Sepsis is a potentially life-threatening condition that represents a dysregulated host response to infection, causing acute organ dysfunction, and substantial hospital mortality [1]. Acute kidney injury (AKI) is one of the complications, with high incidence and adverse clinical outcomes, prolonged hospitalisation and higher costs of hospital care [2,3]. The pathophysiology of Sepsis associated acute kidney injury (SA-AKI) is complex and includes systemic inflammation, endothelial dysfunction, microcirculatory disturbances, oxidative stress and decrease in cell metabolism [4]. It is seen widely depending on level of disease activity, patient factors, clinical context and the diagnostic criteria used. Standardized diagnostic criteria is then vital for correct identification and classification of AKI in the hospital setting [2,5].

There are several factors that affect the development of AKI in those with sepsis, including some demographic, clinical and treatment-related factors. Factors that may predispose to renal injury include advanced age, diabetes mellitus, hypertension, pre-existing chronic renal disease and cardiovascular disease [6,7]. In addition, certain factors, such as septic shock, hypotension, elevated lactate levels, mechanical ventilation, vasopressor usage, and exposure to nephrotoxic medications, are known risk factors for SA-AKI [8,9]. Increased mortality, longer intensive care unit (ICU) stay and a higher risk for renal replacement therapy (RRT) are also linked to the severity and progression of kidney injury [10,11]. Early identification of these factors is crucial to recognize vulnerable patients and to avoid worsening of renal function [12].

Although there has been growing evidence internationally, the incidence and risk factors for SA-AKI continue to vary by healthcare setting. Data on the burden and independent clinical predictors of AKI in the context of sepsis is limited from Pakistan. Variations in patient characteristics, infection patterns, health services, and care delivery have been observed, which emphasizes the importance of data and evidence that are relevant to the local context.

Research Objective

To determine the prevalence and identify the clinical and demographic determinants of AKI among hospitalized patients with sepsis.

Study Design

An analytical cross-sectional study was designed to assess the prevalence and the determinants of AKI in the hospitalized patient with sepsis.

Study Duration

The study was carried out from January to December 2024 for one year.

Study Population

A total of 200 patients 18 years of age and above who were admitted into the medical wards and intensive care unit with the clinical diagnosis of sepsis were studied.

Inclusion Criteria

The study included hospitalized adults (18 years or older) that met the Sepsis-3 diagnostic criteria and gave informed consent.

Exclusion Criteria

The patients who had pre-existent end-stage renal disease, patients on maintenance dialysis, patients with incomplete medical records, and declined to attend were excluded.

Sample Size Calculation and Sampling Technique

A sample of 210 patients was used in the study. The sample size was calculated based on WHO formula for prevalence estimation, with a presumption of 95% confidence interval, and an appropriate margin of error of 5% for the anticipated prevalence of AKI and apply it. This was a consecutive sampling and eligible patients were recruited until the required sample size was reached.

Data Collection Procedure

Both a structured questionnaire and hospital records were used to collect data. Data on age, gender, comorbidities, clinical presentation, vital signs, laboratory investigations and treatment-related factors were documented. AKI was detected by measuring renal function in terms of serum creatinine and urine output.

Operational Definitions

Sepsis was defined as per the Sepsis-3 criteria. The diagnosis of AKI was based on the Kidney Disease: Improving Global Outcomes (KDIGO) criteria: serum creatinine level greater than or equal to 0.3 mg/dL in 48 hours; greater than or equal to 1.5 times baseline in seven days; or less than 0.5 mL/kg/hour for 6 hours. Sepsis-3 criteria were used to define septic shock.

Study Variables

The dependent variable was the occurrence of AKI. Data collected included independent variables such as age, gender, diabetes mellitus, hypertension, pre-existing kidney disease, septic shock, hypotension, severity of sepsis, mechanical ventilation, use of vasopressors, and laboratory parameters.

Data Analysis

The data were analysed using suitable statistical software SPSS (Version 25). Descriptive statistics were employed to describe the demographic and clinical features. The categorical variables were summarized as frequencies and percentages, and the continuous variables were summarized as a mean and standard deviation or a median and interquartile range (IQR), whichever is applicable. Chi-square test, independent-sample t-test, and the appropriate non-parametric tests were used to evaluate the relationships between AKI and independent variables. multivariable logistic regression was used to determine independent risk factors for AKI. A p value of <0.05 was deemed as statistically significant.

The sociodemographic and clinical data of 210 patients with sepsis are described in table 1. The largest age group was 46–60 years (31.43%), followed by patients aged above 60 years (30.48%). The majority of the participants were male (60.95%) and urban residents (56.67%). AKI was seen in 96 patients (45.71%) and in 114 patients (54.29%) no AKI was observed. Regarding KDIGO staging, 41 patients (19.52%) had stage 1, 33 (15.71%) had stage 2, and 22 (10.48%) had stage 3 AKI. The most prevalent comorbidities were hypertension (38.57%) and diabetes mellitus (34.29%), and the most frequent source of infection was respiratory tract infections (37.14%).

Table 1. Sociodemographic and clinical characteristics, prevalence and KDIGO staging of AKI among patients with sepsis (N = 210)

Note: KDIGO stages are reported as percentages of the total study population (N = 210). Comorbidities and clinical interventions were non-mutually exclusive; therefore, their cumulative percentages may exceed 100%.

Table 2 describes the admission laboratory parameters of the study participants. The mean hemoglobin level was 10.82 ± 2.14 g/dL, while the mean total leukocyte count was 15,420 ± 5,630 cells/mm³. The mean platelet count was 186,450 ± 72,380 cells/mm³. Mean serum creatinine and blood urea levels were 1.84 ± 1.12 mg/dL and 68.40 ± 31.25 mg/dL, respectively. The mean serum lactate was 3.12 ± 1.48 mmol/L, while mean potassium and sodium levels were 4.51 ± 0.72 mEq/L and 136.20 ± 5.80 mEq/L, respectively.

Table 2. Admission laboratory parameters of patients with sepsis (N = 210)

Table 3 shows the bivariate association between demographic and baseline clinical characteristics and AKI status. Patients with AKI were significantly older than those without AKI (55.42 ± 14.80 vs. 48.16 ± 15.22 years, p = 0.001). AKI was significantly associated with age above 45 years (71.88% vs. 53.51%, p = 0.006), diabetes mellitus (43.75% vs. 26.32%, p = 0.008), hypertension (46.88% vs. 31.58%, p = 0.023), and pre-existing chronic kidney disease (19.79% vs. 5.26%, p = 0.001). However, gender, residence, cardiovascular disease, and infection source were not significantly associated with AKI (p > 0.05).

Table 3. Bivariate association of demographic and baseline clinical features with AKI status (N = 210)

*Statistically significant at p < 0.05. Categorical variables expressed as n (%), assessed via Pearson’s Chi-square (χ²) test; continuous age assessed via Independent-samples t-test.

Table 4 presents the comparison of clinical presentation and laboratory parameters according to AKI status. Septic shock (51.04% vs. 25.44%, p < 0.001), persistent hypotension (62.50% vs. 37.72%, p < 0.001), mechanical ventilation (34.38% vs. 16.67%, p = 0.003), vasopressor requirement (44.79% vs. 22.81%, p = 0.001), and nephrotoxic drug exposure (30.21% vs. 15.79%, p = 0.014) were significantly more frequent among patients with AKI. Laboratory findings also showed significant differences, including lower hemoglobin (10.45 ± 2.08 vs. 11.13 ± 2.15 g/dL, p = 0.021) and platelet counts (168.20 ± 68.40 vs. 201.80 ± 72.50 × 10³ cells/mm³, p = 0.001), while leukocyte count, serum creatinine, blood urea, lactate, and potassium levels were significantly higher among patients with AKI (all p ≤ 0.001).

Table 4. Bivariate comparison of clinical presentation and laboratory parameters by AKI status (N = 210)

*Statistically significant (p < 0.05). Assessed via Chi-square test for percentages and Independent-samples t-test for continuous laboratory markers.

Table 5 presents the multivariable logistic regression analysis identifying independent determinants of AKI among patients with sepsis. Diabetes mellitus was independently associated with AKI (aOR = 2.12, 95% CI: 1.11–4.05, p = 0.023), as were pre-existing chronic kidney disease (aOR = 3.84, 95% CI: 1.36–10.85, p = 0.011), septic shock (aOR = 2.45, 95% CI: 1.22–4.92, p = 0.012), and serum lactate above 2.5 mmol/L (aOR = 2.38, 95% CI: 1.21–4.68, p = 0.012). Age above 45 years (p = 0.058), vasopressor requirement (p = 0.183), and nephrotoxic exposure (p = 0.060) were not statistically significant after adjustment. The overall regression model was statistically significant (p < 0.001), with a Nagelkerke R² of 0.306

Table 5. Multivariable logistic regression analysis for independent determinants of AKI in sepsis (N = 210)

Model Statistics: Omnibus Test of Model Coefficients χ² = 54.38, p < 0.001; Hosmer-Lemeshow Test χ² = 6.42, p = 0.600; Nagelkerke R² = 0.306. Dependent variable: Presence of AKI (1 = Yes, 0 = No). *Statistically significant independent determinants (p < 0.05).

The present study showed that 45.71% of 210 sepsis patients had AKI of the hospitalized population. Regarding severity, 41 (19.52%) patients had KDIGO stage 1, 33 (15.71%) had stage 2, and 22 (10.48%) had stage 3 AKI. The prevalence is similar to that reported by Liu et al. [13] in their systematic review which showed that AKI was a common complication of sepsis in the hospital and in critical care settings. In a similar study, Song et al. [14] found that AKI occurred in 62.3% of all 5,100 critically ill patients who developed septicemia, though the higher prevalence could be attributed to differences in case definition and severity of patients in the intensive care units. The burden of AKI in critically ill patients was also shown to be significant by Hoste et al. in a multinational study (AKI-EPI) [15] where early identification and monitoring was emphasized.

The present study revealed that patients who developed AKI were significantly older than those who did not develop AKI (55.42 ± 14.80 years old versus 48.16 ± 15.22 years old; p = 0.001). The bivariate analysis also showed that age over 45 years was associated with AKI (71.88% vs 53.51% p=0.006). Diabetes mellitus (43.75% versus 26.32%; p = 0.008), hypertension (46.88% versus 31.58%; p = 0.023), and pre-existing chronic kidney disease (CKD) (19.79% versus 5.26%; p = 0.001) were significantly more frequent among patients with AKI. They are in agreement with the findings of Liu et al. [13] who found diabetes and hypertension to be significant contributors to sepsis-associated AKI. Hoste et al. [15] also highlighted the role of underlying patient factors and comorbidities on the vulnerability to develop AKI. But the age > 45 years was not independent in the adjusted model.

AKI was significantly correlated with hemodynamic instability and severe complications associated with sepsis. Septic shock was found in 51.04% of patients with AKI and 25.44% without AKI (p < 0.001), and persistent hypotension was seen in 62.50% and 37.72% (p < 0.001), respectively. Mechanical ventilation (34.38% versus 16.67%; p = 0.003), vasopressor use (44.79% versus 22.81%; p = 0.001), and nephrotoxic exposure (30.21% versus 15.79%; p = 0.014) were also significantly associated with AKI. Liu et al. [13] also found septic shock, use of vasopressors, and mechanical ventilation to be factors associated with sepsis-related AKI. Peerapornratana et al. [16] described renal injury which occurs during sepsis as a result of systemic inflammation, microcirculation dysfunction, and hemodynamic changes. The ADQI consensus report also stresses how important it is to have careful hemodynamic evaluation and to manage fluids and vasopressors individually [17].

Laboratory results also showed significant differences

between the groups. Patients with AKI had higher total leukocyte counts (17.10 ± 5.82 versus 14.00 ± 5.12 × 10³ cells/mm³; p < 0.001), blood urea (88.50 ± 29.80 versus 51.40 ± 21.60 mg/dL; p < 0.001), lactate (3.75 ± 1.42 versus 2.59 ± 1.30 mmol/L; p < 0.001), and potassium levels (4.78 ± 0.68 versus 4.28 ± 0.67 mEq/L; p < 0.001). Hemoglobin and platelet levels were significantly lower among patients with AKI. This study indicates more inflammatory and metabolic dysfunction in patients with the disease. Peerapornratana et al. [16] identified three mechanisms important to sepsis-associated kidney injury: inflammatory responses, microvascular dysfunction, and abnormalities of cellular metabolism. The ADQI consensus report also emphasizes the need to monitor the patients' renal function, fluid balance, and electrolyte disturbances [17]. The higher creatinine level in the patients with AKI seems more in keeping with the definition of an AKI and therefore is likely more related to the diagnosis than any other parameter.

In multivariable analysis, diabetes mellitus (adjusted OR = 2.12; 95% CI: 1.11–4.05; p = 0.023), pre-existing CKD (adjusted OR = 3.84; 95% CI: 1.36–10.85; p = 0.011), septic shock (adjusted OR = 2.45; 95% CI: 1.22–4.92; p = 0.012), and lactate above 2.5 mmol/L (adjusted OR = 2.38; 95% CI: 1.21–4.68; p = 0.012) remained independently associated with AKI. However, after adjustment, age > 45 years, vasopressor use, and nephrotoxic exposure did not remain statistically significant. The results corroborate the results of Liu et al. [13] and the clinical model introduced by Zarbock et al. [17] that stresses the synergistic effect of underlying renal vulnerability and severity of sepsis. The model was statistically significant (Omnibus χ² = 54.38; p < 0.001), the Nagelkerke R² value was 0.306 and the Hosmer–Lemeshow test was not significant (p = 0.600).

Taken together, the results indicate that AKI is a frequent complication of sepsis-related hospitalisation and linked to pre-existing comorbidities, biochemical abnormalities and hemodynamic instability. The findings recommend the regular evaluation of renal function, uric production, lactate and electrolytes, particularly in diabetic or CKD patients and in septic shock. Careful consideration of potentially nephrotoxic medications, early identification of high-risk patients and appropriate hemodynamic management can help minimize preventable kidney injury. The critical role of early identification and follow up care for potential renal complications later in the development of AKI is also highlighted in the literature on AKI and chronic kidney disease [18].

Strengths and Limitations

The use of Sepsis-3 and KDIGO criteria for sepsis and AKI, respectively, and the evaluation of a large set of demographic, clinical, hemodynamic and laboratory variables are some of the main strengths of this study. In addition, a multivariable logistic regression analysis was conducted to determine factors independently associated with the development of AKI after adjustment for potential confounding factors. This study has its limitations, however. The results might not be generalizable to other health care settings because of its single-center design at PIMS, Islamabad. Selection bias may also have been introduced due to the relatively small sample size and consecutive sampling technique. Furthermore, the cross-sectional study design doesn't allow for temporal relationships or causal associations between identified risk factors and AKI to be determined. It is known that unmeasured residual confounding is not excluded, and that follow-up was not performed longitudinally, which fails to allow for the assessment of renal recovery, chronic kidney disease and long-term patient outcome.

AKI is common in hospitalised patients with sepsis and linked to chronic kidney disease (CKD) and diabetes mellitus (DM) and is more likely in those with severe clinical disease including septic shock and raised lactate levels. Regular assessment of renal function, hemodynamic status and biochemical parameters is key for early identification of high-risk patients. The burden of kidney injury can be minimized by timely and adequate management of sepsis and optimizing hemodynamic stability while avoiding unnecessary nephrotoxic exposures. These findings should be confirmed by additional multicenter prospective studies and followed up for renal outcomes.

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