AB0710 ANISOCYTOSIS INDEX AS AN EARLY PREDICATOR OF HOSPITAL MORTALITY IN PATIENTS WITH COVID-19 PNEUMONIA FROM A LEVEL III HOSPITAL. LIMA PERU
Authors: J. Ravelo
Journal: Annals of the Rheumatic Diseases (2021)

Background: RDW has been analyzed in recent decades as a poor prognostic factor, associated with an increased risk of mortality from all causes: heart disease, lung disease, sepsis, influenza, cancer, complications associated with heart failure, coronary disease, viral hepatitis, COPD, development of DM2, stroke and anemia, which makes it a nonspecific marker of disease with the potential to provide a stratified quantification of risk in a new disease. Objectives: To determine if laboratory tests predict mortality in patients with COVID-19 pneumonia upon admission to hospital. Secondary outcome: evaluate if any laboratory parameter predicts longer hospitalization in patients with COVID-19 pneumonia. Methods: Case control retrospective study of COVID-19 pneumonia patients, admitted to the Peruvian Air Force Hospital from April 6th to June 27th, 2020. Patients were divided in two groups: recovered and deceased and their laboratory parameters entered the statistical analysis. Cox regression was performed (95% CI, p value &lt;0.05, as statistically significant). Bivariate analysis to compare the RDW means of recovered vs. deceased and multivariate analysis with binary logistic regression to evaluate the predictive value of RDW in relation to hospital mortality in our cohort. The statistical package Stata version 14.2 was used. Results: 186 patients were included. The mean age of the recovered patients was 53.6 ± 16.4 years vs 75.9 ± 13.9 years in the deceased group (p &lt;0.0001). The mean value of RDW was 13.14% in recovered vs. 13.96% of deaths (p&lt; 0.0005), associated with an Odds Ratio (OR) of 1.66 (CI: 1.58-1.74) adjusted for the model. Conclusion: The finding of a RDW ≥ 13% in patients with COVID-19 pneumonia was associated with higher mortality. References: [1]Imam Z, Odish F, Gill I, O’Connor D, Armstrong J, Vanood A, et al. Older age and comorbidity are independent mortality predictors in a large cohort of 1305 COVID-19 patients in Michigan, United States. J Intern Med. 2020 Jun 22. DOI: 10.1111/joim.13119 [2]Foy BH,……. Table 1. Characteristics and comorbidities in patients with COVID-19 Pneumonia Total (N:188 ) Recovered (n:147 ) Death (n:41 ) P Age(years ) Media (DS) 59.79 (17.48) 55.32 (15.64) 75.80 (14.15) &lt; 0.000 * Sex Femenino 81 (43.09 %) 64 (79.01 %) 17 (20.99 %) 0.813 Masculino 107 (56.91 %) 83 (77.57 %) 24 (22.43 %) Hypertension No 145 (77.13 %) 119 (82.07 %) 26 (17.93 %) 0.018 Si 43 (22.87%) 28 (65.12 %) 15 (34.88 %) Diabetes mellitus No 158 (84.04 %) 124 (78.48 %) 34 (21.52 %) 0.825 Si 30 (15.96 %) 23 (76.67 %) 7 (23.33) ESRD No 179 (95.21 %) 143 (79.89 %) 36 (20.11 %) 0.012 Si 9 (4.79 %) 4 (44.44 %) 5 (55.56 %) Asthma No 183 (97.34 %) 145 (79.23 %) 38 (20.77 %) 0.036 Si 5 (2.66 %) 2 (40 %) 3 (60 %) Obesity No 181 (96.28 %) 142 (78.45 %) 39 (21.55 %) 0.659 Si 7 (3.72 %) 5 (71.43 %) 2 (28.57 %) Other comorbidities No 133 (71.12 %) 114 (85.71 %) 19 (14.29 %) &lt; 0.000 Si 54 (28.88 %) 32 (59.26 %) 22 (40.74 %) Leukocytes Media (DS) 9.68 (4.44) 9.49 (4.52) 10.35 (4.13) 0.281* Lymphocytes Media (DS) 1.44 (0.88) 1.59 (0.90) 0.90 (0.53) &lt; 0.000* CRP Media (DS) 94.04 (95.61) 82.34 (88.95) 136.48 (107.50) 0.001* pO2 Media (DS) 83.73 (24.39) 83.94 (22.28) 82.98 (31.18) 0.827* pCO2 Media (DS) 33.40 (5.06) 33.32 (4.96) 33.67 (5.47) 0.699* Sat O2 Media (DS) 95.73 (8.74) 95.23 (5.10) 97.55 (16.09) 0.138* Admission days Media (DS) 11.75 (9.04) 10.88 (7.08) 14.82 (13.59) 0.013* TSS Score Media (DS) 7.33 (3.50) 6.59 (3.03) 10.05 (3.80) &lt; 0.000** RDW Media (DS) 13.323 (1.284) 12.971 (1.081) 13.411(1.715) &lt;0.003** Table 2. Multivariate Analysis Using Binary Logistic Regression to Predict Mortality Adjusted OR p CI 95% RDW 1.67 0.004 1.18 –2.35 Lymphocytes 0.27 0.012 0.09 – 0.74 Age 1.08 &lt; 0.001 1.04 – 1.13 Disclosure of Interests: Jorge Ravelo Speakers bureau: Less than 10 speech for Grunenthal and Novartis, Paid instructor for: 1 time for Riverpharma, Grant/research support from: I am working as PI doing sponsored clinical trials since 2008