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Prevalence & risk factors of multi-morbidity in critically ill patients with sepsis-associated acute kidney injury (SA-AKI)
For correspondence: Dr Venkat Raman Kola, Department of Critical Care Medicine, Yashoda Hospitals, Hyderabad 500 084, Telangana, India e-mail: dr_kvraman@yahoo.co.in
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Received: ,
Accepted: ,
Abstract
Background & Objectives
Multi-morbidity, characterised by the coexistence of two or more chronic conditions, significantly impacts critically ill patients. Among sepsis-associated acute kidney injury (SA-AKI) patients, multi-morbidity contributes to poor clinical outcomes, yet its prevalence and associated risk factors remain under-explored. This study examines the prevalence of multi-morbidity among SA-AKI patients in the intensive care unit (ICU) setting and identifies significant risk factors that influence outcomes.
Methods
A cross-sectional study was conducted on 185 adult ICU patients with SA-AKI in a tertiary intensive care unit between January 2023 and January 2024. Risk factors, biochemical profiles, and clinical outcomes were analysed. Logistic regression was employed to identify predictors of multi-morbidity.
Results
Among 185 SA-AKI patients, the prevalence of multi-morbidity was 38.9 per cent, with older age [≥60 yr, adjusted odds ratio (AOR): 22.11, P<0.0001), chloride imbalance (AOR: 0.42, P=0.023), and albumin imbalance (AOR: 0.10, P=0.018) identified as significant risk factors. The most common comorbidities were hypertension (52.4%) and diabetes mellitus (46.5%). Electrolyte imbalances such as hyponatremia (34.1%) and hypoalbuminemia (77.8%) were prevalent. Patients with multimorbidity had higher mechanical ventilation rates (62.5% vs. 28.3%) and hospital mortality rates (60.6% vs. 23.5%, P<0.001). Renal replacement therapy use was not significantly different between groups.
Interpretation & conclusions
The study highlights the high burden of multi-morbidity in SA-AKI patients, with significant implications for clinical management and outcomes. Comprehensive strategies are needed to address the associated risk factors and improve care in this population.
Keywords
Acute renal injuries
biomarker
comorbidity
critical care outcome
health correlates
septicaemia
Sepsis, a life-threatening condition characterised by a dysregulated immune response to infection, remains one of the leading causes of morbidity and mortality worldwide. The Global Burden of Disease (GBD) study estimated that sepsis was responsible for approximately 11 million deaths in 2017, out of 48.9 million cases globally, with India accounting for a significant share, with 2.9 million deaths1,2. Sepsis frequently leads to multi-organ dysfunction, among which Acute Kidney Injury (AKI) is commonly manifested in 16 to 67 per cent of sepsis patients, significantly influencing their prognosis3.
AKI is diagnosed based on a rapid increase in serum creatinine levels and/or a reduction in urine output, with substantial clinical implications, particularly in critically ill patients4. The condition is associated with high prevalence rates in intensive care units (ICUs), often reaching up to 70 per cent, and is linked to poor outcomes such as prolonged hospitalisation, increased risk of multi-organ failure, and higher mortality4-6. Sepsis-associated acute kidney injury (SA-AKI) results from complex interactions, including hemodynamic instability, reduced glomerular filtration rate, and various toxic and immunological factors that exacerbate renal dysfunction7. In India, studies have reported that SA-AKI affects between 31 per cent and 53 per cent of intensive care units (ICUs) patients5-9, with mortality rates ranging from 52 to 56 per cent across different stages of AKI4,8-13.
Multi-morbidity, defined as the coexistence of two or more chronic conditions in an individual, is becoming increasingly prevalent, affecting about 3 to 68 per cent of the adult population, especially in low- and middle-income countries (LMICs), including India14. Multi-morbidity is associated with poorer health outcomes, including reduced quality of life, increased healthcare needs, and higher treatment costs15. Despite the growing recognition of multi-morbidity’s impact on clinical outcomes, its role in critically ill patients, particularly those with SA-AKI, remains underexplored.
This study aimed to investigate the prevalence of and identify risk factors of multi-morbidity among SA-AKI patients in a tertiary care ICU. Understanding these relationships is crucial for improving clinical management and outcomes in this high-risk population.
Materials & Methods
This was a cross-sectional study conducted at the department of Critical Care Medicine, Yashoda Hospital, Hyderabad, Telangana, India, in adult patients aged 18 yr and above, admitted with sepsis to the ICU from January 2023 to January 2024. The study proceeded after obtaining ethics clearance from the institutional ethics committee. We included patients who stayed in the ICU for at least 72 h and developed AKI within seven days of admission (SA-AKI). The least serum creatinine value during the hospital admission was taken as baseline creatinine, and the stages of the AKI were defined based on the Acute Kidney Injury Network (AKIN) criteria5. Purposive sampling was used to select ICU patients diagnosed with SA-AKI, ensuring the sample was relevant to the study’s focus on multi-morbidity and its impact on outcomes. This method allowed for targeted data collection from individuals who met specific clinical criteria, enhancing the study’s relevance. Patient data was collected after obtaining their signed informed consent. Re-admissions and the patients prognosed to have chronic kidney disease (CKD) were excluded from the study to ensure that the results specifically reflect the acute impact of sepsis on kidney function, rather than the long-term effects of pre-existing kidney conditions. CKD patients often have a baseline decline in kidney function, which could confound the findings related to SA-AKI, as their renal impairment may not be solely attributed to the acute infection. Additionally, re-admissions could introduce bias, as these patients may have different clinical histories or complications that could skew the study’s focus on the initial presentation and progression of SA-AKI.
Variables and definitions
We studied the rates, risk factors, and outcomes associated with multi-morbidity (MM). MM is defined as the presence of two or more chronic medical conditions. Adult body mass index (BMI) range and categories according to the Centers for Disease Control and Prevention (CDC) are underweight (<18.5 kg/m2), healthy weight (18.5-24.9 kg/m2), overweight (25-29.9 kg/m2), and obesity (≥30 kg/m2).
Serum levels of sodium (Na), potassium (K), chloride (Cl), and albumin (alb) were evaluated in this study. Electrolyte imbalances were defined as follows: hyponatremia (Na<135 mEq/l), hypernatremia (Na > 145 mEq/l), hypokalaemia (K< 3.7 mEq/l), hyperkalaemia (K > 5.2 mEq/l), hypochloraemia (Cl < 96 mmol/l), hyperchloraemia (Cl> 106 mmol/l), hypoalbuminemia (alb< 3.4g/dl), and hyperalbuminemia (alb> 5.4g/dl).
Demographic data, source of infection, medical history, comorbidities, and outcomes like mechanical ventilation, need for renal replacement therapy, and hospital mortality (death or discharge) were collected from the medical case sheets. Laboratory values on the admission day were collected from the laboratory electronic database. Serum electrolyte levels recorded and evaluated on day one. The cause of AKI was noted by taking help from the consulting clinician.
Statistics
All the collected data in paper-based forms were entered into a password-protected Microsoft Excel spreadsheet. Data was analysed using STATA version 14.0 (StataCorp LP, College Station, TX, USA). Frequencies and percentages were summarised for the qualitative variables. Age was reported as the median with an interquartile range (IQR), due to the non-normal distribution. The Shapiro-Wilk test was used to assess the assumptions of normality and homogeneity of variances. Chi-square tests were done to find the associations between risk factors and MM as well as MM with outcomes. Uni-variate logistic regression analysis was performed to identify the risk associated with each predictor variable under study. Multi-variate logistic regression was done to determine the independent risk factors of multi-morbidity among SA-AKI patients. Variables for multi-variate logistic regression were selected based on statistical significance in univariate analysis. A P< 0.05 was considered statistically significant.
Results
In our cohort of 185 patients diagnosed with SA-AKI, the median age was 60 yr (IQR: 48, 70), with male predominance of 55.7 per cent (n=103). The BMI categorisation revealed that 57.8 per cent (n=107) had abnormal weight. The majority of patients were in stage II AKI (n=76, 41.1%; Table I). The primary causes of SA-AKI were classified into several categories: acute tubular necrosis accounted for 37.3 per cent (n=69), pre-renal factors represented 32.4 per cent (n=60), multifactorial causes comprised 24.3 per cent (n=45), nephrotoxicity was observed in 3.2 per cent (n=6), and hepato-renal causes were identified in 2.7 per cent (n=5). The most common sources of infection were urinary tract (32.4%, n=60), followed by gastrointestinal system (18.4%, n=34), lungs (15.1%, n=28), and blood stream (14.1%, n=26).
| Parameter | Number (%) |
|---|---|
| Age (yr), median (IQR) | 60 (48,70)* |
| Gender | |
| Male | 103 (55.7) |
| Female | 82 (44.3) |
| BMI | |
| Underweight | 5 (2.7) |
| Normal | 78 (42.2) |
| Overweight | 75 (40.5) |
| Obesity | 27 (14.6) |
| AKI stage | |
| Stage 1 | 52 (28.1) |
| Stage 2 | 76 (41.1) |
| Stage 3 | 57 (30.8) |
| Co-morbidities | |
| Diabetes mellitus | 86 (46.5) |
| Hypertension | 97 (52.4) |
| Coronary artery disease | 18 (9.7) |
| Chronic liver disease | 3 (1.6) |
| Cerebro-vascular accident | 9 (4.9) |
Electrolyte imbalances were frequently observed among participants, with hyponatremia, hypokalaemia, hyperchloremia, and hypoalbuminemia affecting 34.1 per cent (n=63), 25.9 per cent (n=48), 36.7 per cent (n=66), and 77.8 per cent (n=144) of patients, respectively. Elevated serum creatinine levels were noted in 91.9 per cent (n=170), with no patients showing low levels (Figure).

- Distribution of serum electrolyte levels among the study population. Light grey represents hypo-electrolytemia, medium grey represents normal electrolytemia and dark grey represents hyper-electrolytemia)
Diabetes mellitus and hypertension were notably prevalent, with 91.7 per cent (n=66) and 98.6 per cent (n=71) of multi-morbid patients affected, while their rates among overall SA-AKI patients were 46.5 per cent (n=86) and 52.4 per cent (n=97), respectively. In contrast, coronary artery disease was present in 22.2 per cent (n=16) of multi-morbidity patients and 9.7 per cent of those with SA-AKI, while chronic liver disease and cerebrovascular accidents were less common, affecting only 4.2 per cent and 8.3 per cent of multi-morbid patients, respectively.
The prevalence of multimorbidity was found to be 38.9 per cent (n=72). The association of various risk factors and presence of MM, highlighting the statistically significant relationships were displayed in table II. The regression analysis revealed that age, chloride imbalance, and albumin imbalance were significantly associated with multimorbidity. Individuals aged 40-59 yr and 60 yr and above had higher odds of multi-morbidity compared to those aged 18-39 yr, with the association becoming stronger in older age groups [Adjusted odds ratio (AOR) for 40-59 yr: 7.25, P=0.018; AOR for 60 yr and above: 22.11, P<0.001]. Those with chloride imbalance and albumin imbalance were less likely to be associated with multimorbidity, with significant AOR values of 0.42 and 0.10, respectively. Conversely, while stage 3 AKI initially showed lower odds of multi-morbidity (UOR: 0.35, P=0.012), this association weakened after adjustment (AOR: 0.41, P=0.061), and stage 2 AKI showed no significant association with multi-morbidity. Other factors like gender, BMI, and potassium imbalance did not demonstrate consistent associations with MM (Table III).
| Parameter | Multi-morbidity, n (%) | P value | |
|---|---|---|---|
| Yes (n=72) | No (n=113) | ||
| Age (yr) | |||
| 18-39 | 2 (6.9) | 27 (93.1) | <0.001* |
| 40-59 | 17 (27.4) | 45 (72.6) | |
| 60 & above | 53 (56.4) | 41 (43.6) | |
| Gender | |||
| Male | 44 (42.7) | 59 (57.3) | 0.235 |
| Female | 28 (34.2) | 54 (65.8) | |
| BMI (kg/m2) | |||
| Underweight | 3 (60) | 2 (40) | 0.304 |
| Normal | 25 (32.1) | 53 (67.9) | |
| Overweight | 31 (41.3) | 44 (58.7) | |
| Obesity | 13 (48.2) | 14 (51.8) | |
| AKI stage | |||
| Stage 1 | 25 (48.1) | 27 (51.9) | 0.024* |
| Stage 2 | 33 (43.4) | 43 (56.6) | |
| Stage 3 | 14 (24.6) | 43 (75.4) | |
| Sodium imbalance | |||
| Yes | 38 (43.2) | 50 (56.8) | 0.257 |
| No | 34 (35.1) | 63 (64.9) | |
| Potassium imbalance | |||
| Yes | 33 (41.7) | 46 (58.3) | 0.492 |
| No | 39 (36.8) | 67 (63.2) | |
| Chloride imbalance | |||
| Yes | 25 (27.8) | 65 (72.2) | 0.002* |
| No | 47 (49.5) | 48 (50.5) | |
| Albumin imbalance | |||
| Yes | 50 (34.7) | 94 (65.3) | 0.028* |
| No | 22 (53.6) | 19 (46.4) | |
P*<0.05
| Risk factor | Category | UOR (95% CI) | P value | AOR (95%CI) | P value |
|---|---|---|---|---|---|
| Age (yr) | 18-39 | Reference | |||
| 40-59 | 5.099 (1.09, 23.81) | 0.038* | 7.25 (1.41, 37.26) | 0.018* | |
| 60 & above | 17.45 (3.92, 77.67) | <0.001* | 22.11 (4.54, 107.59) | <0.001* | |
| AKI stage | Stage 1 | Reference | |||
| Stage 2 | 0.83 (0.41, 1.68) | 0.603 | 0.96 (0.41, 2.25) | 0.931 | |
| Stage 3 | 0.35 (0.15, 0.79) | 0.012* | 0.41 (0.16, 1.04) | 0.061 | |
| Chloride imbalance | No | Reference | |||
| Yes | 0.39 (0.21, 0.72) | 0.003* | 0.42 (0.20, 0.89) | 0.023* | |
| Albumin imbalance | No | Reference | |||
| Yes | 0.46 (0.23, 0.93) | 0.03* | 0.10 (0.02, 0.68) | 0.018* | |
P*<0.05. UOR, unadjusted odds ratio (representing the crude association between risk factors and MM without controlling for confounding variables); AOR, adjusted odds ratio (representing the association after accounting for potential confounders)
Among participants with multi-morbidity, 62.5 per cent (n=45) required mechanical ventilation, compared to only 28.3 per cent (n=32) of those without. The vast majority of both groups did not require renal replacement therapy, with 95.8 per cent (n=69) of multi-morbid patients and 95.6 per cent (n=108) of non-multi-morbid patients. All-cause mortality during hospital stays was significantly higher among patients with multi-morbidity (60.6%; n=43; Table IV).
| Outcome variable | Multi-morbidity, n (%) | P value | |
|---|---|---|---|
| Yes (n=72) | No (n=113) | ||
| Need for mechanical ventilation | |||
| Yes | 45 (58.4) | 32 (41.6) | <0.001* |
| No | 27 (25) | 81 (75) | |
| Need for renal replacement therapy | |||
| Yes | 3 (37.5) | 5 (62.5) | 0.933 |
| No | 69 (38.9) | 108 (61.1) | |
| All-cause mortality within hospital stay | |||
| Yes | 43 (66.2) | 22 (33.8) | <0.001* |
| No | 28 (23.5) | 92 (76.5) | |
P*<0.05
Discussion
The prevalence of multi-morbidity among patients diagnosed with SA-AKI in our study was found to be 38.9 per cent, highlighting a significant burden of chronic health conditions in this population. Studying the risk factors and role of multi-morbidity in influencing outcomes among critically ill patients, especially with sepsis, is crucial in the management of SA-AKI. Failure of which may worsen the condition, leading to multiple organ dysfunction or failure and even death.
The demographic analysis of our participants revealed a broad age range, with significant findings related to the association between age and multimorbidity. The majority of patients were aged between 48 and 77 years, with a notable increase in multi-morbidity among those aged 63 to 77 years, with 45.8 per cent being multi-morbid. Like other studies investigating multi-morbidity among varied diagnoses, we observed multi-morbidity increasing with age, demonstrating a positive association16-19. Older patients often had a greater burden of chronic diseases, which could contribute to the severity of acute conditions like SA-AKI.
Our findings also revealed a male predominance (55.7%) in the cohort. Although this difference was not statistically significant, it reflected a trend noted in other studies where male patients often presented with more severe comorbidities and worse outcomes19-21. It is essential to consider gender differences in multi-morbidity when developing care strategies, as these may influence both the presentation and management of SA-AKI21.
Obese patients are prone to multiple chronic health conditions, including an increase in the prevalence of diabetes22. Our study focused on the co-occurrence of morbidities, and thereby, the effect these diseases could have on clinical outcomes when combined rather than individually. Diabetes mellitus and hypertension were prevalent among patients with multi-morbidity, affecting 91.7 per cent and 98.6 per cent of this group, respectively, which was similar to the studies in which hypertension and DM were documented as the most common comorbidities among sepsis patients17,23,24. While studies conducted in Palestine, Middle East Asia, and Saudi Arabia reported CVD as common19,21,25.
Our study found that 76.4 per cent (n=55) of patients had at least two comorbidities, followed by 22.2 per cent and 1.4 per cent with three and four comorbidities, respectively. Such proportions were higher than those documented from Nepal (12.9%) and Jordan (62.2%)26-28.
The association between diabetes, hypertension, and kidney function deterioration is well-documented, underscoring the need for monitoring and managing these chronic conditions in at-risk populations. The high rates of these comorbidities in our cohort suggested that patients with SA-AKI often had multiple health challenges that might have complicated their clinical management.
Electrolyte imbalances were prevalent among our participants, with hyponatremia and hypoalbuminemia being particularly common in the multi-morbid group. This finding was slightly different from a study conducted in Kathmandu with hypokalaemia in 8.99 per cent among 59.7 per cent sepsis-associated AKI patients26; further emphasising the need for nutritional and metabolic monitoring in this population.
The sources of infection among our study participants were quite significant, with urinary tract infections being the most prevalent, accounting for 32.4 per cent of cases, followed by gastrointestinal (18.4%) and lung infections (15.1%). This finding was similar to other studies26,29,30. The significant association between specific infection types and multimorbidity, particularly lung and skin infections, suggests that patients with multiple comorbidities may have had a higher susceptibility to severe infections, complicating their clinical management.
Among the multimorbid SA-AKI patients, 62.5 per cent required mechanical ventilation, compared to only 28.3 per cent of those without multimorbidity. This aligns with the findings of a study conducted in other parts of India27 that showed significantly higher ventilator requirement rates compared to studies from other geographical settings such as Egypt, Europe and Nepal19,26,31.
Interestingly, while the need for renal replacement therapy (RRT) did not show a significant difference between the groups, the majority of both multi-morbid and non-multi-morbid patients did not require this treatment. This finding suggests that, while multi-morbidity increases the complexity of care, it may not necessarily translate to an increased need for RRT in all cases. Future studies could explore this relationship further to clarify the implications of multi-morbidity on renal management strategies. RRT had a significant association with sepsis mortality, aligning with the literature32.
The all-cause mortality rate during hospital stays was significantly higher among patients with MM, with 60.6 per cent; similar to the findings of 32.2 to 75 per cent ICU mortality in varied geographical settings23,30,33. Literature also suggests that an increase in the number of comorbidities increases the odds of death23.
This study had several strengths, including its focus on the critical issue of SA-AKI and the underexplored role of MM in critically ill patients, particularly in LMICs like India. It identifies key risk factors associated with poor outcomes, highlighting the clinical relevance of addressing both acute and chronic health conditions in this high-risk population. Additionally, the study provided real-world insights into the prevalence of multi-morbidity and its association with increased mortality, mechanical ventilation needs, and complications in SA-AKI patients, contributing valuable information for improving patient care and clinical management strategies. By exploring these relationships in the context of sepsis and kidney injury, the study laid the groundwork for future research.
However, our investigation had a few limitations. The cross-sectional study design limited the ability to establish causal relationships between MM and SA-AKI outcomes. A longitudinal study may help develop a deeper understanding of such associations. Furthermore, there may be unmeasured confounding factors, like genetic predispositions or undetected comorbidities, which could have influenced the outcomes. Participants were selected using purposive sampling due to operational and logistical constraints. While purposive sampling allowed for targeted data collection, we acknowledge that a consecutive sampling approach would have reduced potential selection bias and improved generalisability. Lastly, the accuracy of the results depended on the completeness and reliability of the medical records, which could introduce potential reporting errors or omissions. While missing or incomplete data were minimal (less than 5%), particularly in laboratory results and documentation of comorbidities, we acknowledge that such omissions could have a small impact on the results.
Declaration
The study abstract was presented at the fifth Annual conference of Epidemiology Foundation of India, 2024, by the first author (SSM).
Financial support & sponsorship
None.
Conflicts of Interest
None.
Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation
The authors confirm that there was no use of AI-assisted technology for assisting in the writing of the manuscript and no images were manipulated using AI.
References
- The third international consensus definitions for sepsis and septic shock (Sepsis-3) JAMA. 2016;315:801-10.
- [Google Scholar]
- A European renal best practice (ERBP) position statement on the kidney disease improving global outcomes(KDIGO) clinical practice guidelines on acute kidney injury: Part 1: Definitions, conservative management and contrast-induced nephropathy. Nephrol Dial Transplant. 2012;27:4263-72.
- [Google Scholar]
- A novel risk-predicted nomogram for sepsis associated-acute kidney injury among critically ill patients. BMC Nephrol. 2021;22:173.
- [Google Scholar]
- Sepsis-associated acute kidney injury: Consensus report of the 28th acute disease quality initiative workgroup. Nat Rev Nephrol. 2023;19:401-17.
- [Google Scholar]
- Septic acute kidney injury in critically ill Indian patients. Indian J Crit Care Med. 2013;17:49-52.
- [Google Scholar]
- Epidemiology and outcomes of acute kidney injury in critically ill: Experience from a tertiary care center. Indian J Nephrol. 2018;28:413-20.
- [Google Scholar]
- Spectrum of acute kidney injury in critically ill patients: A single center study from South India. Indian J Nephrol. 2014;24:280-5.
- [Google Scholar]
- The effects of alternative resuscitation strategies on acute kidney injury in patients with septic shock. Am J Respir Crit Care Med. 2016;193:281-7.
- [Google Scholar]
- A pharmacoepidemiologic study of community-dwelling, disabled older women: Factors associated with medication use. Am J Geriatr Pharmacother. 2010;8:215-24.
- [Google Scholar]
- Multimorbidity states associated with higher mortality rates in organ dysfunction and sepsis: A data-driven analysis in critical care. Crit Care. 2019;23:247.
- [Google Scholar]
- Profile of comorbidity and multimorbidity among women attending antenatal clinics: An exploratory cross-sectional study from Odisha, India. J Family Med Prim Care. 2022;11:1980-8.
- [Google Scholar]
- Association of in-hospital multimorbidity with healthcare outcomes in Swiss medical inpatients. Swiss Med Wkly. 2021;151:w20405.
- [Google Scholar]
- Community-versus nosocomial-acquired severe sepsis and septic shock in patients admitted to a tertiary intensive care in Saudi Arabia, etiology and outcome. J Infect Public Health. 2015;8:418-24.
- [Google Scholar]
- The role of infection and comorbidity: Factors that influence disparities in sepsis. Crit Care Med. 2006;34:2576-82.
- [Google Scholar]
- Epidemiology of sepsis syndrome among intensive care unit patients at a Tertiary university hospital in Palestine in 2019. Indian J Crit Care Med. 2020;24:551-6.
- [Google Scholar]
- Comorbidity and intensive care outcome – A multivariable analysis. J Intensive Care Soc. 2014;15:205-12.
- [Google Scholar]
- Comorbid conditions predict outcomes in patients with severe sepsis. Chest. 2016;149:A170.
- [Google Scholar]
- Prevalence and outcomes of chronic comorbid conditions in patients with sepsis in Korea: A nationwide cohort study from 2011 to 2016. BMC Infect Dis. 2024;24:184.
- [Google Scholar]
- Community-and healthcare-associated infections in critically ill patients: A multicenter cohort study. Int J Infect Dis. 2015;37:80-5.
- [Google Scholar]
- Sepsis among patients admitted to the intensive care unit of a tertiary care centre. JNMA J Nepal Med Assoc. 2023;61:691-4.
- [Google Scholar]
- Clinical profile and outcome of patients with severe sepsis treated in an intensive care unit in India. Ceylon Med J. 2016;61:181-4.
- [Google Scholar]
- Characteristics of adult sepsis patients in the intensive care units in a tertiary hospital in Jordan: An observational study. Crit Care Res Pract. 2021;2021:2741271.
- [Google Scholar]
- A study of clinical profile of sepsis in patients admitted in intensive care unit at tertiary care hospital. Med Pulse Int J Med. 2022;21:78-83.
- [Google Scholar]
- Prevalence and outcome of sepsis and septic shock in intensive care units in Addis Ababa, Ethiopia: A prospective observational study. Afr J Emerg Med. 2021;11:188-95.
- [Google Scholar]
- Sepsis occurrence in acutely ill patients investigators. Sepsis in European intensive care units: results of the SOAP study. Crit Care Med. 2006;34:344-53.
- [Google Scholar]
- Acute renal failure in patients with sepsis in a surgical ICU: Predictive factors, incidence, comorbidity, and outcome. J Am Soc Nephrol. 2003;14:1022-30.
- [Google Scholar]
- Sepsis and underlying comorbidities in intensive care unit patients. Med Klin Intensivmed Notfmed. 2024;119:123-8.
- [Google Scholar]
