Effect of atorvastatin as a renal protective agent in patients with systemic inflammatory response syndrome using the renal arterial resistive index

Mina Maher Raouf; Eslam Antar Shadad; Nagy Sayed Ali

doi:10.4266/acc.003912

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Original Article Trauma Effect of atorvastatin as a renal protective agent in patients with systemic inflammatory response syndrome using the renal arterial resistive index: Mina Maher Raouf, Eslam Antar Shadad, Nagy Sayed Ali; Acute and Critical Care 2025;40(1):95-104.
DOI: https://doi.org/10.4266/acc.003912
Published online: February 18, 2025

Department of Anesthesia, Intensive Care Unit, and Pain Management, Minia University Hospital, Minia, Egypt

Corresponding author: Mina Maher Raouf Department of Anesthesia, Intensive Care Unit, and Pain Medicine, Minia University, Minia 61511, Egypt Tel: +20-1015752424 Email: drmina2015@gmail.com

• Received: October 14, 2024 • Revised: October 30, 2024 • Accepted: October 30, 2024

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
KEY MESSAGES
NOTES
REFERENCES

Abstract

Background
Current meta-analyses have yielded inconclusive results regarding the effectiveness of statins in preventing early renal injury in the context of poly-trauma. Notably, renal artery Doppler-derived resistance indices have shown a strong correlation with early detection of renal impairment, underscoring their importance in clinical assessment.
Methods
The study involved 106 adults aged 18 years and older of both sexes, who presented to Minia University Hospital, Egypt, with poly-trauma with a two-point or greater increase in the sequential organ failure assessment score within the first 72 hours of hospital admission and who met two or more of the diagnostic criteria of systemic inflammatory response syndrome. Participants were randomly assigned to either the atorvastatin group, which received oral atorvastatin at a dosage of 20 mg every 12 hours for 1 week alongside conventional therapy (antimicrobial agents and balanced crystalloids), or the control group, which received conventional therapy along with a placebo tablet every 12 hours for 1 week.
Results
The atorvastatin group yielded a significantly lower incidence of acute kidney injury (AKI; P<0.001). Additionally, there was significant reduction in renal resistance and pulsatility indices in the atorvastatin group. Furthermore, the atorvastatin group exhibited a shorter intensive care unit (ICU) stay (P=0.004). The renal index had a sensitivity of 90% and specificity of 68% for AKI prediction when the cutoff value was 0.61. Pulsatility index had a sensitivity of 90% and a specificity of 53% when the cutoff value was 1.28.
Conclusions
Atorvastatin was impactful in mitigating the incidence of AKI, improving renal resistive vascular indices, and abbreviating ICU stays in the poly-traumatized population.
Key Words: atorvastatin; creatinine; renal artery doppler; renal replacement; resistive index

INTRODUCTION

Systemic inflammatory response syndrome (SIRS) is an exaggerated bodily defense mechanism in response to various harmful stressors, such as infection, trauma, surgery, and acute inflammation. SIRS aims to localize and eliminate the source of the injury, whether endogenous or exogenous. This response involves the release of acute-phase reactants and pro-inflammatory substances, which serve as direct mediators of widespread alterations in the autonomic and immunological systems. Although the intention is protective, an uncontrolled cytokine storm can trigger a massive inflammatory cascade, potentially leading to reversible or irreversible multiple organ dysfunction [1]. SIRS and sepsis are closely related. Sepsis involves infection plus the criteria of SIRS. According to the Sepsis-3 definition, sepsis is characterized by a "dysregulated host response to inflammation," incorporating the SIRS criteria [2]. The conflict between pro- and anti-inflammatory mediators affect the clinical course and possible outcome. When the scale tips, pro-inflammatory mediators and progressive endothelial leaks result in excessive activation with a resulting state of capillary failure and loss of circulatory integrity, leading to ischemic injury. Acute kidney injury (AKI) secondary to SIRS is a devastating clinical scenario encountered due to this uncontrolled inflammatory process. AKI is prevalent, affecting up to 60% of SIRS patients; in half of these cases, AKI develops prior to admission to the emergency department [3]. Statins are hydroxyl-3-methylglutaryl co-reductase inhibitors and possess pleiotropic anti-inflammatory properties in addition to their lipid-lowering effects. In terms of SIRS, the use of statins is a matter of debate. Patients using statin showed more favorable outcomes in terms of sepsis prevention than non-users. However, statins could not reduce mortality in cases of severe sepsis [4]. This suggests that statins may be more effective in mitigating disease progression in the early stages rather than in severely ill patients. AKI in addition to SIRS and poly-trauma is a deleterious scenario. Potential therapeutic modalities for early diagnosis and prevention are needed. The purpose of the present study was to appraise the therapeutic efficacy of statins in offering renal protection by reducing renal artery resistive vascular indices in the poly-trauma SIRS population.

MATERIALS AND METHODS

This research was conducted in accordance with the principles outlined in the Helsinki Declaration and was designed as a prospective, randomized, double-blind, placebo-controlled intervention. Approval was granted from the ethical council (No. 343-2022), and the clinical trial was registered under the identifier NCT05946122 on the ClinicalTrials.gov platform at https://classic.clinicaltrials.gov/ct2/show/NCT05946122. This study took place in a multi-disciplinary intensive care unit (ICU) in Minia University Hospital, Egypt, from May 2023 to December 2023 and comprised 106 patients, from whom informed consent was collected.

Participant Selection

The current study enrolled 106 patients, male and female, 18 years or older from a poly-trauma population that exhibited a two-point or greater increase in sequential organ failure assessment (SOFA) in the first 72 hours of hospital admission, along with two of four criteria of SIRS. These four criteria are total leucocytic count (TLC) greater than 12,000 mm³ or less than 4,000 mm³, temperature higher than 38 °C or less than 36 °C, heart rate greater than 90 beats/min, and respiratory rate greater than 20 cycles/min, in agreement with sepsis-2 consensus criteria. The Newcastle definition of abbreviated injury score >3 in two or more body regions was established to define polytrauma [5]. Monotrauma, preadmission chronic statin use (>3 months), chronic kidney disease, frequent use of non-steroid anti-inflammatory drugs, cardiomyopathic population (ejection fraction <40%), hemodynamic instability at any time during enrollment, on prednisolone ≥5 mg, chemotherapeutic drug use, pre-existing myopathy, multi-organ failure syndrome, or reluctance to participate were exclusion criteria of the study.

Study Flow

The enrolled cohort was admitted to the ICU, and demographic details, comorbidities, and clinical characteristics were. A randomization sequence was created using the website www.sealedenvelope.com and the blocked randomization method with four blocks which was consistent with 1:1 randomization. The serial randomization was C1,C2, Z1,Z2,…etc. Concealment was achieved via the closed envelope method, where each sealed envelope contained an unlabeled sheet numbered in an alphabetical and numerical sequence (e.g., 1A, 2A, and 1B), indicating the specific patient group and sequence. Assignments were maintained until completion of the study. The 106 patients were equally divided into two groups: group I (Atorvastatin- Ator, EIPICO): 53 patients received atorvastatin 20 mg every 12 hours for 1 week plus conventional therapy (anti-microbial, balanced crystalloids); group II (control): 53 patients received conventional therapy (anti-microbial, balanced crystalloids) plus a placebo tablet of the same color and size as the test drug every 12 hours for 1 week.

The SOFA score was calculated at the time of admission and daily for 1 week. Patients were followed until hospital discharge or death. Bilateral renal index (RI), pulsatility index (PI), and mean flow velocity (MFV) were measured using a Doppler-based flow-meter (Mindray) at four-time intervals: on admission and 6 hours, 24 hours, and 72 hours after admission in the ICU. Metrics of daily routine renal function (serum creatinine, and urea) and liver function (alanine transaminase and aspartate transaminase) and a complete blood panel were obtained. The patients and the outcome-assessing physician were unaware of the group assignment.

Renal Resistive Index Measurement

Positioning

The patient was positioned in a supine or slightly lateral position with his back facing the radiologist.

Probe placement

A curvilinear probe transducer (GE Healthcare Vivid T8) was placed over the abdomen after sterilization with povidone iodine 10% for 3 minutes. Typical placement was in the flank region midway between the anterior superior iliac spine and costal margin to obtain optimal images of the renal arteries. Obese patients were tilted to facilitate sonographic imaging. The image depth was set at 5–8 cm.

Localization of renal arteries

B-mode ultrasound was initially used to visualize the kidneys and locate the renal arteries. This helped in identifying the optimal Doppler sampling sites.

Doppler sampling

Once the renal arteries were identified, the Doppler mode was activated to obtain blood flow velocity waveforms. Doppler sampling was performed by placing the sample volume (a small box or cursor) within the lumen of the interlobar artery. This allowed the ultrasound machine to measure the velocity of blood flow within that specific region.

Definition and Categorization of AKI

AKI was classified into three stages based on Kidney Disease: Improving Global Outcomes (KDIGO) classification. Stage 1 denotes an acute increase in serum creatinine of 0.3 mg/dl within 2 days or a 1.5–1.9 fold increase from basal serum creatinine or urine output less than 0.5 ml/kg/hr for 6–12 hours. Stage 2 involves to a 2.9-fold increase in basal serum creatinine or urine output less than 0.5 ml/kg/hr for more than 12 hours. Stage 3 is a 3-fold increase in basal serum creatinine or anuria for more than 12 hours or establishment of renal replacement therapy (RRT) [6].

Sample Size Calculation

No other studies have appraised the effect of statin on renal resistive indices in SIRS. The current study performed a pilot study on 10 population samples (5 in each group). In that study, the mean renal resistive index after 24 hours was 0.6±0.06 in group I and 0.73±0.1 in group II, with an effective size of 0.55. A sample size of 50 patients in each group was determined to provide 80% power for the independent samples t-test at 0.05 significance using G*Power 3.1 9.2 software (Heinrich-Heine-Universität Düsseldorf). Six patients (10%) were added in each group to compensate for drop-outs (Figure 1).

Statistical Analysis

All data were collected, tabulated, and statistically analyzed in the SPSS software version 26 (IBM Corp.). The data were tested for normal distribution using the Shapiro-Wilks test. Qualitative data are presented as frequencies and relative percentages. The chi-square test and Fisher’s exact test were used to calculate the differences between quantitative variables, that are expressed as mean±standard deviation or median and range for parametric and non-parametric data, respectively. The Friedmann test was used to calculate differences between quantitative variables in one group and related data across time points. An independent t-test and a Mann-Whitney U-test were used to calculate differences in quantitative variables between two groups for parametric and non-parametric variables, respectively. Receiver operating characteristic (ROC) analysis of AKI predictability was performed using the resistive index and PI. All statistical comparisons were two-tailed, with a P-value ≤0.05 indicating a significant difference.

RESULTS

Enrollment of 121 patients was documented. However, 15 candidates were excluded due to refusal to participate or pre-admission statin use as illustrated in the Consolidated Standards of Reporting Trials (CONSORT) chart (Figure 2). Table 1 shows the demographic and clinical data of the studied groups at the time of ICU admission, which were comparable between the groups. Table 1 shows the ICU stays and in-hospital mortality among the studied groups. Length of ICU stay was significant shorter in the atorvastatin group than the control group (P=0.004). Mortality rates were comparable between the two groups (Table 1). Table 2 reports the number of patients with AKI, their KDIGO stage, and the fate of candidates with AKI in the studied groups. There was a significant difference between the studied groups regarding number of patients with AKI (3 cases in the atorvastatin group versus 17 in the control group, P<0.001). Complete recovery, number in need of RRT, and number in each KDIGO stage were significantly different in the studied groups (P=0.001, P=0.02, and P=0.001, respectively) (Table 2).

Table 3 shows changes in serum creatinine on the first, second, and fourth days after admission. Serum creatinine values are listed in Table 3 for intergroup comparison. There was a significant difference at days 2 and 4 (P=0.01 and P=0.004, respectively). For intragroup comparison, there was a significant difference in serum creatinine between the first and fourth days in both groups. Table 3 offers data about urine output in the studied groups at the first, second, and fourth days after admission. For intergroup comparison, there was a significant difference between groups on the second and fourth days (P=0.03 and P=0.01, respectively). For intragroup comparison, there was a significant difference in urine output on the second and fourth days compared to the basal values only in the control group as shown in Table 3.

Table 4 shows a comparison between the studied groups regarding mean PI and MFV. Renal PI was significantly different between groups at all tested time points (P=0.01, P=0.02, and P=0.03, respectively). The MFV values were comparable between the groups. Table 3 shows the median SOFA score in the studied groups on days 1–7 after ICU admission. Intergroup comparison showed a significant difference at 5, 6, and 7 days of follow up (P=0.02, P=0.02, and P=0.01, respectively). Intragroup comparison presented a significant difference in SOFA score on days 5, 6, and 7 compared to the preadmission value in the atorvastatin group. There was no significant difference in the control group.

Table 3 shows changes in TLC in the studied groups on the first, second, and fourth days after admission. TLC changes throughout the study are represented in Table 3, showing comparable results between the studied groups. For intragroup comparison, there was a significant difference in TLC on the second and fourth days compared to the basal values in the atorvastatin group and in the control group. Table 3 shows changes in serum C-reactive protein (CRP) in the studied groups on the first, second, and fourth days. Significant difference was observed between the groups in serum CRP at days 2 and 4 after admission (P=0.03 and P=0.01, respectively). At day 1, data were comparable between the studied groups. Table 5 shows the ROC analysis of the resistive index and PI in prediction of AKI. As shown in Table 5, the RI and PI had significant value for predicting AKI (P=0.001 and P=0.01, respectively), with area under the curve >0.7 for both variables. RI had a sensitivity of 90% and specificity of 68% for AKI prediction when the cutoff value was 0.61. The PI had a sensitivity and specificity of 90% and 53%, respectively, for AKI predictability (Table 5, Figures 3-5). at a cutoff value of 1.28.

DISCUSSION

Experimental evidence from in vitro studies suggests that statins may reduce the risk of sepsis-induced AKI, lower mortality rates by dampening the systemic inflammatory response, and decrease renal vascular permeability and tubular injury [7]. However, the actual influence of statins on risk of sepsis-induced AKI and long-term mortality related to AKI in humans remains unknown. Numerous clinical trials and meta-analyses have investigated the potential renal-protective effects of statins in septic patients, yet these analyses have produced conflicting and inconsistent findings. For instance, a large-scale, prospective cohort study by Murugan et al. [8] examined the impact of statin use on the risk and outcomes of AKI in patients with community-acquired pneumonia (CAP). They enrolled 1,836 individuals diagnosed with CAP and found no significant impact of pre-admission statin use on either the incidence of AKI or 1-year mortality. The authors noted that confounding factors related to different indications for statin use may have influenced these results. Specifically, statin users were more prevalent among patients with diabetes and cardiovascular disease—conditions that justify statin prescriptions but are recognized risk factors for AKI. Thus, statin use may have obscured the true relationship between statins and AKI risk. Additionally, the study included individuals with chronic kidney disease, a significant risk factor for AKI. These factors raised concerns related to the reliability of the end results.

Another interesting experimental study [7] investigated the effectiveness of simvastatin in reducing AKI incidence following cecal ligation and puncture in mice, demonstrating beneficial effects in AKI and mortality. However, as in most studies in this area, the researchers focused on populations experiencing severe sepsis or requiring mechanical ventilation in relation to statin use. A recent meta-analysis [9] examined the efficacy of high-dose atorvastatin (>80 mg/day) as a pre-treatment to reduce the risk of contrast-induced nephropathy (CIN) in patients undergoing coronary angiography. The analysis found that atorvastatin significantly lowered the risk of CIN compared to a control group (P=0.004). The proposed mechanisms include prevention of reabsorption of contrast agents and deactivation of the complement apoptotic intrinsic pathway. However, a clinical trial by Ozhan et al. [10] on CIN indicated that short-term high-dose atorvastatin did not significantly decrease the incidence of AKI. This disparity points to the current study merit of focusing on the potential benefits of early low-dose atorvastatin supplementation for renal protection in poly-trauma patients. Furthermore, we investigated the relationship between atorvastatin and renal Doppler resistive indices, a unique contribution to the field.

We reported that atorvastatin reduced renal resistive vascular indices (RI, PI), lowered the incidence of and improved the recovery rate of AKI, shortened ICU stay, and decreased serum CRP. The cutoff values for AKI diagnosis were 0.61 and 1.28 for RI and PI, respectively. The current research did not reveal any impact on in-hospital mortality and TLC in the studied groups. All cases with AKI in the atorvastatin group were reversible and did not need dialytic support, while four patients in the control group needed RRT. The current study revealed a significant decrease in serum CRP but not in TLC count between studied groups at all follow up points. The anti-inflammatory effects of statins have been extensively studied and shown to be due to decreases in levels of CRP, serum amyloid A protein, and intracellular adhesion molecules [11]. Schnüriger et al. [12] reported that multiple factors may influence TLC in poly-trauma patients. An elevated white blood cell (WBC) count upon admission is nonspecific and does not reliably predict clinical course and outcomes. However, WBC count ≥20.0 is independently associated with severe injury, while that ≤12.5 suggests a low risk. Nonetheless, the sensitivity of these cutoff values in predicting clinical trajectories is limited, and the diagnostic utility of serial WBC counts within the first 24 hours posttrauma is minimal [12].

Supporting data from Hani et al. [13] demonstrated that short-term atorvastatin significantly decreases the percentage of lymphocytes (P<0.001) without affecting overall leukocyte count. Leung et al. [14] found no significant difference in TLC between a control group and patients receiving atorvastatin in a study on blood flow infection. Additionally, Yoon et al. [15] observed statin use to be associated with significant reduction in WBC count and CRP level even after adjusting for potential confounders. The variable inclusion criteria potentially explain these differences in results. Renal vascular derangements due to intra-renal oxygen shunting can lead to AKI. Ultrasound-guided renal artery resistive indices (RI, PI, and MFV) allow the exploration of renal hemodynamics and the prediction of early renal dysfunction. Patients with increased RI are more prone to experience renal injury, especially in the presence of sepsis [16]. Many renal and non-renal variables can alter renal hemodynamic microcirculation, influencing the sensitivity of RI measurements. Pulse pressure, mean arterial pressure [17], heart rate, effective intravascular volume [18], and partial oxygen tension [19] are considered the most important non renal factors that affect RI.

The present study showed significant reduction in RI and PI but not MFV between the studied groups at all follow-up points. ROC analysis of RI and PI was performed for the prediction of AKI. Sensitivity and specificity of RI for the prediction of AKI were 90% and 68%, respectively, when the cutoff was 0.61 with a significant difference (P=0.001). The PI had a sensitivity of 90% and a specificity of 53% when the cutoff value was 1.28 and can be calculated by

PI=(PSV–EDV)/MFV

MFV is calculated as

MFV=(PSV+2×EDV)/3,

Where PSV means peak systolic velocity and EDV, end-diastolic velocity.

The renal artery is a low-resistance vessel and requires perfusion during the whole cardiac cycle (unlike high-resistance vessels such as the external carotid artery), resulting in high diastolic flow or EDV. In cases of poly-trauma and systemic inflammatory response, vasoconstriction impedes diastolic flow (low EDV) and increases PSV. Increased hepatic arterial PSV can be the first sign of acute graft rejection before laboratory findings [20]. Major orthopedic and digestive surgeries are a direct cause of increased renal PI due to purported blood loss and systemic vasoconstriction leading to potential renal ischemia [21]. In the MFV equation, the sum will be divided over three making changes in the values to be comparable. For example, if PSV increases from 50 to 60 cm/sec and EDV decreased from 20 to 15 cm/sec, MFV will be 30 in both intervals while PI will be 1 and 1.3, respectively. Statin anti-inflammatory, immunomodulatory, and anti-thrombotic functions mediate this effect. Statins maintain patency of the vascular lumen, hindering vasoconstriction through indirect action. Statins maintain endothelial function integrity by enhancing the constitutive (non-inflammatory) nitric oxide synthase mediating vasodilatation, increasing smooth muscle relaxation, enhancing the activity of fibrinolysis and tissue plasminogen activator and decreasing that of its inhibitor, and facilitating the functional activity of thrombomodulin, an essential cofactor for protein C activation. On the other hand, statins decrease and inhibit vascular leakage, loss of systemic vascular resistance, excessive vasodilatation, and vasoplegia by inhibiting the inducible (inflammatory) form of nitric oxide synthase [22].

The low specificity of statin compared to sensitivity can be attributed to several factors, including pulse pressure and sympathetic stimulation, which are key determinants of the renal resistive index. High pulse pressure resulting from hyper-dynamic circulation and sympathetic surges can cause significant vasoconstriction, leading to elevated RI that may falsely indicate AKI as reported by Afsar et al. [23]. Many studies align with these results. A clinical trial by Mogawer et al. [24] about the role of RI in prediction of early hepato-renal syndrome reported high sensitivity (100%) and low specificity (66.7%) in prediction of hepato-renal syndrome. They attributed this difference to the cirrhosis-induced vasoconstriction in intra-renal circulation leading to high RI even in a non-azotemic population. Supporting material published by Kim et al. [25] reported that RI >0.8 had sensitivity of 83.3% and specificity 61.9% in prediction of AKI in patients with chronic kidney disease on angiotensin converting enzyme inhibitor or angiotensin receptor blocker. In alignment with the current study, Wang et al. [26] performed a meta-analysis in which they reported that preoperative statin medication had no marked impact on the mortality rate but was linked to a lower risk of major adverse events and acute renal injury following coronary artery bypass graft (CABG) surgery. CABG is well known for its ability to induce systemic inflammation secondary to the use of cardio-pulmonary bypass [26].

The results of the meta-analysis conducted by Vahedian-Azimi et al. [27] do not match ours regarding AKI incidence and ICU stay with statin use postoperatively. Neither ICU stay (P=0.321) nor the development of AKI (P=0.659) was significantly impacted. This discrepancy can be explained by the diversity of the population, which showed significant differences between patients in terms of pathological mechanisms, clinical course, and prognosis.

KEY MESSAGES

▪ Renal artery Doppler is a sensitive mode for early prediction of acute renal injury in a poly-trauma population.

▪ Early atorvastatin administration can shorten intensive care unit stay, provide renal protection, and reduce renal resistive indices.

NOTES

CONFLICT OF INTEREST

No potential conflict of interest relevant to this article was reported.

FUNDING

None.

ACKNOWLEDGMENTS

We thank the Radiology Department, Minia University Hospital for their impactful and helpful role in renal Doppler in our study.

AUTHOR CONTRIBUTIONS

Conceptualization: MMR. Formal analysis: MMR, NSA. Data curation: MMR, EAS. Project administration: NSA. Writing - original draft: EAS. Writing - review & editing: all authors. All authors read and agreed to the published version of the manuscript.

Figure 1.

Sample size calculation by G power system.

Figure 2.

Consolidated Standards of Reporting Trials (CONSORT) flowchart.

Figure 3.

Clustered bar chart represents a comparison among the studied groups regarding the change in the renal index (RI). The data among the studied groups were comparable at admission. Statistically significant differences were observed among the groups at all follow-up points (P=0.04).

Figure 4.

Box plot represents comparison between acute kidney injury (AKI) and non-AKI cases regarding mean resistive index (P=0.02).

Figure 5.

Box plot represents comparison between acute kidney injury (AKI) cases and non-AKI cases regarding mean pulsatility index (P=0.04).

Table 1.

Demographic and clinical data among the studied groups at time of ICU admission

Variable		Group I: atorvastatin (n=53)	Group II: control (n=53)	P-value
Age	Mean±SD (range)	35±9.7 (25–65)	36.5±14.8 (25–70)	0.53
Sex	Male	8 (15.1)	9 (17)	0.7
	Female	45 (84.9)	44 (83)
DM	No	48 (90.6)	49 (92.5)	0.7
	Yes	5 (9.4)	4 (7.5)
HTN	No	46 (86.7)	45 (84.9)	0.3
	Yes	7 (13.3)	8 (15.1)
Day 1 PRBC transfusion	No	51 (96.3)	50 (94.4)	0.9
	Yes	2 (3.7)	3 (5.6)
CRP	Median (IQR)	145 (112–187)	160 (122–180)	0.2
ICU stay (day)	Median (IQR)	5 (5–9)	10 (8–11)	0.004
In-hospital mortality	Yes	0	1 (5)	0.189

Values are presented as number (%) unless otherwise indicated.

ICU: intensive care unit; SD: standard deviation; DM: diabetes mellitus; HTN: hypertension; PRBC: packed red blood cell; CRP: C-reactive protein; IQR: interquartile range.

Independent samples t-test for normally distributed quantitative data between the two groups. Chi-square test for qualitative data between the two groups. Significant level at a P<0.05.

Table 2.

Number of patients with AKI, their KDIGO staging, and the fate of candidates with AKI in the studied groups

Variable	Ator group (n=53)	Control group (n=53)	P-value
AKI	3 (5.7)	17 (32.0)	<0.001
Complete recovery	3 (100)	13 (76.4)	0.001
RRT	0	4 (23.6)	0.02
KDIGO stage			0.001
Stage 1	3 (100)	8 (47.1)
Stage 2	0	5 (29.4)
Stage 3	0	4 (23.5)

Values are presented as number (%).

AKI: acute kidney injury; KDIGO: Kidney Disease: Improving Global Outcomes; RRT: renal replacement therapy.

Mann-Whitney test for non-normally distributed quantitative data between the two groups. Chi-square test for qualitative data between the two groups.

Table 3.

Data about serum creatinine, UOP, SOFA score, TLC, and CRP

Variable	Group I: atorvastatin (n=53)	Group II: control (n=53)	P-value
Serum creatinine
Day 1	0.9 (0.8–1)	1 (0.8–1)	0.42
Day 2	0.9 (0.7–1)	1.4 (0.8–1.7)	0.01
Day 4	0.8^a)(0.7–0.9)	1.8^a)(1.2–2.2)	0.004
UOP
Day 1	1,000±200 (800–1,400)	950±200 (750–1,200)	0.15
Day 2	1,100±150 (850–1,300)	750±250 (550–1,000)^a)	0.03
Day 4	1,200±300 (900–1,550)	800±300 (500–1,100)^a)	0.01
Day 4 SOFA score
Pre-admission	3 (3–5)	4 (3–5)	0.9
Day 1	3 (3–5)	4 (3–5)	0.9
Day 2	3 (3–4)	3 (3–4)	1.0
Day 3	3 (2–4)	3 (2–4)	0.9
Day 4	2 (2–4)	3 (2–4)	0.9
Day 5	1^a) (1–2)	3 (2–4)	0.02
Day 6	1^a) (0–1)	3 (2–3)	0.02
Day 7	0^a)	2 (0–3)	0.01
TLC
Day 1	19.3 (16–23)	19.2 (16–25)	0.9
Day 2	16.8^a)(13.1–21)	17.1^a)(12.1–21)	0.7
Day 4	14^a)(10.2–13)	13^a)(9.6–14)	0.8
CRP
Day 1	135 (108–147)	144 (133–162)	0.9
Day 2	100 (92–122)	133 (118–149)	0.03
Day 4	44 (28–86)	119 (104–138)	0.01

Values are presented as median (interquartile range) or mean±standard deviation (range).

UOP: urine output; SOFA: Sequential Organ Failure Assessment; TLC: total leucocytic count; CRP: C-reactive protein.

^a)Significant difference between the two times within each group at a P<0.05.

Mann-Whitney test for non-normally distributed quantitative data between the two groups. Wilcoxon Signed rank test for not normally distributed quantitative data between two times within each group. Significant level at P<0.05.

Table 4.

Comparison among the studied groups regarding mean PI and mean MFV (cm/sec)

Variable	Time	Group I: atorvastatin (n=53)	Group II: control (n=53)	P-value
PI	At admission	1.2±0.1	1.2±0.4	0.6
	After 6 hr	1.2±0.1	1.5±0.1	0.01
	After 24 hr	1.2±0.1	1.4±0.4	0.02
	After 72 hr	1.1±0.1	1.5±0.7	0.03
MFV	At admission	37.5±1.5	35.5±3.5	0.8
	After 6 hr	35.5±2.5	35.2±4.0	0.6
	After 24 hr	38.1±1.5	38.5±3.5	0.9
	After 72 hr	36.1±3.5	37.5±2.5	0.7

Values are presented as mean±standard deviation.

PI: pulsatility index; MFV: mean flow velocity.

Table 5.

The ROC curve analysis of the resistive index and pulsatility index in prediction of acute kidney injury occurrence

	Resistive index	Pulsatility index
Cutoff value	>0.61	>1.28
AUC	0.89	0.80
95% CI	0.82–0.97	0.67–0.93
P-value	<0.001	<0.001
Sensitivity (%)	90	90
Specificity (%)	68	53
Positive predictive value (%)	90	90
Negative predictive value (%)	59	46.5

ROC: receiver operating characteristic; AUC: area under the curve.

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Effect of atorvastatin as a renal protective agent in patients with systemic inflammatory response syndrome using the renal arterial resistive index

Acute Crit Care. 2025;40(1):95-104. Published online February 18, 2025

DOI: https://doi.org/10.4266/acc.003912

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Figure

Effect of atorvastatin as a renal protective agent in patients with systemic inflammatory response syndrome using the renal arterial resistive index

Figure 1. Sample size calculation by G power system.

Figure 2. Consolidated Standards of Reporting Trials (CONSORT) flowchart.

Figure 3. Clustered bar chart represents a comparison among the studied groups regarding the change in the renal index (RI). The data among the studied groups were comparable at admission. Statistically significant differences were observed among the groups at all follow-up points (P=0.04).

Figure 4. Box plot represents comparison between acute kidney injury (AKI) and non-AKI cases regarding mean resistive index (P=0.02).

Figure 5. Box plot represents comparison between acute kidney injury (AKI) cases and non-AKI cases regarding mean pulsatility index (P=0.04).

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Effect of atorvastatin as a renal protective agent in patients with systemic inflammatory response syndrome using the renal arterial resistive index

Variable		Group I: atorvastatin (n=53)	Group II: control (n=53)	P-value
Age	Mean±SD (range)	35±9.7 (25–65)	36.5±14.8 (25–70)	0.53
Sex	Male	8 (15.1)	9 (17)	0.7
	Female	45 (84.9)	44 (83)
DM	No	48 (90.6)	49 (92.5)	0.7
	Yes	5 (9.4)	4 (7.5)
HTN	No	46 (86.7)	45 (84.9)	0.3
	Yes	7 (13.3)	8 (15.1)
Day 1 PRBC transfusion	No	51 (96.3)	50 (94.4)	0.9
	Yes	2 (3.7)	3 (5.6)
CRP	Median (IQR)	145 (112–187)	160 (122–180)	0.2
ICU stay (day)	Median (IQR)	5 (5–9)	10 (8–11)	0.004
In-hospital mortality	Yes	0	1 (5)	0.189

Variable	Ator group (n=53)	Control group (n=53)	P-value
AKI	3 (5.7)	17 (32.0)	<0.001
Complete recovery	3 (100)	13 (76.4)	0.001
RRT	0	4 (23.6)	0.02
KDIGO stage			0.001
Stage 1	3 (100)	8 (47.1)
Stage 2	0	5 (29.4)
Stage 3	0	4 (23.5)

Variable	Group I: atorvastatin (n=53)	Group II: control (n=53)	P-value
Serum creatinine
Day 1	0.9 (0.8–1)	1 (0.8–1)	0.42
Day 2	0.9 (0.7–1)	1.4 (0.8–1.7)	0.01
Day 4	0.8^a)(0.7–0.9)	1.8^a)(1.2–2.2)	0.004
UOP
Day 1	1,000±200 (800–1,400)	950±200 (750–1,200)	0.15
Day 2	1,100±150 (850–1,300)	750±250 (550–1,000)^a)	0.03
Day 4	1,200±300 (900–1,550)	800±300 (500–1,100)^a)	0.01
Day 4 SOFA score
Pre-admission	3 (3–5)	4 (3–5)	0.9
Day 1	3 (3–5)	4 (3–5)	0.9
Day 2	3 (3–4)	3 (3–4)	1.0
Day 3	3 (2–4)	3 (2–4)	0.9
Day 4	2 (2–4)	3 (2–4)	0.9
Day 5	1^a) (1–2)	3 (2–4)	0.02
Day 6	1^a) (0–1)	3 (2–3)	0.02
Day 7	0^a)	2 (0–3)	0.01
TLC
Day 1	19.3 (16–23)	19.2 (16–25)	0.9
Day 2	16.8^a)(13.1–21)	17.1^a)(12.1–21)	0.7
Day 4	14^a)(10.2–13)	13^a)(9.6–14)	0.8
CRP
Day 1	135 (108–147)	144 (133–162)	0.9
Day 2	100 (92–122)	133 (118–149)	0.03
Day 4	44 (28–86)	119 (104–138)	0.01

Variable	Time	Group I: atorvastatin (n=53)	Group II: control (n=53)	P-value
PI	At admission	1.2±0.1	1.2±0.4	0.6
	After 6 hr	1.2±0.1	1.5±0.1	0.01
	After 24 hr	1.2±0.1	1.4±0.4	0.02
	After 72 hr	1.1±0.1	1.5±0.7	0.03
MFV	At admission	37.5±1.5	35.5±3.5	0.8
	After 6 hr	35.5±2.5	35.2±4.0	0.6
	After 24 hr	38.1±1.5	38.5±3.5	0.9
	After 72 hr	36.1±3.5	37.5±2.5	0.7

	Resistive index	Pulsatility index
Cutoff value	>0.61	>1.28
AUC	0.89	0.80
95% CI	0.82–0.97	0.67–0.93
P-value	<0.001	<0.001
Sensitivity (%)	90	90
Specificity (%)	68	53
Positive predictive value (%)	90	90
Negative predictive value (%)	59	46.5

Table 1. Demographic and clinical data among the studied groups at time of ICU admission

Values are presented as number (%) unless otherwise indicated.

ICU: intensive care unit; SD: standard deviation; DM: diabetes mellitus; HTN: hypertension; PRBC: packed red blood cell; CRP: C-reactive protein; IQR: interquartile range.

Independent samples t-test for normally distributed quantitative data between the two groups. Chi-square test for qualitative data between the two groups. Significant level at a P<0.05.

Table 2. Number of patients with AKI, their KDIGO staging, and the fate of candidates with AKI in the studied groups

Values are presented as number (%).

AKI: acute kidney injury; KDIGO: Kidney Disease: Improving Global Outcomes; RRT: renal replacement therapy.

Mann-Whitney test for non-normally distributed quantitative data between the two groups. Chi-square test for qualitative data between the two groups.

Table 3. Data about serum creatinine, UOP, SOFA score, TLC, and CRP

Values are presented as median (interquartile range) or mean±standard deviation (range).

UOP: urine output; SOFA: Sequential Organ Failure Assessment; TLC: total leucocytic count; CRP: C-reactive protein.

Significant difference between the two times within each group at a P<0.05.

Table 4. Comparison among the studied groups regarding mean PI and mean MFV (cm/sec)

Values are presented as mean±standard deviation.

PI: pulsatility index; MFV: mean flow velocity.

Table 5. The ROC curve analysis of the resistive index and pulsatility index in prediction of acute kidney injury occurrence