.3)	15(1.1)	13(1.6)	0.34
Opium	105(5)	49(3.7)	56(7)	**<0.001
Temperature (IQR) — °C	37.05 ± 0.96	36.96 ± 0.84	37.18 ± 1.11	**<0.001
Breath rate
14–18	837(41)	579(46)	258(33.1)
18–22	819(40.2)	487(38.7)	332(42.6)
22–28	383(18.8)	193(15.3)	190(24.4)	**<0.001
Pa O2 Saturation %
> 93%	1523(72.7)	820(62.5)	703(88)
≤ 93%	587(27.8)	491(37.5)	96(12)	**<0.001
CT Scan	1864(91.2)	1119(89.5)	745(93.8)	**<0.001
Mechanical Ventilation	200(9.5)	71(5.4)	129(16.1)	**<0.001
Dialysis(N = 103)	28(27.2)	12(25.5)	16(28.6)	0.7
Chemotherapy	18(39.1)	9(40.9)	9(40.9)	0.8
Oxygen Therapy	2013(97.9)	1237(97.9)	776(98)	0.85
Outcome
Discharge Alive	1792(84.9)	560(70.1)	1232(94)
Death	318(15.1)	79(6)	239(29.9)	**<0.001
** P < 0.01, *P < 0.05

Older females and young males were the most frequently admitted to hospital with COIVD-19. The median onset of symptoms length to discharge/death (11.74 ± 6.7 vs 9.48 ± 5.92) and the median length of hospital stay (6.99 ± 5.79 vs. 4.48 ± 4.38) were higher for elderly patients compared to young adults (P < 0.001). Elderly patients with COVID-19 had a higher proportion of comorbidities in comparison to younger patients, with the most common comorbidities including hypertension (58.6%), diabetes (47.4%), cardiovascular disease (29.3%), COPD (15.3%), chronic neurological disease (11.1%), CKD (7%), and cancer (3%) (P < 0.05). Besides, 1.3% of patients with COVID-19 were smokers, of whom 1.6% were elderly. Also, 5% of patients with COVID-19 reported using opium, and elderly (7% vs 3.7%) patients significantly used more opium (P < 0.001). Older patients (88%) had significantly lower oxygen saturation levels than younger patients (62. 5%).while also showing greater evidence of abnormal chest CT (93.8% vs. 89.5%) (P < 0.001). More elderly (16.1%) than young patients (5.4%) were placed on mechanical ventilation. Elderly patients (29.9%) had significantly higher COVID-19 in-hospital mortality than younger patients (5.4%) (P < 0.001), making up 29.9% of the COVID-19 deaths (Table 1).

Table 2 shows the clinical characteristics of hospitalized patients with COVID-19 based on sex

Table 2

Clinical characteristics of hospitalized patients with COVID-19 based on sex
Characteries	Female N = 1144	Male N = 966	P-value
Mean Age	59(42–70)	55(39–71)	0.09
Distribution Age (%)
< 65	200(17.5)	141(14.6)
≥ 65	453(39.6)	346(35.8)	0.07
Hospitalization Length (days)	5.45 ± 5.03	5.41 ± 5.17	**<0.001
Onset of Symptoms Length (days)	5.34 ± 4.01	5.37 ± 3.77	0.18
exposure	809(83.7)	966(84.4)	0.66
Fever	605(52.9)	556(57.6)	*0.032
Cough	615(52.3)	505(53.8)	0.49
Respiratory ‎Distress	928(81.1)	790(81.8)	0.69
Chest Pain	98(8.6)	59(6.1)	*0.03
Stomach ache	38(3.3)	37(3.8)	0.54
Vomiting	126(11.1)	97(10.1)	0.45
Nausea	170(15)	115(11.9)	*0.044
Diarrhoea	80(7)	66(6.8)	0.85
loss appetite	122(10.7)	121(12.6)	0.19
Muscular Pain	638(55.8)	508(52.6)	0.14
Paresis	12(1.5)	6(0.5)	0.9
Plegia‎	0(00)	3(0.3)	0.06
Headache	187(16.4)	150(15.6)	0.58
Dizziness	58(5.1)	33(3.4)	0.06
Unconsciousness	205(17.9)	185(19.2)	0.46
Seizures	3(0.3)	9(0.9)	*0.042
loss of smell	20(51.3)	19(48.7)	0.71
Taste Loss	10(40)	15(60)	0.15
Cardiovascular disease	191(16.7)	154(15.9)	0.64
Hypertension	478(41.8)	257(26.6)	**<0.001
Diabetes mellitus	417(36.5)	227(23.5)	**<0.001
Cancer	22(1.9)	24(2.5)	0.37
Chronic Obstructive Pulmonary Disease	93(8.1)	103(10.7)	*0.046
Chronic Kidney Disease	51(4.5)	52(5.4)	0.32
Asthma	24(2.1)	11(1.1)	0.086
ChronicLiver Disease	14(1.2)	12(1.2)	0.96
Blood Disorder	16(1.4)	12(1.2)	0.75
Chronic Neurological Disease	75(7.8)	74(6.5)	0.247
HIV	2(0.2)	1(0.1)	0.66
Smoke	5(0.4)	23(2.4)	**<0.001
Opium	32(2.8)	73(7.6)	**<0.001
Temperature (IQR) — °C	37.06 ± 0.97	37.04 ± 0.95	0.53
Breath rate
14–18	452(54)	385(46)
18–22	451(55.1)	368(44.9)
22–28	201(52.5)	182(47.5)	0.7
Pa O2 Saturation %
> 93%	822(54)	701(46)
≤ 93%	322(54.9)	265(45.1)	0.7
CT Scan	1011(54.2)	853(45.8)	0.6
Mechanical Ventilation	100(50)	100(50)	0.2
Dialysis(N = 103)	12(42.9)	16(57.1)	0.4
Chemotherapy	9(50)	9(50)	0.8
Oxygen Therapy	1094(54.3)	919(45.7)	0.9
Outcome
Discharge Alive	1005(87.8)	841(87.1)
Death	139(14.3)	125(15.9)	0.76
** P < 0.01, *P < 0.05

The proportion of hospitalization cases for COVID-19 was more in females (54.2%) than males (45. 8%). The median age of men (55 years) at the time of hospitalization was lower than that of women (59 years), but no significant differences were observed. Totally, 84.1% of the patients had contact with definite cases of COVID-19, with women (54.4%) reporting more exposure to people with COVID-19 than men (45.6%), although there were no significant differences. The median length of hospital stay was four days, while there was a significant difference between men and women (Table 1). The most common clinical symptoms were respiratory distress (84.1%), fever (55%), and muscle pain (54.3%), respectively. The most prevalent comorbidities were hypertension (34.8%), diabetes (30.5%), and heart diseases (16.4%), while female patients mainly reported chest pain (8.6%), and nausea (15%) and more men (57.6%) reported fever (P < 0.05). Hypertension (41.8%) and diabetes mellitus (36.5%) were more prevalent among females, while COPD (10.7%), smoking (2.4%), and opium (7.6%) had a higher prevalence among males (P < 0.05) (Table 1). The respiratory rate of 18.8% of patients was between 22 and 28 breaths per minute. Oxygen levels of 72.7% of patients were < 93%, and 91.2% of the patients had lung involvement. Out of the 2110 patients, only 200 (9.5%) needed endotracheal intubation and mechanical ventilation. Out of 103 patients, only 28 (27.2%) needed dialysis treatment. Out of 46 patients, 18 (39.1%) underwent chemotherapy, and the majority of patients (97.9%) needed oxygen therapy. Although the number of dead men was more than women (15.3% vs. 14.9%), mortality was not affected by gender (Table 2).

Table 3 shows the clinical characteristics of patients based on and in hospital outcome.

Table 3

Clinical characteristics of hospitalized patients with COVID-19 based on in-hospital outcome
Characteristics	Discharge N = 1792	Death N = 318	P-value
Mean Age	53.33 ± 18.55	71.78 ± 16.18	**<0.001
Distribution Age (%)
< 65	1232(68.8)	79(24.8)
≥ 65	560(31.3)	239(75.2)	*<0.001
Sex
Male	812(45.3)	154(48.4)
Female	980(54.7)	164(51.6)	0.3
Hospitalization Length (days)	4.65 ± 4.24	9.85 ± 6.98	**<0.001
Onset of Symptoms Length (days)	5.39 ± 3.82	5.2 ± 4.21	0.42
exposure	1491(83.2)	284(89.3)	0.006
Fever	983(54.9)	178(56)	0.39
Cough	966(53.9)	154(48.4)	0.07
Respiratory ‎Distress	1427(79.6)	292(91.5)	**<0.001
Chest Pain	140(7.9)	17(5.3)	0.11
Stomach ache	61(3.4)	14(4.4)	0.38
Vomiting	186(10.4)	37(11.6)	0.5
Nausea	248(13.9)	37(11.6)	0.27
Diarrhoea	135(7.6)	11(3.5)	**0.008
loss appetite	202(11.3)	41(12.9)	0.32
Muscular Pain	1007(52.6)	139(43.7)	**<0.001
Paresis	14(0.8)	4(1.3)	0.130
Plegia‎	2(0.1)	1(0.3)	0.379
Headache	308(17.3)	32(9.1)	**0.002
Dizziness	78(4.4)	13(4.1)	0.817
Unconsciousness	211(11.8)	179(56.3)	**<0.001
Seizures	9(0.5)	3(0.9)	0.335
loss of smell	37(94.9)	2(5.1)	0.08
Taste Loss	25(100)	0(0)	*0.034
Cardiovascular disease	248(13.8)	91(30.5)	**<0.001
Hypertension	551(30.7)	184(57.9)	**<0.001
Diabetes mellitus	475(26.5)	170(53.5)	**<0.001
Cancer	28(1.6)	18(5.7)	**<0.001
Chronic Obstructive Pulmonary Disease	132(7.4)	64(20.1)	**<0.001
Chronic Kidney Disease	63(3.5)	40(12.6)	**<0.001
Asthma	28(1.6)	7(2.2)	0.194
ChronicLiver Disease	23(1.3)	3(0.9)	0.612
Blood Disorder	21(1.2)	7(2.2)	*0.044
Chronic Neurological Disease	95(5.3)	54(17)	**<0.001
HIV	3(0.2)	0(0)	0.376
Smoke	22(1.2)	6(1.9)	0.34
Opium	71(4)	34(10.7)	*0.025
Temperature °C	37.02 ± 0.9	37.2 ± 1.23	**<0.001
Breath rate
14–18	749(43.2)	837(28.7)
18–22	699(40.4)	120(39.1)
22–28	284(16.4)	99(32.2)	**<0.001
Pa O2 Saturation %
> 93%	1231(80.8)	292(19.2)
≤ 93%	561(31.3)	26(8.3)	**<0.001
CT Scan	1559(90.1)	305(97.1)	**<0.001
Mechanical Ventilation	18(1)	182(57.2)	**<0.001
Dialysis(N = 103)	9(14.3)	19(47.5)	**<0.001
Chemotherapy	9(32.1)	9(50)	0.22
Oxygen Therapy	1704(97.9)	309(97.8)	0.8
** P < 0.01, *P < 0.05

Out of all patients, 318 (15.1%) died, whose median age (73 years) was significantly higher than that of recovered patients (54 years). Men (15.2%) died more than women (14.9%), but there were no significant differences in mortality between male and female groups (P > 0.05). The mean duration of hospital stay in the deceased patients was significantly higher than that of recovered patients (P < 0.001) Most of patients who died due to the infection with COVID-19 had contact with a confirmed COVID-19 patient compared with the recovered patients (P = 0.003). The most common clinical symptoms observed more frequently in deceased patients included respiratory distress syndrome and unconsciousness, while complications such as muscular pain and headaches were less frequent (P < 0.01). More patients who died due to the COVID-19 infection suffered from CVD, COPD, and chronic kidney disease (P < 0.001). Most deceased patients with COVID-19 were addicted to opium (P < 0.001). Oxygen saturation levels of most deceased patients were < 93%, and the majority of them had lung involvement. Also, more deceased patients needed endotracheal intubation and mechanical ventilation and dialysis treatment (Table 3).

Table 4 shows comparison Survival time in hospitalized patients with COVID-19 based age, sex, read admission and pandemic waves.

Table 4

Means and median for Survival time in hospitalized patients with COVID-19
	Mean ± SD	95%CI	Median ± SD	95%CI
Age
< 65	19.71 ± 1.29	17.81–22.25	18-0.84	16.35–19.65
≥ 65	16.07 ± 0.64	14.81–17.33	15 ± 0.84	13.33–16.66	**<0.001
Sex
Male	17.31 ± 0.82	15.6–18.9	17 ± 0.82	15.59–18.4
Female	16.2 ± 19.67	16.2-19.67	16 ± 1.19	13.65–18.34	0.26
Group
Non-Readmission	16.3 ± 0.53	15.3–17.3	16 ± 0.89	14.66–17.34
Readmission	22.3 ± 1.76	18.84–25.73	21 ± 1.97	17.14–24.86	**0.005
Wave Pandemic
Frist	17.82 ± 2.51	12.9–2.74	14 ± 1.68	10.71–17.29
Second	17.21 ± 0.92	15.4–19	18 ± 1.084	15.87–20.13
Three	17.7 ± 0.7	16.3–19.2	16 ± 0.73	14.56–17.4
Early of Fourth	9.91 ± 78	7.66–10.72	-	-	0.33
Total	17.91 ± 0.66	16.6–19.2	17 ± 0.64	15.37–18.27
*P < 0.01, Log-Rank Test, Time from admission to discharge/death in hospital

The median 47-day in-hospital survival time of the patients from the onset of symptoms to discharge/death using the Kaplan-Meir method was 25 days (95% CI: 23.40-26.59) (Fig. 1). And the median 43-day in-hospital survival time from admission to discharge/death in hospital was 17 days (95% CI: 15.73–18.27) (Table 4, Fig. 1).

The median length of hospitalization from admission to death/discharge in elderly patients was statistically significantly less ‎than for young patients (P < 0.001) (Table 4, Fig. 1).

Also, the median length of hospitalization from time of admission to death/discharge differed significantly for patients’ readmission and non-readmission (P = 0.006). The median length of hospitalization was higher during the second wave, but there were no statistically significant differences. Females and males did not differ in length of hospitalization. The log-rank test results indicated statistically significant differences in survival curves by age and for patients’ readmission and non-readmission. (Table 4, Fig. 1).

Figure 1 shows Kaplan–Meier curves in hospitalized patients with COVID-19 based on age, sex, read admission and pandemic waves

Table 5 shows sub-group analyses risk factors associated to in-hospital mortality in COVID-19 patients

Table 5

Multivariable logistic regression model for risk factors associated to in-hospital mortality ‎due to COVID-19‎
Variables	18 ≤ Age < 65		Age ≥ 65
Variables	OR(95% CI)	P-value	OR(95% CI)	P-value
CVD	-	-	1.42(1.01–1.98)	0.044
HTN	1.191(1.1–3.32)	0.022	-	-
DM	2.62(1.52–4.51)	< 0.001	1.583(1.15–2.178)	0.005
Cancer	5.57(1.86-16.657)	0.002	2.416(1.023–5.704)	0.44
COPD	-	-	1.955(1.292–2.957)	0.002
CKD	4.12(1.86–9.05)	< 0.001	2.216(1.251–3.928)	0.006
Neurologic	3.916(1.87–8.19)	< .001	2.05(1.289–3.26)	0.002
Opium	2.662(1.112–6.375)	0.028	2.027(1.144–3.593)	0.016
*P < 0.05, OR: Odds Ratio, CI:Confidence Interval

Odds ratios (ORs) obtained from the multivariate logistic regression model were estimated for all clinical characteristics of COVID-19epositive patients (Table 2). Multivariable logistic regression results showed the mortality odds ratio of COVID-19 had been associated with increase age, such that odds of death 3.8 times higher in inpatients aged 65 years or older (odds ratio [OR], 3.819; 95% CI, 2.890–5.046; P < .001). In sub-group analysis by multivariable logistic regression showed in both group aged < 65 and aged ≥ 65 years variables cancer (OR = 3.819; 95% CI, 2.890–5.046 vs OR = 3.819; 95% CI, 2.890–5.046, P < .001), diabetes (OR = 3.819; 95% CI, 2.890–5.046 vs OR = 3.819; 95% CI, 2.890–5.046, P < .001), CKD (OR = 3.819; 95% CI, 2.890–5.046 vs OR = 3.819; 95% CI, 2.890–5.046, P < .001), neurologic disease (OR = 3.819; 95% CI, 2.890–5.046 vs OR = 3.819; 95% CI, 2.890–5.046, P < .001), opium (OR = 3.819; 95% CI, 2.890–5.046 vs OR = 3.819; 95% CI, 2.890–5.046, P < .001), diabetes opium (OR = 3.819; 95% CI, 2.890–5.046 vs OR = 3.819; 95% CI, 2.890–5.046, P < .001) associated with increase odds of death from COVID-19. Also Multivariable logistic regression showed patients aged ≥ 65 years with CVD (OR = 3.819; 95% CI, 2.890-5. 046, P < .001) and patients aged < 65 with hypertension (OR = 3.819; 95% CI, 2.890-5. 046, P < .001) were associated with increased odds of death.

Figure 2 shows a ROC curve analysis was performed for ability to distinguish between hospital discharge or dead patients due to COVID-19.

The area under the ROC curve was 0.809 (95% CI: 0.76–0.83, P < 0.001) to discriminate between discharge or death on hospitalized patients with COVID-19 and indicating a good discrimination for patients ‎with higher risk of in-hospital mortality in COVID-19(Fig. 2).

As of February 7, 2021, in total, 2110 patients with COVID + were admitted to the hospital in the city of Rafsanjan, of whom 318 (15.1%) died while hospitalized. The highest frequency (70.2%) of hospitalized patients with COVID + was reported during the third and early fourth waves.

The mean age of patients in the current study was 56.11 years (SD = 19.37), which was in the reported mean age range of patients in other studies (23).

According to the findings, the in-hospital mortality trend decreased from the first (19.2%) to the second wave (10.7%) and increased ‎significantly during the third wave until as early as one month after the start of the fourth wave ‎‎ (16.3%) (P < 0.01). It was also found that the infected patients aged < 65 years and had lower mortalities in the second wave.

However, we did not have enough knowledge about the course of the disease in the first wave of the disease, when the governments implemented quarantine, social isolation, and closure of public places to control the spread of the COVID-19 disease. The predominant virus in Iran was the Chinese virus from Wuhan in the first three waves of the corona and the British variant in the early fourth wave.

In line with similar previous studies (24, 25), our data showed that in-hospital mortality increased ‎significantly with age as 75.2% of the deaths due to COVID-19 in our data affected patients aged ≥ 65 years, and most hospitalized patients (32.9%) during the first wave also aged ≥ 65 years. The worse prognosis of COVID-19 in elderly patients was associated with a weaker immune response (26), obesity (27), decreased age-related respiratory function (28), weakness (29), multiple diseases (30), and changes related to immune defense (31). Elderly patients may also have unequal access to health care (32).

Our findings showed higher hospitalization rates among females compared with males. However, sex distribution did not differ significantly during the pandemic waves. Similar to previous studies, it was found that the male's in-hospital mortality was higher than females (15.3% vs 14.9%) (13, 31, 33, 34). Scully et al. reported that men were hospitalized and experienced more disease severity and ‎adverse outcomes than women (33). However, consistent with some studies (20, 33), the mortality rate in the COVID-‎‎19 hospitalized patients was not affected by gender.

In-hospital mortality rates were lower in patients with a history of the COVID-19 infection; however, there was no ‎significant ‎relationship. According to observations, most patients had a history of exposure to COVID-19 patients and aged ≥ 65 years with higher mortality rates (89.3%) in the hospital (P < 0.001).

Consistent with similar studies, our data showed respiratory distress (81.4%), fever (55%), muscle pain (54.3%), and cough (53.1%) as common symptoms. In the line some studies, we also found that those aged ≥ 65 years were more likely to report respiratory distress symptom (35) or loss of appetite, and patients aged < 65 were more likely to report muscular pain, diarrhea, and chest pain. Previous studies reported more prevalence of gastrointestinal symptoms in older patients (36), and we found that poor appetite was more common in older patients as compared to the younger ones. As confirmed by reports, older people suffer more from poor appetite at home and care home (37), leading to increased risk of weight loss and nutritional deficiencies (38).

Men were more likely to report fever (57.6%), while women reported chest pain (8.65), nausea (15%), and seizures more (5.1%) (P < 0.05). The prevalence of symptoms of cough, respiratory distress, muscle pain, headache, weakness, and loss of sense of smell was significantly associated with the death from COVID-19. Mean body temperature was significantly higher in males than females and also in older than younger patients. The elderly had a significantly higher breathing rate than younger patients. Our data showed that the need for mechanical ventilation and dialysis was more in older in comparison to younger patients. Previous studies reported that the need for mechanical ventilation treatment increased significantly with increasing age, but Farzan et al. did not find a significant relationship between age groups and the treatment with mechanical ventilation (39). Consistent with the results of the study by Badedas (40) (King 2020), Mortality (90%) Was High In Mechanically Ventilated Patients and most deceased patients with COVID-19 were among those requiring mechanical ventilation and dialysis treatment. Consistent with previous research (36), more than 90% of the hospitalized patients had lung abnormalities, which were more frequent among deceased than recovered patients.

The median overall 47-day and 43-day in-hospital survival times in the hospitalized patients were 25 and 17 days, respectively. Sadeghi et al. reported the median 2-month-survival time from the onset of symptoms to death 30 days (41) and the 180-day survival rate of COVID-19 patients, 59.5% (33). Bobdey et al. reported that 91.4% of patients died within 28 days of the onset of symptoms and deaths occurred in 24.9% of elderly patients (42). We observed no differences in the median length of hospitalization among males and females and pandemic waves in Kaplan Meir method, but the median length of hospitalization in older patients was significantly higher than young patients. Burn et al. also reported that aging was associated with an increased risk of hospitalization and mortality (32). The median length of the hospital stays in dead patients (8.5 days) was twice that of recovered patients (4 days). Our analysis using the cox model showed that the risk of mortality increased during the first to the early fourth wave, but the increase was not significant. The need for health care usually increases with age, while biological differences between men and women lead to different health outcomes, and life expectancy is lower in men than women (43). Different factors such as age structure, history of underlying diseases, etc. affect the median length of patients' survival in different populations. Using the Kaplan-Mayer method, we showed that the median length of hospitalization of re-hospitalized patients was on average 3 days longer than that of once-hospitalized patients, and the difference in median in-hospital survival between re-hospitalized patients was significantly greater (5 days on average) than that of patients who were hospitalized once, and in general, 17% of all deaths occurred among these patients. Also, of the 23.7% of patients who were readmitted, 14% died, and the mortality in these patients was more than those with one hospitalization. One issue in this study was patients who left the hospital with personal consent for reasons such as stress or fear of illness and continued treatment at home but were re-admitted to the hospital due to deteriorating conditions.

In this study, among 39.3% of the COVID-19 patients with comorbidities, the most common comorbidities were hypertension, diabetes, and cardiovascular disease, which was in line with previous studies. After adjustment for significant comorbidities, we found that age significantly increased the odds of deaths due to COVID-19. In elder patients, the odds of mortality were 4.75 times higher (AOR = 4.75, 95%CI = 3.5, 6.4) than those 18 to 65. Previous studies have widely reported age as a strong risk factor for mortality in the COVID-19 similar to MERS-Cov (44). We conducted subgroup analyses using multivariate logistic regression models to explore the effect of comorbidities on mortality in each elderly and young patient. Our findings showed that comorbidities included cancer, diabetes, CKD, and neurologic disease in both age groups, while opium was associated with increased odds of death from COVID-19. Besides, age was shown to be related to underlying disease, significantly increasing the in-hospital mortality of COVID-19.

According to previous studies, multimorbidity diseases are not limited to the elderly (45). The prevalence of various chronic diseases among the elderly and young has increased during the years 2004–2014 (46) and the prevalence of various chronic diseases in studies reported in young people up to 55 years is estimated to be between 20% and 30% and in studies focused on the elderly up to 98% (45). The average Defined Daily Dose for people 35 to 50 years and older has also increased significantly (46).

Other than the common diseases mentioned in the two age groups, we found CVD and COPD in elder patients and hypertension in younger, increasing the odds of deaths of COVID-19. We observed older adults were more likely than younger people to suffer from hypertension, CVD, and diabetes, and the half of deceased patient had hypertension, 28.6% CVD, 26.2% DM. As reported, comorbidities were very common in the elderly than in younger patients (47), and high-prevalence age-related conditions (48, 49). Also, hypertension significantly increases the risk of cardiovascular disease, brain, kidney, and other diseases (https://www.who.int/news-room/fact-sheets/detail/hypertension).

We found that opium remained in the final model and increased odds of mortality in hospitalization in elder and younger patients after adjustment for other risk factors. In our study, 5% of hospitalized patients were opium addicts, and 10.7% of deceased patients used opium. In a study from Rafsanjan cohort study on 9990 adults aged 30–70 years, opium use was reported in 46.19% of males and 4.27% of females (50). Some studies reported patients with opium addicts experienced severity and higher mortality in COVID-19 (51), while some studies have referred to opium use as a serious problem in Iran.

We interpreted the data of admitted COVID-19 patients during one year from the onset of the pandemic in Rafsanjan. Given that the world is exposed to a growing number of epidemic events, and according to the results widely published, indicating that underlying disease and aging increase the severity and mortality of COVID-19 and considering the prevalence of underlying conditions in our society, there is a warning sign that we will face many challenges in the event of an epidemic in the future.

Our study had significant limitations, including insufficient information from the intensive care unit and inadequate laboratory data. Additionally, the body mass index of patients was not recorded. Survival of resuscitation patients may be slightly more skewed than that of patients with a single hospitalization due to discontinuation of the hospitalization time. Additionally, this study was one of the first to comprehensively characterize the age and sex characteristics, as well as hospital outcome factors, of COVID-19 patients and their survival within one year after the COVID-19 pandemic in Rafsanjani city.

Age was a strong risk factor for the death from COVID-19, and we found that the effect of pre-existing chronic diseases on the mortality of COVID-19 varied based on age, but mortality was not affected by the patients' sex. We also found opium was an independent risk factor for death. Therefore, chronic disease management is recommended for both young and old population while monitoring and controlling underlying diseases, especially hypertension, cardiovascular disease, and diabetes, along with the opium use.

Conflict of interest

The authors have no conflicts of interest to declare for this study.

Statement

This manuscript is original, has not been published before, and is not under consideration for ‎publication anywhere.

Acknowledgements

We would like to thank the patients and their families who have given permission to use of their clinical data and also we appreciate the personnel of Ali-Ibn-Abi-Talib Hospital in Rafsanjan city, Iran.

Authors’ contributions: M.MH, F.M performed the data analysis and drafted the manuscript. M.R is the manuscript responsible for the manuscript contents and reviewed the critical manuscript. H.A confirmed the data analysis and review. SM.M and SM.M. reviewed the manuscript. All Authors approved the final version.

Funding: This work was supported by Rafsanjan University of Medical Sciences, Rafsanjan, Iran

Competing Interests: The authors declare that they have no competing interests

Patient and public involvement: In our study patients and/or the public were not involved in plan, manage, design and carry out research. Our study findings are being made publicly available to participants and the general public through the production of study reports and open access journal articles.

Ethics approval and consent to participate

The present study was ethically approved by the Rafsanjan University of Medical Sciences’ ethics committee (ethics code: IR.RUMS.REC.1399.178). All provisions of the Declaration of Helsinki adhered in our study, especially appropriate ethical and scientific review. In this study were used of clinical data of hospitalization patient with COVID-19.

Informed Consent

All patients signed a predefined informed consent specially their clinical data usage.

Availability of Data and Materials

The data that support the findings of this study are available from Rafsanjan University of Medical Sciences but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available.

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No competing interests reported.

Characteristics and Subgroup Analysis of Risk Factors Associated with In-Hospital Mortality among COVID-19 Patients: A Retrospective Cohort Study

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Version 1

Abstract

Figures

Introduction

Materials And Methods

Results

Discussion

Strengths And Weaknesses

Conclusions

Declarations

References

Additional Declarations

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Version 1