The Role of the De Ritis Ratio in ICU Mortality Among Critically Ill Patients with COVID-19

Hüseyin Özkök, Şeyma Şenocak, Özlem Aktürk, Ahmed Cihad Genç, Deniz Çekiç, Yusuf Durmaz, Ahmed Bilal Genç, Selçuk Yaylacı

Volume 9 · Issue 2 · pp. 427–434

Published: 2026-06-30

Abstract

Objective: The De Ritis ratio (aspartate aminotransferase/alanine aminotransferase) has emerged as a prognostic biomarker in critical illness. This study aimed to evaluate the independent prognostic value of the De Ritis ratio for ICU mortality in critically ill patients with COVID-19. Methods: This retrospective observational cohort study was conducted at a single tertiary center. Medical records of 642 adult patients with RT-PCR–confirmed COVID-19 admitted to the Internal Medicine ICU between January and December 2021 were reviewed. Demographic data, comorbidities, laboratory parameters, severity scores (APACHE II and SOFA), and organ support requirements were recorded at ICU admission. Patients were stratified into survivor and non-survivor subgroups. Independent predictors of ICU mortality were identified through two multivariable logistic regression models. Discriminative performance was assessed by receiver operating characteristic curve analysis. Results: ICU mortality was recorded in 341 patients (53.1%). Non-survivors were significantly older and had markedly elevated inflammatory biomarkers, D-dimer, urea, and De Ritis ratio values. Although absolute AST and ALT concentrations did not differ significantly between groups, the De Ritis ratio was independently associated with ICU mortality in both models (Model A: OR 1.27, 95% CI 1.06–1.51, p = 0.009; Model B: OR 1.26, 95% CI 1.05–1.50, p = 0.013). Combining the De Ritis ratio with severity scores improved discriminative performance (AUC up to 0.661). Conclusion: The De Ritis ratio at ICU admission was independently associated with mortality in critically ill COVID-19 patients and provided additional prognostic information beyond established severity scores. Given its modest discriminative performance, it should be interpreted as a supplementary rather than a standalone prognostic marker.

Keywords: COVID-19; De Ritis ratio; ICU mortality

1. Introduction

Multiorgan involvement is a defining pathophysiological feature of severe coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The predilection of SARS-CoV-2 for extrapulmonary tissues is largely attributable to the ubiquitous expression of angiotensin-converting enzyme 2 (ACE2)—its principal cellular receptor—across anatomically diverse sites including the myocardium, hepatic parenchyma, renal tubules, intestinal epithelium, and vascular endothelium1,2, conferring a systemic vulnerability that fundamentally distinguishes COVID-19 from classical respiratory viral syndromes.

A dysregulated and self-amplifying cytokine cascade, compounded by endothelial activation and coagulopathy, precipitates organ failure at sites remote from the primary pulmonary focus3. Hepatic involvement ranks among the most frequently encountered extrapulmonary complications, with abnormal liver enzyme concentrations documented in 14–53% of hospitalised patients4. The pathogenesis of this hepatic derangement is multifactorial, encompassing direct viral cytopathic effects on hepatocytes, cytokine storm-mediated hepatitis, hypoxia-driven ischaemia–reperfusion injury, and pharmacological hepatotoxicity5.

Conventional hepatic monitoring focuses on absolute alanine aminotransferase (ALT) and aspartate aminotransferase (AST) values, yet the ratio of AST to ALT—the De Ritis ratio—carries prognostic information that neither enzyme alone conveys. First described in 1957 as a tool for viral hepatitis classification6, the De Ritis ratio has subsequently been validated as a mortality-associated biomarker across a spectrum of critical conditions including sepsis, acute respiratory distress syndrome (ARDS), and cardiovascular disease7,8. Accumulating evidence from COVID-19 cohorts indicates that an elevated De Ritis ratio at the time of initial presentation correlates with heightened disease severity, escalating therapeutic demands, and reduced likelihood of survival9. Its derivability from universally available routine laboratory data, without imposing any additional diagnostic burden, renders it a highly practicable candidate for early prognostic stratification10. Against this background, the present investigation sought to determine whether the De Ritis ratio at ICU admission constitutes an independent prognostic determinant of mortality in critically ill patients with confirmed COVID-19.

2. Materials and Methods

We performed a retrospective cohort analysis at a single tertiary-care center. Medical records of 642 adults aged 18 years or above admitted to the Internal Medicine ICU of Sakarya University Training and Research Hospital between January and December 2021 were reviewed. Entry into the study required both RT-PCR–confirmed SARS-CoV-2 infection and a complete set of clinical and biochemical data available at ICU admission. Exclusion criteria included age below 18 years, unavailable clinical or laboratory records, death preceding formal ICU admission or occurring within the initial 24-hour period of ICU stay, and concurrent terminal malignancy or pregnancy.

Demographic data, chronic comorbid conditions, laboratory and hematological results at ICU admission, ventilatory support requirements, vasopressor and inotropic therapy, and definitive ICU outcome were extracted. Acute illness severity was quantified using the Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) scoring systems. The De Ritis ratio was defined as the quotient of AST to ALT at ICU admission. Patients were allocated to survivor or non-survivor subgroups based on ICU outcome.

2.1. Statistical Analysis

Baseline characteristics were summarised using standard descriptive measures. Continuous variables satisfying the normality assumption were characterised as mean ± SD; all others as median (IQR). Normally distributed variables were compared using the independent-samples t-test; the Mann–Whitney U test served as the non-parametric counterpart. Categorical variables were compared by chi-square testing. Independent determinants of ICU mortality were identified through two multivariable logistic regression models: Model A combined the APACHE II score with the De Ritis ratio, while Model B substituted the SOFA score. Calibration was checked with the Hosmer–Lemeshow test; discriminatory capacity was evaluated by ROC curves and AUC values. Two-tailed p values below 0.05 were considered statistically significant. All computations were carried out using IBM SPSS Statistics, version 22.0.

The study protocol was approved by the Clinical Research Ethics Committee of Sakarya University Faculty of Medicine (Approval Date: March 25, 2023; Decision No: 115). The study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Due to the retrospective design and use of anonymised patient data, the requirement for written informed consent was waived.

3. Results

A total of 642 COVID-19 patients admitted to the Internal Medicine ICU were eligible for analysis. ICU survival was achieved by 301 patients (46.9%); the remaining 341 (53.1%) died. Mean age was 69.50 ± 14.18 years. Non-survivors were modestly older (70.82 ± 14.34 vs. 68.01 ± 13.86 years; p = 0.012). Sex distribution was identical in both groups. Demographic and comorbidity data are given in Table 1.

Table 1. Baseline demographic characteristics and comorbidities at ICU admission

Table 1

Variable Survivors (n=301) Non-survivors (n=341) Total (N=642) p
Age (years) 68.01±13.86 70.82±14.34 69.50±14.18 0.012
Female sex, n (%) 136 (45.2) 154 (45.2) 290 (45.2) 0.995
Malignancy, n (%) 18 (6.0) 52 (15.3) 70 (10.9) <0.001
DM, n (%) 104 (34.6) 107 (31.4) 211 (32.9) 0.393
HT, n (%) 156 (51.8) 187 (54.8) 343 (52.0) 0.445
Coronary artery disease, n (%) 70 (23.3) 98 (28.7) 168 (26.2) 0.115
Heart failure, n (%) 29 (9.6) 42 (12.3) 71 (11.1) 0.280
COPD, n (%) 21 (7.0) 35 (10.3) 56 (8.7) 0.140
Asthma, n (%) 11 (3.7) 15 (4.4) 26 (4.0) 0.633
CKD, n (%) 27 (9.0) 41 (12.0) 68 (10.6) 0.209

Data are presented as mean ± SD or n (%). DM: diabetes mellitus; HT: hypertension; COPD: chronic obstructive pulmonary disease; CKD: chronic kidney disease.

Malignancy was markedly more prevalent among non-survivors (15.3% vs. 6.0%; p < 0.001; OR: 2.83; 95% CI: 1.62–4.96). Vasopressor therapy was required far more frequently among non-survivors (59.2% vs. 29.9%; OR: 3.41; 95% CI: 2.43–4.78; p < 0.001), as was invasive mechanical ventilation (72.4% vs. 21.9%; OR: 9.35; 95% CI: 6.50–13.45; p < 0.001). Results for all pharmacological and mechanical support interventions are detailed in Table 2.

Table 2. Association between pharmacological and mechanical support interventions and ICU mortality

Table 2

Clinical Intervention Survivors (n=301) Non-survivors (n=341) Total (N=642) OR (95% CI) p
Vasopressor use, n (%) 90 (29.9) 202 (59.2) 292 (45.5) 3.41 (2.43–4.78) <0.001
Inotropic support, n (%) 41 (13.6) 76 (22.3) 117 (18.2) 1.83 (1.22–2.76) 0.004
Invasive mechanical ventilation, n (%) 66 (21.9) 247 (72.4) 313 (48.8) 9.35 (6.50–13.45) <0.001
Non-invasive ventilation, n (%) 52 (17.3) 117 (34.3) 169 (26.3) 2.49 (1.71–3.62) <0.001
High-flow nasal oxygen, n (%) 45 (15.0) 96 (28.2) 141 (22.0) 2.23 (1.48–3.36) <0.001

Data are presented as n (%). ORs calculated using univariate logistic regression. OR: odds ratio; CI: confidence interval.

Routine blood count indices showed no statistically significant variation between outcome groups. Inflammatory markers diverged sharply: IL-6, CRP, and ferritin were each significantly higher in patients who died (p = 0.006, p = 0.002, and p = 0.023). Absolute AST and ALT values were comparable between outcome groups (AST: p = 0.177; ALT: p = 0.497). The De Ritis ratio was significantly higher in non-survivors (1.82 ± 0.99 vs. 1.60 ± 0.86; p = 0.003). Full laboratory results are in Table 3.

Table 3. Comparison of laboratory parameters at ICU admission between survivors and non-survivors

Table 3

Parameter Survivors (n=301) Non-survivors (n=341) Total (N=642) p
Leukocyte (×10³/μL) 10.70±11.42 11.25±7.34 10.99±9.48 0.469
Lymphocyte (×10³/μL) 0.84±0.93 1.03±2.05 0.94±1.63 0.121
Neutrophil (×10³/μL) 9.16±10.00 9.64±6.61 9.41±8.37 0.470
Hemoglobin (g/dL) 12.00±2.11 11.93±2.14 11.97±2.13 0.661
Platelet (×10³/μL) 235.54±105.00 222.11±103.70 228.41±104.44 0.104
D-dimer (ng/mL) 731 (503–1840) 1050 (559–2215) 890 (540–2030) 0.003
Ferritin (ng/mL) 641 (279–1474) 900 (432–2000) 770 (350–1800) 0.023
IL-6 (pg/mL) 38 (19–96) 58 (24–141) 48 (21–118) 0.006
CRP (mg/L) 93 (54–154) 110 (64–180) 101 (58–170) 0.002
LDH (U/L) 456 (331–590) 485 (376–625) 470 (350–610) 0.058
Urea (mg/dL) 57 (42–88) 67 (45–100) 62 (44–94) 0.006
Creatinine (mg/dL) 1.27±1.36 1.47±1.35 1.37±1.35 0.063
Albumin (g/L) 30.03±4.55 29.08±5.13 29.52±4.89 0.011
Globulin (g/L) 22.77±12.84 24.09±14.13 23.47±13.55 0.219
CK-MB (U/L) 27.10±18.83 31.84±30.67 29.63±25.92 0.022
AST (U/L) 37 (26–55) 39 (26–61) 38 (26–58) 0.177
ALT (U/L) 26 (15–47) 25 (15–44) 25 (15–45) 0.497
De Ritis ratio 1.60±0.86 1.82±0.99 1.72±0.94 0.003

Data are presented as mean ± SD or median (IQR). IL-6: interleukin-6; CRP: C-reactive protein; LDH: lactate dehydrogenase; CK-MB: creatine kinase–myocardial band; AST: aspartate aminotransferase; ALT: alanine aminotransferase.

Severity score values were substantially higher among non-survivors: APACHE II 19.07 ± 7.37 vs. 15.60 ± 7.06 (p < 0.001), and SOFA 6.80 ± 2.72 vs. 5.35 ± 2.55 (p < 0.001) (Table 4).

Table 4. Comparison of prognostic scoring systems between survivors and non-survivors

Table 4

Parameter Survivors (n=301) Non-survivors (n=341) Total (N=642) p
APACHE II score 15.60±7.06 19.07±7.37 17.44±7.43 <0.001
SOFA score 5.35±2.55 6.80±2.72 6.12±2.74 <0.001
De Ritis ratio 1.60±0.86 1.82±0.99 1.72±0.94 0.003

Data are presented as mean ± SD. APACHE II: Acute Physiology and Chronic Health Evaluation II; SOFA: Sequential Organ Failure Assessment.

Multivariable logistic regression established the De Ritis ratio as an independent predictor of ICU mortality across both models. In Model A, APACHE II (OR: 1.07; 95% CI: 1.05–1.09; p < 0.001) and De Ritis ratio (OR: 1.27; 95% CI: 1.06–1.51; p = 0.009) each retained significance. Model B yielded analogous findings for SOFA (OR: 1.23; 95% CI: 1.16–1.30; p < 0.001) and De Ritis ratio (OR: 1.26; 95% CI: 1.05–1.50; p = 0.013) (Table 5).

Table 5. Multivariable logistic regression analysis for ICU mortality

Table 5

Model Variable OR (95% CI) p
Model A APACHE II score 1.07 (1.05–1.09) <0.001
De Ritis ratio 1.27 (1.06–1.51) 0.009
Model B SOFA score 1.23 (1.16–1.30) <0.001
De Ritis ratio 1.26 (1.05–1.50) 0.013

OR: odds ratio; CI: confidence interval.

Standalone ROC analysis demonstrated modest but significant discrimination for the De Ritis ratio (AUC: 0.562; 95% CI: 0.517–0.606; p = 0.007). When incorporated into composite models, performance improved: AUC 0.652 (95% CI: 0.609–0.694) for the APACHE II–based model and 0.661 (95% CI: 0.619–0.703) for the SOFA-based model (Table 6, Figure 1).

Table 6. ROC curve analysis

Table 6

Model AUC 95% CI p
De Ritis ratio 0.562 0.517–0.606 0.007
APACHE II score + De Ritis ratio 0.652 0.609–0.694 <0.001
SOFA score + De Ritis ratio 0.661 0.619–0.703 <0.001

AUC: area under the curve; CI: confidence interval.

References

  1. 1. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382:1708-1720.
  2. 2. Bourgonje AR, Abdulle AE, Timens W, Hillebrands JL, Navis GJ, Gordijn SJ, et al. Angiotensin-converting enzyme 2 (ACE2), SARS-CoV-2 and the pathophysiology of coronavirus disease 2019 (COVID-19). J Pathol. 2020;251:228-248.
  3. 3. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497-506.
  4. 4. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA. 2020;323:2052-2059.
  5. 5. Nardo AD, Schneeweiss-Gleixner M, Bakail M, Dixon ED, Lax SF, Trauner M. Pathophysiological mechanisms of liver injury in COVID-19. Liver Int. 2021;41:20-32.
  6. 6. De Ritis F, Coltorti M, Giusti G. An enzymic test for the diagnosis of viral hepatitis: the transaminase serum activities. Clin Chim Acta. 1957;2:70-74.
  7. 7. Zinellu A, Arru F, De Vito A, Sassu A, Valdes G, Scano V, et al. The De Ritis ratio as prognostic biomarker of in-hospital mortality in COVID-19 patients. Eur J Clin Invest. 2021;51:e13427.
  8. 8. Shaikh SM, Varma A, Kumar S, Acharya S, Patil R. Navigating disease management: a comprehensive review of the De Ritis ratio in clinical medicine. Cureus. 2024;16:e64447.
  9. 9. Mangoni AA, Zinellu A. An updated systematic review and meta-analysis of the association between the De Ritis ratio and disease severity and mortality in patients with COVID-19. Life (Basel). 2023;13. doi:10.3390/life13061324
  10. 10. Pranata R, Huang I, Lim MA, Yonas E, Vania R, Lukito AA, et al. Elevated De Ritis ratio is associated with poor prognosis in COVID-19: a systematic review and meta-analysis. Front Med (Lausanne). 2021;8:676581.
  11. 11. Khalid I, Alshukairi AN, Khalid TJ, Imran M, Imran M, Akhtar MA, et al. Characteristics and outcome of tertiary care critically ill COVID-19 patients with multiple comorbidities admitted to the intensive care unit. Ann Thorac Med. 2022;17:59-65.
  12. 12. Peckham H, de Gruijter NM, Raine C, Radziszewska A, Ciurtin C, Wedderburn LR, et al. Male sex identified by global COVID-19 meta-analysis as a risk factor for death and ITU admission. Nat Commun. 2020;11:6317.
  13. 13. Gebhard C, Regitz-Zagrosek V, Neuhauser HK, Morgan R, Klein SL. Impact of sex and gender on COVID-19 outcomes in Europe. Biol Sex Differ. 2020;11:29.
  14. 14. Jin JM, Bai P, He W, Wu F, Liu XF, Han DM, et al. Gender differences in patients with COVID-19: focus on severity and mortality. Front Public Health. 2020;8:152.
  15. 15. Lee LYW, Cazier JB, Angelis V, Arnold R, Bisht V, Campton NA, et al. COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: a prospective cohort study. Lancet. 2020;395:1919-1926.
  16. 16. Del Valle DM, Kim-Schulze S, Huang HH, Beckmann ND, Nirenberg S, Wang B, et al. An inflammatory cytokine signature predicts COVID-19 severity and survival. Nat Med. 2020;26:1636-1643.
  17. 17. Hu B, Guo H, Zhou P, Shi ZL. Characteristics of SARS-CoV-2 and COVID-19. Nat Rev Microbiol. 2021;19:141-154.
  18. 18. Xue G, Gan X, Wu Z, Xie D, Xiong Y, Hua L, et al. Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19. Int Immunopharmacol. 2020;89:107065.
  19. 19. Demirel A, Miniksar OH. The role of inflammatory indices in predicting intensive care unit mortality in critically ill COVID-19 patients. Turk J Intensive Care. 2024;22(4):239-247.
  20. 20. Paranga TG, Mitu I, Pavel-Tanasa M, Rosu MF, Miftode IL, Constantinescu D, et al. Cytokine storm in COVID-19: exploring IL-6 signaling and cytokine-microbiome interactions as emerging therapeutic approaches. Int J Mol Sci. 2024;25. doi:10.3390/ijms252111411
  21. 21. Zeng F, Huang Y, Guo Y, Yin M, Chen X, Xiao L, et al. Association of inflammatory markers with the severity of COVID-19: a meta-analysis. Int J Infect Dis. 2020;96:467-474.
  22. 22. Soetedjo NNM, Iryaningrum MR, Damara FA, Permadhi I, Sutanto LB, Hartono H, et al. Prognostic properties of hypoalbuminemia in COVID-19 patients: a systematic review and diagnostic meta-analysis. Clin Nutr ESPEN. 2021;45:120-126.
  23. 23. Aklilu AM, Kumar S, Nugent J, Yamamoto Y, Coronel-Moreno C, Kadhim B, et al. COVID-19-associated acute kidney injury and longitudinal kidney outcomes. JAMA Intern Med. 2024;184:414-423.
  24. 24. Tang N, Li D, Wang X, Sun Z. Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia. J Thromb Haemost. 2020;18:844-847.
  25. 25. Abdollahi A, Nateghi S, Panahi Z, Inanloo SH, Salarvand S, Pourfaraji SM. The association between mortality due to COVID-19 and coagulative parameters: a systematic review and meta-analysis study. BMC Infect Dis. 2024;24:1373.
  26. 26. Drácz B, Czompa D, Müllner K, Hagymási K, Miheller P, Székely H, et al. The elevated De Ritis ratio on admission is independently associated with mortality in COVID-19 patients. Viruses. 2022;14. doi:10.3390/v14112360
  27. 27. Fu Y, Du S, Liu X, Cao L, Yang G, Chen H. A linear relationship between De Ritis ratio and mortality in hospitalized patients with COVID-19: a secondary analysis based on a large retrospective cohort study. ILIVER. 2022;1:169-175.
  28. 28. Beigmohammadi MT, Amoozadeh L, Rezaei Motlagh F, Rahimi M, Maghsoudloo M, Jafarnejad B, et al. Mortality predictive value of APACHE II and SOFA scores in COVID-19 patients in the intensive care unit. Can Respir J. 2022;2022:5129314.

Cite this article

Hüseyin Özkök, Şeyma Şenocak, Özlem Aktürk, Ahmed Cihad Genç, Deniz Çekiç, Yusuf Durmaz, Ahmed Bilal Genç, Selçuk Yaylacı. The Role of the De Ritis Ratio in ICU Mortality Among Critically Ill Patients with COVID-19. Journal of Cukurova Anesthesia and Surgical Sciences. 9(2):427-434. https://doi.org/10.36516/jocass.1903636

Scroll to Top