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Article

Comparison of COVID-19 Patients With and Without Acute Kidney Injury at ICU Admission: Evaluation of Associated Factors and Outcomes

1
Department of Anesthesiology and Reanimation-Intensive Care, Ankara Bilkent City Hospital, Yıldırım Beyazıt University Faculty of Medicine, Ankara 06800, Turkey
2
Department of Nephrology, Ankara Bilkent City Hospital, Ankara 06800, Turkey
3
Department of Intensive Care, Ankara Bilkent City Hospital, Ankara 06800, Turkey
4
Yenimahalle Education and Research Hospital, Ankara 06370, Turkey
5
Department of Anesthesiology and Reanimation-Intensive Care, Ankara Bilkent City Hospital, University of Health Sciences, Ankara 06800, Turkey
*
Author to whom correspondence should be addressed.
COVID 2025, 5(9), 145; https://doi.org/10.3390/covid5090145
Submission received: 12 July 2025 / Revised: 22 August 2025 / Accepted: 25 August 2025 / Published: 1 September 2025
(This article belongs to the Section COVID Clinical Manifestations and Management)

Abstract

Although acute kidney injury (AKI) is common among patients with coronavirus disease 2019 (COVID-19), there are only limited data on its occurrence at intensive care unit (ICU) admission. Assessing the factors associated with AKI is essential for early diagnosis and intervention. This study aims to compare the clinical and laboratory characteristics and survival outcomes of COVİD-19 patients with and without AKI at ICU admission and determine the factors associated with AKI. In this study, patients with SARS-CoV-2 infection were categorized based on the presence (AKI group) or absence (non-AKI group) of AKI. Clinical and laboratory data and outcomes were analyzed retrospectively. Of the 712 patients included in this study, 198 were assigned to the AKI group and 514 were assigned to the non-AKI group. Patients with AKI had more comorbidities and higher disease severity; higher rates of invasive mechanical ventilation, vasopressor therapy, and mortality; and longer hospital stays (p < 0.05). Our multivariate analysis identified advanced age, a high Acute Physiology and Chronic Health Evaluation II score, a high neutrophil-to-lymphocyte ratio, a low albumin level, and the presence of comorbidities as independent factors associated with AKI. In patients with COVID-19, AKI observed at ICU admission is associated with advanced age and increased disease severity. The early diagnosis and monitoring of patients may improve clinical outcomes.

1. Introduction

With a broad clinical spectrum, coronavirus disease 2019 (COVID-19) can range from mild symptoms to multiorgan dysfunction and severe respiratory failure [1]. The kidneys may also be affected by COVID-19, and acute kidney injury (AKI) can develop in approximately 44–46% of critically ill patients [2,3,4].
The kidneys can be affected by COVID-19, both directly as a target for the virus and indirectly through mechanisms like renin–angiotensin–aldosterone system dysregulation, cytokine release, and complement system dysfunction [2,5]. Volume depletion and the nephrotoxic effects of medications have also been reported to contribute to the pathophysiology of AKI [1,6]. Additionally, the hypoxia and hypercapnia observed in patients with acute respiratory distress syndrome (ARDS) are thought to exacerbate inflammation and, along with impaired pulmonary function, contribute to the development of AKI [1].
Although numerous studies have investigated the outcomes and risk factors of kidney failure in patients severely infected by SARS-CoV-2, most have either focused on hospitalized cohorts as a whole or assessed kidney failure [3,7,8,9]. Data examining patients with AKI at intensive care unit (ICU) admission are lacking. Many previous studies have included patients with pre-existing chronic kidney disease (CKD), potentially confounding the identification of AKI-specific predictors [3,7,9]. Our study aims to compare COVID-19 patients without prior kidney disease who were admitted to the ICU with and without AKI in terms of their clinical and laboratory characteristics, duration of hospital stays, and survival outcomes and determine the factors associated with AKI.

2. Materials and Methods

2.1. Patients

Our retrospective observational study received approval from the Institutional Ethics Committee (No: E2-23-3591). Our study population consisted of patients admitted to the ICU between April 2021 and January 2023 with a diagnosis of COVID-19. These patients’ hospital records were reviewed and categorized into two groups: patients with AKI (AKI group) and those without AKI (non-AKI group). AKI was diagnosed based on the kidney disease improving global outcomes (KDIGO) guidelines upon admission. Patients were considered to have AKI if they met one of the following criteria: an increase in creatinine by more than 0.3 mg/dL within 48 h, a 1.5-fold increase from baseline creatinine within the last 7 days, or urine output of less than 0.5 mL/kg/h for 6 h [10]. Patients with pre-existing kidney failure or those who were undergoing kidney replacement therapy (KRT) prior to admission were excluded from this study. This decision was driven by our aim to investigate the incidence and factors associated with newly emerging AKI in COVID-19 patients. We considered that including patients with pre-existing kidney disease could introduce confounding factors such as varying CKD stages, comorbidities, and medication regimens that could obscure the direct impact of SARS-CoV-2 on acute kidney function. By focusing on a more homogeneous cohort, we aimed to obtain clearer, more interpretable results regarding AKI related to COVID-19.

2.2. Clinical Assessment and Data Collection Instruments

We compared demographic and clinical characteristics including sex, age, comorbidities [hypertension (HT); diabetes mellitus (DM); heart failure (HF); and cardiovascular, pulmonary, and neurological diseases, among others], Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, severity of illness (classified according to the World Health Organization’s disease severity classification as moderate, severe, or critical), modality of respiratory therapies [non-invasive treatments: mask oxygen, high flow nasal oxygen (HFNO), and non-invasive mechanical ventilation (NIMV) or invasive mechanical ventilation (IMV)], vasopressor therapy, KRT, length of stay in the hospital and ICU, and survival outcomes (discharge or death) [11]. We also compared the laboratory parameters at ICU admission between the groups, including complete blood count parameters [leucocyte, lymphocyte, eosinophil, and platelet counts (×109/L), red cell distribution width (RDW %), and neutrophil-to-lymphocyte ratio (NLR)], interleukin-6 (IL-6, pg/mL), fibrinogen (g/L), D-dimer (mg/L), albumin (g/L), prealbumin (g/L), lactate (mmol/L), triglyceride (TG, mg/dL), high-density lipoprotein (HDL, mg/dL), C reactive protein (CRP, mg/L), and ferritin (µg/L) levels.
The hemogram parameters were measured using the impedance method (Siemens Advia 2120); the albumin, prealbumin, lactate, and cholesterol panel were measured via the spectrophotometric method (Siemens Atellica CH analyzer, Malvern, PA, USA); fibrinogen was measured via the optic turbidimetric method using the Clauss method (Sysmex CS-S100 Coagulometer, Kobe, Japan); D-dimer was measured using the immunoturbidimetric method (Sysmex CS-S100 Coagulometer, Kobe, Japan); and IL-6 was measured using a chemiluminescent immunoassay (Siemens Atellica IM analyzer, Swords, Ireland).

2.3. Statistical Analyses

IBM SPSS Statistics version 27.0 (Armonk, NY, USA: IBM Corp.) and MedCalc version 15.8 (MedCalc Software bvba, Ostend, Belgium) were used to perform the statistical analyses. We employed descriptive statistical methods (frequency, percentage, mean, standard deviation, median, minimum–maximum, and interquartile range [IQR]) to summarize the data. The chi-square test was used to compare categorical variables. The normality of the data distribution was assessed using the Kolmogorov–Smirnov test and the skewness–kurtosis values. Continuous variables with a normal distribution were compared using an independent samples t-test, while those without a normal distribution were compared using the Mann–Whitney U test. We conducted receiver operating characteristic (ROC) curve analysis to identify the variables’ discriminative ability. Binary logistic regression analysis was conducted to identify the associated factors. A p-value of <0.05 was considered statistically significant.

3. Results

A total of 925 patients with SARS-CoV-2 infection were admitted to the ICU between April 2021 and January 2023. In total, 83 patients with pre-existing kidney disease or who were undergoing KRT and 131 patients with incomplete hospital records were excluded from this study. Therefore, 712 patients were enrolled in this study, of whom 198 were assigned to the AKI group and 514 to the non-AKI group.
Comorbidities were more prevalent among the patients in the AKI group than among those in the other group (p < 0.001). The patients in the AKI group had a higher prevalence of HT (n = 120, 60%; n = 202, 39.3%) and HF (n = 33, 16.7%; n = 53, 10.3%) compared with the patients in the other group (p < 0.001; p = 0.028). No significant differences were observed among the other comorbidities of the groups (p > 0.05). Table 1 presents a comparison of the characteristics of the two groups. A total of 45 patients (22.7%) in the AKI group required KRT. There was no difference in the sex distribution between the groups (p = 0.823). However, differences in age, APACHE II scores, disease severity, respiratory treatment modalities, vasopressor therapy, length of hospital stay, and survival were observed between the groups (p < 0.001) (Table 1). There were also differences between the groups in terms of the rates of oxygen therapy via face mask and HFNO as respiratory support modalities.
The AKI group had lower levels of lymphocytes, albumin, prealbumin, and HDL and higher levels of leukocytes, RDW, NLR, IL-6, D-dimer, lactate, ferritin, and CRP compared with the other group (p < 0.05) (Table 2). However, neither group showed significant differences in the eosinophil and platelet counts, fibrinogen, or TG levels (p > 0.05).
We performed ROC analysis on the variables that showed significant differences in the pairwise comparisons between the groups. The cutoff values were determined for the following variables: age, APACHE II score, lymphocyte count, leukocyte count, RDW, NLR, IL-6, D-dimer, albumin, prealbumin, lactate, and CRP levels (Table 3).
According to the regression analysis, age, APACHE II score, NLR, albumin level, and the presence of comorbidities were significantly associated with AKI (p < 0.05) (Table 4).

4. Discussion

Our findings indicate that the COVID-19 patients with AKI in our study were more critically ill. They required more IMV and vasopressor therapy, they stayed in hospital for longer, and they had higher mortality rates. Advanced age, the presence of comorbidities, an elevated APACHE II score, a high NLR, and low albumin levels were the factors identified to be associated with AKI. The following cutoff values were determined for the independent factors associated with AKI: age > 76 years, APACHE II score > 19, NLR > 15, and albumin level < 34 g/L.
It has been reported that the incidence of AKI in COVID-19 patients can reach approximately 40–50%, especially in critical care patients [12,13,14]. In our study, we observed that approximately 28% of patients admitted to the ICU had AKI. Previous studies of patients with COVID-19 and AKI have identified advanced age, DM, obesity, CKD, and HT to be risk factors for AKI [2,7,8,12,15]. In our study, we excluded patients with pre-existing kidney failure or CKD. The pairwise comparisons revealed that HT and HF were more prevalent in AKI patients. However, the multivariate logistic regression analysis showed that these specific comorbidities were significantly associated with AKI. Schaubroeck et al. reported an elevated APACHE II score to be a risk factor for AKI in their multicenter study [16]. Another study evaluating 738 patients with AKI and SARS-CoV-2 infection found that a quick SOFA (qSOFA) score of ≥1 was a predictor of AKI [7]. In our study, we found that advanced age (age > 76 based on our ROC analysis), the presence of comorbidities in general, and a high APACHE II score (>19) were associated with AKI. We believe that the age-related decline in kidney function, the presence of multiple comorbidities, and an inflammatory response in elderly patients may explain this association. The higher APACHE II scores observed in AKI patients also emphasize the connection between disease severity and kidney involvement. While some studies suggest that the male sex is an AKI risk factor [1,2,8], we found no difference between the men and women in our groups.
It has been reported that vasopressor therapy and higher rates of MV are more frequent in patients with AKI due to SARS-CoV-2 infection [3,8,9,12,17]. Although classical septic shock is not commonly observed in these patients, hypotension in critically ill patients can impair renal perfusion and promote the development of AKI [13,14,18]. A study by Gupta et al. involving 3099 patients identified hypoxemia at ICU admission as a risk factor requiring KRT [19]. In a review evaluating studies conducted in hospitalized COVID-19 patients, the development of AKI was determined to be associated with ARDS [13]. Guzatti and colleagues found that the extubation failure rate was higher in patients requiring hemodialysis (HD) [20]. MV, particularly when used in high-positive-pressure settings, may increase the risk of AKI [1,15,16]. In our study, we observed higher rates of IMV and vasopressor therapy in patients with AKI, which is consistent with the findings in the literature. The reason for ICU admission in COVID-19 patients is frequently severe hypoxemia, and we believe that this oxygen deficiency may have contributed to the development of kidney failure in the patients we studied. The use of non-invasive respiratory treatment modalities, such as oxygen therapy via face mask and HFNO, was more common among patients without AKI, whereas the rate of IMV was higher in those with AKI. This difference may reflect illness severity, as patients with AKI tend to present with more severe conditions that often necessitate IMV. The need for IMV itself may contribute to the development or worsening of AKI, potentially due to the associated hemodynamic problems. Cheng and colleagues’ study, which included 701 patients with COVID-19, identified a correlation between AKI and disease severity [21]. In our cohort, patients with AKI were also found to have more critical illnesses. Our findings align with those of previous studies indicating that AKI is a significant complication in severe COVID-19, particularly among patients requiring ICU admission [3,19]. The severity of the disease has also been reported to be associated with continuous KRT rates [22]. In our study, we found the proportion of AKI patients requiring KRT to be approximately 23%. It is anticipated that mortality in AKI patients who need KRT may be even higher than in end-stage kidney disease patients, and some surviving patients may continue to require KRT after discharge [23]. One patient in our cohort who was not diagnosed with AKI at ICU admission subsequently required KRT during follow-up. This could be explained by the progression of the underlying critical illness, the impact of therapeutic interventions, or the development of secondary complications such as sepsis or hemodynamic instability. This highlights the dynamic nature of kidney function in critically ill patients and underlines the importance of ongoing renal monitoring even in those without AKI at presentation.
In addition to the demographic, clinical, and laboratory characteristics of the patients, medications such as vasopressors, angiotensin-converting enzyme inhibitors (ACEis), angiotensin receptor blockers (ARBs), non-steroidal anti-inflammatory drugs (NSAIDs), diuretics, and corticosteroids can also contribute to nephrotoxicity [24]. Corticosteroids have been used in COVID-19 patients experiencing respiratory failure, and it was highly probable that the majority of patients admitted to our ICU had previously been prescribed corticosteroids. Furthermore, we believe that the use of diuretics (to avoid fluid overload) or NSAIDs for analgesic and antipyretic purposes may have also contributed to the deterioration of kidney function. The pharmacological treatments administered to the patients in our study are unknown, and we were unable to definitively rule out the use of nephrotoxic drugs in our patients; however, we believe that the potential nephrotoxic effects of these treatments should be considered when assessing AKI risk. Recent studies have found that COVID-19 patients with AKI have higher (approximately 52%) mortality rates and longer hospital stays [1,3,4,8,9,19,25]. However, we did not find any difference in terms of the length of stay in the ICU between the groups in our study.
Studies evaluating laboratory parameters in COVID-19 patients have reported differences in inflammatory markers and complete blood count values between those with and without AKI [1,3,7,8,19]. Evidence suggests that patients with AKI have lower lymphocyte and platelet counts, along with elevated levels of lactate, CRP, D-dimer, ferritin, leukocytes, and NLR compared with those without AKI [3,4,8,9,21,25,26]. A study by Anandh et al. involving 393 patients with AKI requiring HD identified low albumin values as a risk factor for mortality [27]. In another study conducted on COVID-19 patients with ARDS, both elevated NLR and decreased albumin levels emerged as independent predictors of AKI [28]. In our study, COVID-19 patients with AKI presented with significantly worse inflammatory profiles and poorer prognostic markers that reflect systemic inflammation, coagulation activation, and organ dysfunction. Consistent with the findings of previous research, we observed lower levels of lymphocytes, albumin, and prealbumin and higher NLRs, leukocyte count, IL-6, D-dimer, lactate, CRP, and ferritin levels in AKI patients compared with those without AKI. Our multivariate regression analysis found that only low albumin levels (<34 g/L) and high NLR (>15) were significantly associated with AKI. While our analysis identified several statistically significant associations between various laboratory parameters and AKI in COVID-19 patients, it is important to contextualize these findings. The area under the curve (AUC) values derived from our ROC analysis, ranging from 0.55 to 0.66, indicate a modest discriminatory ability for these individual markers. This suggests that while these parameters are associated with AKI, their standalone predictive power for clinical decision-making is limited. The ROC analysis revealed that although the overall discriminative power of the parameters was low, their negative predictive values were relatively high. In complex, multifactorial conditions such as AKI in critically ill COVID-19 patients, the use of highly robust single-biomarker prediction models may be uncommon. The primary contribution of this study is the identification and confirmation of these associations to help us better understand how different factors contribute to the development of AKI.
A reduction in HDL level is a common finding during systemic inflammation, and this has been correlated with an unfavorable prognosis in septic patients [29]. Reduced HDL levels may also predict the development of AKI [29]. Henry and colleagues evaluated the lipid profiles of COVID-19 patients and found a correlation between elevated TG levels and increased creatinine [30]. Furthermore, elevated RDW levels have also been linked to sepsis-related AKI [31]. Considering the hyper-inflammatory state that patients are in when suffering from COVID-19, we compared the HDL and RDW levels between the groups in our study and found that patients with AKI had significantly lower HDL levels and higher RDW levels in the pairwise comparisons. However, these findings were not statistically significant in the regression analysis. More definitive results are needed, necessitating further studies with larger patient populations.
The patients in our study were ill during a period when the SARS-CoV-2 Omicron variant was predominantly widespread. We believe that the AKI profile in these patients may differ from that of patients infected with other variants. For example, in their study comparing the Delta and Omicron variants, Li et al. suggested that the Omicron variant might be associated with more severe kidney damage [32]. Conversely, McAdams et al., in their study comparing Omicron, Delta, and other variants, reported that severe AKI rates were lower in patients infected with the Omicron variant [33]. In the same study, another complex finding that does not lead to a clear conclusion regarding AKI development in patients with specific variants was also reported: patients infected with the Omicron variant were found to be older but had less severe disease. We believe that the characteristics and clinical findings of these patients may differ from those infected with other variants, and therefore it would be appropriate to investigate the potential different molecular mechanisms or clinical effects on AKI.
Our study has several strengths. These include the relatively large ICU cohort of critically ill COVID-19 patients and the application of both statistical univariate and multivariate models. However, our study also has some limitations. The single-centered and retrospective design of the study may lead to selection bias and restrict the generalizability of our findings. Additionally, this study did not evaluate data on the use of nephrotoxic medications that could influence pathophysiology, nor did it consider the precise timing and staging of AKI. Furthermore, we were unable to conduct a comprehensive long-term follow-up of kidney function in the surviving patients. One notable aspect of our methodology is that we excluded patients with pre-existing CKD. That being said, we acknowledge the significant clinical importance of AKI in the CKD population and believe that this complex group warrants inclusion in future studies with tailored methodologies to discover the factors associated with acute renal deterioration and outcomes.

5. Conclusions

In conclusion, the patients diagnosed with AKI at ICU admission due to COVID-19 in our study had a more severe disease course, a longer hospital length of stay, and higher rates of IMV, vasopressor therapy, and mortality. Easily obtainable clinical and laboratory parameters, such as age, comorbidities, APACHE II score, NLR, and albumin levels, are closely associated with the presence of AKI in COVID-19 patients. Early identification and close monitoring of these patients enable timely interventions to reduce kidney damage and improve clinical outcomes.

Author Contributions

Conceptualization, D.K.C., and I.O.T.; methodology, D.K.C., I.O.T., and S.I.; validation, D.K.C., M.K., D.B., and P.U.; formal analysis, D.K.C., and S.I.; investigation, P.U., N.H.S., D.B., and E.T.; resources, D.K.C., E.T., N.H.S., and D.B.; data curation, D.K.C., E.T., M.K., and P.U.; writing—original draft preparation, D.K.C., and S.I.; writing—review and editing, D.K.C., and S.I.; visualization, N.H.S., D.B., and M.K.; supervision, S.I.; project administration, D.K.C., I.O.T., and S.I. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki. Ethical approval was obtained from the institutional ethics committee (No: E2-23-3591; approved on 15 March 2023).

Informed Consent Statement

Informed consent from each volunteer is not required in our institution for retrospective studies.

Data Availability Statement

The data presented in this study are available on reasonable request from the corresponding author due to the legal and ethical restrictions. The authors do not have permission to share raw data.

Conflicts of Interest

The authors declare no conflicts of interest.

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Table 1. Comparison of characteristics of the groups.
Table 1. Comparison of characteristics of the groups.
Non-AKI
n = 514
AKI
n = 198
p
SexFemale 196 (%38.1)78 (%39.4)0.823 a
Male 318 (%61.9)120 (%60.6)
Age (year)69.6 ± 16.477.3 ± 12.4<0.001 b
ComorbidityNo88 (%17.1)12 (%6.1)<0.001 a
Yes426 (%82.9)186 (%93.9)
APACHE II19.1 ± 9.524.5 ± 10.6<0.001 b
Severity of
COVID-19
Moderate 45 (%8.8)9 (%4.5)<0.001 a
Severe157 (%30.5)37 (%18.7)
Critical312 (%60.7)152 (%76.8)
Respiratory
treatment
IMV162 (%31.5)108 (%54.5)
Non-invasive
Mask O2
HFNO
NIMV
352 (%68.5)
197 (%38.3)
152 (%29.6)
3 (%0.6)
90 (%45.5)
46 (%23.2)
43 (%21.7)
1 (%0.5)
<0.001 a
Vasopressor
therapy
No421 (%81.9)110 (%55.6)<0.001 a
Yes93 (%18.1)88 (%44.4)
KRT No513 (%99.8)153 (%77.3)<0.001 a
Yes1 (%0.2)45 (%22.7)
Length of ICU stay (day)8.0 (5.0–15.0)7.5 (3.0–15.0)0.095 c
Length of hospital stay (day)15.0 (9.0–24.0)12.0 (5.0–22.0)<0.001 c
Survival Discharged 379 (%73.7)96 (%48.5)<0.001 a
Death 135 (%26.3)102 (%51.5)
AKI: acute kidney injury, APACHE II: Acute Physiology and Chronic Health Evaluation II, IMV: invasive mechanical ventilation, non-invasive treatments (O2: oxygen, HFNO: high flow nasal oxygen and NIMV: non-invasive mechanical ventilation), KRT: kidney replacement therapy, ICU: intensive care unit, a: chi-square test (n (%)), b: independent samples t test (mean ± SD), c: Mann–Whitney U test (median (Q1–Q3)).
Table 2. Comparison of laboratory values of the groups at ICU admission.
Table 2. Comparison of laboratory values of the groups at ICU admission.
Non-AKI
n = 514
AKI
n = 198
p
Lymphocyte (×109/L)0.70 (0.50–1.00)0.60 (0.40–0.90)0.013 c
Leucocyte (×109/L)9.0 (6.0–12.0)11.0 (7.0–16.0)<0.001 c
Platelet (×109/L)245.2 ± 119.1228.8 ± 116.60.099 b
Red cell distribution width (%)15.0 (13.9–16.4)15.6 (14.8–17.0)<0.001 c
Eosinophil (×109/L)0.02 (0.01–0.05)0.01 (0.01–0.04)0.156 c
Neutrophil/lymphocyte ratio9.5 (5.4–16.0)14.0 (7.8–26.1)<0.001 c
Interleukin-6 (pg/mL)39.0 (17.0–99.5)56.0 (21.0–242.8)0.001 c
Fibrinogen (g/L)5.0 (3.9–6.1)5.0 (3.8–6.2)0.987 c
D-Dimer (mg/L)1.8 (1.0–3.5)3.4 (1.7–8.0)<0.001 c
Albumin (g/L)34.7 ± 5.832.6 ± 5.8<0.001 b
Prealbumin (g/L)0.11 (0.08–0.16)0.10 (0.07–0.14)<0.001 c
Lactate (mmol/L)2.1 (1.8–3.0)2.5 (1.8–3.8)0.005 c
Triglyceride (mg/dL)138.0 ± 60.3149.6 ± 71.40.179 b
High-density lipoprotein (mg/dL)35.9 ± 14.531.7 ± 11.00.015 b
C reactive protein (mg/L)85.5 ± 84.3123.3 ± 104.5<0.001 b
Ferritin (µg/L)778.7 ± 1.192.81.486.5 ± 2.794.80.001 b
AKI: acute kidney injury, b: independent samples t test (mean ± SD), c: Mann–Whitney U test (median (Q1–Q3)).
Table 3. ROC analysis of variables with significant differences in pairwise comparisons.
Table 3. ROC analysis of variables with significant differences in pairwise comparisons.
AUC%95 CICut OffSensitivitySpecificityYouden Index+PV−PVp
Age0.6390.602–0.674>7662.661.90.24538.781.1<0.001
APACHE II0.6610.625–0.696>1964.160.30.24538.481.4<0.001
Lymphocyte0.5600.522–0.597≤0.654.657.20.11732.976.60.013
Leucocyte0.6140.577–0.650>12.342.977.40.20442.377.9<0.001
RDW 0.6010.564–0.637>14.775.345.00.20334.682.5<0.001
NLR0.6300.594–0.666>1548.073.10.21140.878.5<0.001
Interleukin 60.5870.548–0.625>12935.681.10.16841.177.40.001
D-Dimer0.6700.634–0.705>2.264.760.90.25538.981.7<0.001
Albumin0.6060.569–0.643≤3461.656.90.18535.679.3<0.001
Prealbumin0.5910.552–0.629≤0.1166.149.30.15534.078.7<0.001
Lactate0.5680.531–0.605>2.455.161.30.16335.478.00.009
HDL0.5750.510–0.638≤4082.934.50.17434.183.10.052
CRP0.6130.577–0.649>9151.066.10.17136.777.8<0.001
Ferritin0.5440.506–0.581>181017.993.20.11050.074.80.075
APACHE II: Acute Physiology and Chronic Health Evaluation II, RDW: red cell distribution width, NLR: neutrophil/lymphocyte ratio, HDL: high-density lipoprotein, CRP: C reactive protein.
Table 4. Univariate and multivariate logistic regression analysis for AKI at ICU admission.
Table 4. Univariate and multivariate logistic regression analysis for AKI at ICU admission.
Univariate Multivariate
Odds95% CIpH-L TestOdds95% CIp
Age1.041.02–1.05<0.0010.2301.031.013–1.043<0.001
APACHE II1.051.04–1.07<0.0010.2751.041.017–1.054<0.001
NLR1.021.01–1.030.0010.2531.031.013–1.039<0.001
Albumin0.940.91–0.97<0.0010.4580.970.934–0.9980.037
Comorbidity3.201.71–6.00<0.001--2.121.015–4.4120.046
Hypertension2.381.70–3.32<0.001--------
Heart failure1.741.09–2.780.021--------
Lymphocyte0.690.49–0.950.0250.518------
Leucocyte1.071.04–1.10<0.0010.267------
Prealbumin0.020.00–0.290.0040.857------
Ferritin 1.001.00–1.00<0.0010.198------
Interleukin 61.001.00–1.000.0010.135------
C reactive protein1.001.00–1.01<0.0010.278------
HDL0.980.95–1.000.0310.718------
D-Dimer 1.061.04–1.09<0.0010.002------
RDW1.010.99–1.030.2410.006------
Lactate1.000.99–1.010.597<0.001------
APACHE II: Acute Physiology and Chronic Health Evaluation II, NLR: neutrophil/lymphocyte ratio, HDL: high-density lipoprotein, RDW: red cell distribution width, Nagelkerke R2 = 0.179, Hosmer and Lemeshow Test = 0.489.
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Calili, D.K.; Ulubasoglu, P.; Toy, E.; Bolukbasi, D.; Keles, M.; Selmi, N.H.; Ozkocak Turan, I.; Izdes, S. Comparison of COVID-19 Patients With and Without Acute Kidney Injury at ICU Admission: Evaluation of Associated Factors and Outcomes. COVID 2025, 5, 145. https://doi.org/10.3390/covid5090145

AMA Style

Calili DK, Ulubasoglu P, Toy E, Bolukbasi D, Keles M, Selmi NH, Ozkocak Turan I, Izdes S. Comparison of COVID-19 Patients With and Without Acute Kidney Injury at ICU Admission: Evaluation of Associated Factors and Outcomes. COVID. 2025; 5(9):145. https://doi.org/10.3390/covid5090145

Chicago/Turabian Style

Calili, Duygu Kayar, Pinar Ulubasoglu, Erol Toy, Demet Bolukbasi, Meryem Keles, Nazan Has Selmi, Isil Ozkocak Turan, and Seval Izdes. 2025. "Comparison of COVID-19 Patients With and Without Acute Kidney Injury at ICU Admission: Evaluation of Associated Factors and Outcomes" COVID 5, no. 9: 145. https://doi.org/10.3390/covid5090145

APA Style

Calili, D. K., Ulubasoglu, P., Toy, E., Bolukbasi, D., Keles, M., Selmi, N. H., Ozkocak Turan, I., & Izdes, S. (2025). Comparison of COVID-19 Patients With and Without Acute Kidney Injury at ICU Admission: Evaluation of Associated Factors and Outcomes. COVID, 5(9), 145. https://doi.org/10.3390/covid5090145

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