The Effect of Anti-coagulation Dosage on the Outcome of Hospitalized COVID-19 Patients in Ethiopia

A Multi-Center Retrospective Cohort Study

Abel Girma Tessema; Zekarias Masresha Mengiste; Tsegaye Gebreyes Hundie; Hailemichael Getachew Yosef; Dawit Kebede Huluka; Abebaw Bekele Seyoum; Hannibal Kassahun Abate; Rawleigh Craig Howe

Disclosures

BMC Pulm Med. 2023;23(85)

Results

Socio-demographic and Baseline Clinical Characteristics

In this study, a total of 472 patients diagnosed with COVID-19 were included. Among the study participants, 50.2% (237 patients) received a prophylactic dose of anticoagulation and 49.8% (235 patients) received a therapeutic dose of anticoagulation. The median age of the study subjects in the prophylactic and therapeutic groups was 59 years (IQR = 45.5 – 67.0) and 60 years (IQR = 48.0 – 67.0) respectively. There was a uniform distribution of underlying comorbidities in both groups with no statistically significant difference. The five commonest comorbidities included hypertension, diabetes, HIV/AIDS, asthma and stroke. Forty-six per cent (217 patients) required mechanical ventilation at some point during their hospital stay. In terms of COVID-19 severity, there was no statistically significant difference between the two cohort groups (p = 0.261). In addition, there was no statistically significant difference in vital signs at presentation, with the exception of respiratory rate, which was higher for the therapeutic arm (p < 0.001). Regarding baseline laboratory measurements, the only value which had statistically significant difference between the two groups was blood urea level [median = 32.50, IQR (21.3 – 46.5) in the prophylactic group vs [24.30, IQR (16.1 – 37.1) in the therapeutic group; p = 0.001]. Table 1 summarizes the demographic and baseline clinical characteristics of the study participants.

In-hospital Mortality in Hospitalized COVID-19 Patients

Among the 472 patients included in this study, 154 (32.6%) of them died during their hospital stay. All-cause in-hospital mortality was higher in the therapeutic cohort (37%, n = 88) as compared to the prophylactic cohort (28%, n = 66) (RR 1.35, 95% CI, 1.03—1.75, p = 0.027).

We used a multivariable binary logistic regression model to control for the contribution of several clinical and demographic variables. Among these, those which showed an association with in-hospital mortality (p < 0.25) in a univariate analysis were older age (> 60 years), not receiving at least one dose of COVID-19 vaccine, presence of hypertension, history of stroke, presence of malignancy, a higher level of severity of COVID-19 at admission and receiving therapeutic dosage of anticoagulation. After adjusting for these potential confounding variables, therapeutic dose of anticoagulation was still significantly associated with a higher inpatient mortality (AOR 1.70, 95% CI, 1.02 – 2.84, p = 0.042). Other factors which remained significantly associated with a higher inpatient mortality after multivariable logistic regression analysis included: older age (> 60 years), not receiving at least one dose of COVID-19 vaccine, presence of malignancy, and a higher level of COVID-19 severity (p < 0.05). Table 2 below displays the outcome of the binary logistic regression model with odds ratio for in-hospital mortality before and after adjustment for potential confounders (only variables with p < 0.25 in univariate analysis are shown in the table).

We did a subgroup analysis using multivariable binary logistic regression for in-hospital mortality to further account for the severity of COVID-19. In severe COVID-19 patients, there was no statistically significant difference between in-hospital mortality and anticoagulation dosage, where the odds of inpatient mortality in the therapeutic cohort was 1.02 (95% CI, 0.45 – 2.33); p = 0.958. On the other hand, on the critical COVID-19 subgroup, therapeutic anticoagulation was significantly associated with a higher inpatient mortality (AOR 2.27, 95% CI, 1.18 – 4.35, p = 0.013), when compared to prophylactic anticoagulation.

To further control confounders and see the effect of anticoagulation dosage on the time to death, we utilized a multivariable Cox regression analysis model. In the univariate Cox regression model, the potential predictors of mortality (p < 0.25) included: older age, not receiving at least one dose of COVID-19 vaccine, hypertension, a higher level of severity of COVID-19 at admission, a higher demand of oxygen supplementation at admission and receiving therapeutic dosage of anticoagulation. After adjusting for these confounding variables, patients who received therapeutic dose of anticoagulation had significantly higher risk of death compared to prophylactically anticoagulated patients (AHR 1.41, 95% CI, 1.01 – 1.96, p = 0.042) in multivariable Cox regression model. This effect was found to be more pronounced in a subgroup analysis done among critical COVID-19 patients (AHR 1.57, 95% CI, 1.09—2.27, p = 0.015). However, there was no significant difference between the groups in the severe COVID-19 subset of patients, (HR 0.86, 95% CI 0.38—1.92, p = 0.711). Cox regression analyses done for in-hospital mortality is summarized in Table 3 and Figure 1.

(Enlarge Image)

Figure 1.

Cox proportional hazard cumulative survival plot. Left: survival plot severe COVID-19 patients receiving prophylactic vs therapeutic dose anticoagulation after adjusting for the listed confounders; Right: a survival plot for the critical subgroups

Length of Hospital Stay Among Survivors

Among the 472 patients enrolled in this study, 300 patients (63.6%) were discharged improved, 154 patients (32.6%) were deceased in the hospital and the remaining 18 patients (3.8%) were transferred to another health facility. To evaluate the length of stay among survivors, we again used a multivariable Cox regression analysis model, censoring deceased patients and those transferred to another health facility.

On univariate Cox regression analysis, variables associated with a longer hospital stay (p < 0.25) included: older age, male sex, not receiving at least one dose of COVID-19 vaccine, history of stroke, a higher admission respiratory rate, a higher level of COVID-19 severity at admission, a higher oxygen demand at admission, and receiving therapeutic dosage of anticoagulation. After correction for these variables, the multivariable Cox regression analysis model indicated that therapeutic dose of anticoagulation was independently associated with a longer hospital stay as compared to prophylactic dose of anticoagulation (AHR 0.70, 95% CI, 0.55—0.91; p = 0.006).

After stratification of patients based on COVID-19 severity, this effect was more prominent among the severe subgroup of patients (AHR 0.76, 95% CI, 0.59—0.98, p = 0.033) and was lost for the critical subgroup (HR 0.61, 95% CI, 0.36 – 1.04, p = 0.069). The following tables displays the Cox regression analysis summary of factors affecting the length of hospital stay in severe and critical COVID-19 patients (Table 4).

Thrombotic and Bleeding Complications in Hospitalized COVID-19 Patients

Forty-two patients (8.90%) were clinically diagnosed with thrombosis during their hospital stay. Of these, 26 (62%) received a prophylactic dose of anticoagulation and 16 (38%) received a therapeutic dose. One patient was diagnosed with both pulmonary thrombo-embolism (PTE) and deep vein thrombosis (DVT). Two patients were diagnosed with both PTE and myocardial infarction (MI). One patient was diagnosed with PTE and acute limb ischemia. Confirmed diagnosis of thrombosis using definitive investigation modalities was achieved on only 13 patients (5.49%) of patients in the prophylactic group and 5 patients (2.13%) in the therapeutic group. The majority of these (two thirds) were venous thromboembolism (i.e., PTE and DVT). Therapeutic anticoagulation modestly decreased the incidence of definitive thrombosis in comparison with prophylactic anticoagulation (RR 0.39, 95% CI, 0.14—1.07, p = 0.07); however, this association reached only borderline statistical significance. The difference in the incidence of thrombosis for severe subgroup of patients was relatively more pronounced (8 thrombosis in the prophylactic group vs. 1 in the therapeutic group; p = 0.038), although this difference was lost in further multivariable binary logistic regression analysis (AOR 0.15, 95% CI, 0.02 – 1.20, p = 0.073). However, this might have some clinical value despite it being statistically non-significant. For critical subgroup, 5 patients (2.1%) from the prophylactic cohort developed thrombotic events as compared to 4 patients (1.7%) from the therapeutic cohort (OR 0.69, 95% CI, 0.18 – 2.67, p = 0.595).

The overall proportion of patients with bleeding events were 2.97% (n = 14). Among these only 43% (n = 6) were major or minor and clinically significant which resulted in either temporary or permanent discontinuation of anticoagulant. Comparing the two groups, patients who received therapeutic dose of anticoagulation had significantly higher bleeding risk as compared to prophylactic dose of anticoagulation [6 patients vs. 0 patient; p = 0.015].

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Table 1. Demography, baseline characteristics and clinical variables of hospitalized COVID-19 patients in Ethiopia
		Prophylactic anticoagulation (n = 237)	Therapeutic anticoagulation (n = 235)	p-value
Hospital	Eka-Kotebe General Hospital	83 (35.0%)	91 (38.7%)	0.648
	Millennium COVID-19 Care Center	99 (41.8%)	96 (40.9%)
	COVID-19 St. Peter's Field Hospital	55 (23.2%)	48 (20.4%)
Age in years, median (IQR)		59.00 (45.5 – 67.0)	60.00 (48.0 – 67.0)	0.711
Gender	Male, n (%)	154 (65.0%)	135 (57.4%)	0.108
Gender	Female, n (%)	83 (35.0%)	100 (42.6%)	0.108
Comorbidity, n (%)
Hypertension		85 (35.9%)	83 (35.3%)	0.924
Diabetes Mellitus		76 (32.1%)	74 (31.5%)	0.921
HIV/AIDS		11 (4.6%)	12 (5.1%)	0.834
Asthma		10 (4.2%)	13 (5.5%)	0.508
Stroke		7 (3.0%)	5 (2.1%)	0.772
Malignancy		2 (0.84%)	5 (2.1%)	0.284
Ischemic Heart Disease		3 (1.3%)	4 (1.7%)	0.724
Prior history of Tuberculosis		2 (0.8%)	5 (2.1%)	0.284
Chronic Kidney Disease		4 (1.69%)	1 (0.43%)	0.372
Chronic Liver Disease		2 (0.8%)	1 (0.43%)	1.000
Schizophrenia		0 (0.0%)	3 (1.3%)	0.123
Smoking, n (%)		3 (1.3%)	6 (2.6%)	0.337
COVID-19 Severity at admission, n (%)
Severe		147 (62.0%)	133 (56.6%)	0.261
Critical		90 (38.0%)	102 (43.4%)	0.261
Type of Oxygen therapy used at admission, n (%)				0.021
Nasal cannula		107 (45.1%)	80 (34.0%)
Simple Face mask		40 (16.9%)	53 (22.6%)
Face mask with reservoir		28 (11.8%)	41 (17.4%)
Non-invasive ventilation		53 (22.4%)	44 (18.7%)
Invasive ventilation		9 (3.8%)	17 (7.2%)
Vital Sign, median (IQR)
Heart rate, bpm		94.00 (86.0 – 106.0)	94.00 (83.0 – 105.0)	0.221
Respiratory rate, rate/min		28.00 (24.0 – 32.0)	31.00 (26.0 – 36.0)	< 0.001
Diastolic blood pressure, mm Hg		75.00 (67.0 – 83.5)	72.00 (65.0 – 80.0)	0.095
Systolic blood pressure, mm Hg		126.00 (111.5 – 145.0)	129.00 (112.0 – 142.0)	0.958
Laboratory values, median (IQR)
Hemoglobin, g/dL		14.10 (13.0 – 15.5)	14.05 (13.0 – 15.3)	0881
Hematocrit, %		41.60 (38.4 – 45.2)	42.00 (38.5 – 45.0)	0.553
Total WBC count, × 10 ³/mL		9.60 (6.4 – 11.9)	8.94 (6.4 – 13.1)	0.831
Neutrophil, %		87.50 (81.0 – 92.0)	89.85 (81.5 – 92.4)	0.144
Lymphocyte, %		6.35 (3.7 – 10.4)	6.30 (3.9 – 10.6)	0.745
Platelet count, 10 ⁹/L		244.50 (175.8 – 315.0)	234.00 (167.5 – 310.8)	0.622
Alanine aminotransferase, U/L		40.60 (25.6 – 65.1)	31.95 (22.8 – 62.5)	0.479
Aspartate aminotransferase, U/L		40.95 (29.1 – 62.2)	38.00 (27.1 – 60.1)	0.887
Creatinine, mg/dL		0.72 (0.62 – 0.90)	0.80 (0.60 – 1.0)	0.112
Urea, mg/dL		32.50 (21.3 – 46.5)	24.30 (16.1 – 37.1)	0.001
Sodium, mmol/L		138.00 (134.0 – 140.0)	137.00 (133.0 – 140.0)	0.456
Potassium, mmol/L		4.26 (3.90 – 4.70)	4.10 (3.70 – 4.60)	0.055

Table 2. Binary logistic regression analysis with odds ratio for in-hospital mortality
		Inpatient mortality, n (%)	Total	Crude OR (95% CI)	p-value	Adjusted OR (95% CI)	p-value
Age	< 60 yrs	66 (24.1%)	274
Age	> 60 yrs	88 (44.4%)	198	2.52 (1.70–3.74)	< 0.001	2.74 (1.60–4.69)	< 0.001
Vaccine status	Not received	149 (33.7%)	442
Vaccine status	Received at least 1 dose	5 (16.7%)	30	0.39 (0.15–1.05)	0.062	0.23 (0.07–0.84)	0.025
Hypertension	No	89 (27.4%)	304
Hypertension	Yes	65 (38.0%)	168	1.52 (1.03–2.27)	0.037	1.52 (0.87–2.65)	0.139
History of Stroke	No	148 (32.2%)	460
History of Stroke	Yes	6 (50.0%)	12	2.11 (0.67–6.65)	0.203	2.44 (0.47–12.52)	0.286
Malignancy	No	148 (31.8%)	465
Malignancy	Yes	6 (85.7%)	7	12.85 (1.53–107.71)	0.019	19.70 (1.52–255.44)	0.023
COVID-19 Severity	Severe	25 (8.9%)	280
COVID-19 Severity	Critical	129 (67.2%)	192	20.56 (12.55–34.76)	< 0.001	23.37 (13.45–40.62)	< 0.001
Anticoagulation dosage	Prophylactic	66 (27.8%)	237
Anticoagulation dosage	Therapeutic	88 (37.4%)	235	1.55 (1.05–2.29)	0.027	1.70 (1.02–2.84)	0.042

Table 3. Cox proportional hazard model for in-hospital mortality
	Crude HR (95% CI)^a	p-value	Adjusted HR (95% CI)^a	>p-value
Age^b	1.03 (1.02—1.04)	< 0.001	1.03 (1.02—1.04)	< 0.001
Vaccination Status	0.52 (0.21—1.26)	0.145	0.43 (0.17—1.06)	0.067
Hypertension	1.48 (1.07 – 2.04)	0.017	1.25 (0.90—1.75)	0.188
COVID-19 Severity	6.63 (4.31 – 10.10)	< 0.001	9.03 (4.30 – 18.99)	< 0.001
Anticoagulation dosage	1.23 (0.89 – 1.69)	0.215	1.41 (1.01 – 1.96)	0.042

^aHazard ratios of in-hospital mortality before and after adjusting for potential confounders given (only variables with p < 0.25 in univariate analysis are included)
^bAll independent variables are categorical except age which is continuous

Table 4. Cox regression analysis for length of hospital stay
Covariates	Severe		Covariates	Critical
Covariates	Adjusted HR (95% CI)	p-value	Covariates	HR (95% CI)	p-value
Anticoagulation dosage	0.76 (0.59 – 0.98)	0.033	Anticoagulation dosage	0.61 (0.36 – 1.04)	0.069
Age	0.99 (0.98 – 1.00)	0.047
Gender (male sex)	1.21 (0.93 – 1.58)	0.151
Stroke	0.32 (0.12 – 0.88)	0.027

Left: subgroup analysis for severe patients, Right: subgroup analysis for critical patients. (Variables with p < 0.25 in univariate analysis are included)