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Association between serum osmolality and deteriorating renal function in patients with acute myocardial infarction: analysis of the MIMIC- IV database

BMC Cardiovascular Disorders volume 24, Article number: 490 (2024) Cite this article

Abstract

Background

To investigate the association between serum osmolality and deteriorating renal function in patients with acute myocardial infarction (AMI).

Methods

Three thousand eight hundred eighty-five AMI patients from the Medical Information Mart for Intensive Care IV were enrolled for this study. The primary outcome was deteriorating renal function. Secondary outcomes included the new-onset of acute kidney injury (AKI) and progress of AKI. < 293.2725 mmol/L was defined as low serum osmolality, and ≥ 293.2725 mmol/L as high serum osmolality based on upper quartile. Univariate and multivariate logistic regression models were used to explore the associations between serum osmolality and the development of deteriorating renal function, the new-onset of AKI and progress of AKI among AMI patients. Subgroup analysis was also conducted.

Results

One thousand three hundred ninety-three AMI patients developed deteriorating renal function. After adjusting all confounding factors, high serum osmolality was associated with increased risk of deteriorating renal function [odds ratio (OR) = 1.47, 95% confidence interval (CI): 1.22–1.78], new-onset of AKI (OR = 1.31, 95% CI: 1.01–1.69), and progress of AKI risk (OR = 1.26, 95% CI: 1.01–1.59) among AMI patients. In addition, when the stratified analysis was performed for age, AMI type, cardiogenic shock, and estimated glomerular filtration rate (eGFR), high serum osmolality was risk factor for the risk of deteriorating renal function among patients aged 65 years or older, without cardiogenic shock, and with an eGFR ≥ 60 mL/min/1.73m2.

Conclusion

Higher serum osmolality increased the risk of deteriorating renal function among AMI patients.

Peer Review reports

Background

Acute myocardial infarction (AMI) is the necrosis of the myocardium resulting from acute and persistent ischemia and hypoxia of the coronary arteries, making it a prevalent condition in intensive care units (ICUs) [1]. Deterioration of renal function, including the occurrence of acute kidney injury (AKI), is a prevalent complication observed in patients with AMI, leading to a significantly heightened risk of mortality [2,3,4]. Therefore, identification of early biomarkers for deteriorating renal function in patients with AMI is crucial for effective disease management.

Serum osmolality is the cumulative osmolality of ions and particles dissolved in body fluid, which is affected by the concentration of sodium (Na), potassium (K), glucose, and urea [5]. The presence of elevated serum osmotic pressure, indicative of dehydration, constitutes a significant risk factor for renal function impairment [5, 6]. Yang J and colleagues reported that there was a significant correlation of both early high serum osmolality and low serum osmolality with an increased risk of development of AKI for critically ill patients [7]. Elevated serum osmolality is considered an independent risk factor for the development of chronic kidney disease [8]. In addition, high level of plasma osmolality has the potential to serve as a prognostic indicator for the short-term mortality among acute coronary syndrome patients undergoing coronary stenting [9]. A retrospective observational clinical study also pointed out that elevated serum osmolality at intensive care unit (ICU) admission was related to an increased mortality risk in critically ill patients [10]. These findings imply that serum osmolality could serve as a valuable prognostic indicator for diverse diseases. However, to the best of our knowledge, the relationship between serum osmolality and the development of deteriorating renal function in AMI patients has not been investigated.

Therefore, the objective of this study was to analyze the correlation between serum osmolality and the risk of deteriorating renal function in patients with AMI, utilizing a publicly available database, which providing a basis for disease monitoring, treatment decision-making, and prognosis improvement in AMI patients.

Methods

Study population

All data utilized in this analysis was obtained from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, encompassing the medical records of 382,278 in-patients who received care at the Beth Israel Deaconess Medical Center across the United States 2008–2019 [11]. This database includes patient demographics, laboratory measurements, medications administered, vital signs documented, and so on [12]. The institutional review board at Massachusetts Institute of Technology has obtained consent for the collection of data and approved the establishment of the database. The requirement of ethical approval for this was waived by the Institutional Review Board of Chengdu Second People's Hospital, because the data was accessed from MIMIC-IV (a publicly available database). The need for written informed consent was waived by the Institutional Review Board of Chengdu Second People's Hospital due to retrospective nature of the study. All methods were performed in accordance with the relevant guidelines and regulations.

We included patients diagnosed as AMI at ICU admission were extracted from MIMIC-IV database. International Classification of Diseases, Ninth Revision (ICD-9) codes 41000–41092 were used to identify patients with AMI. Exclusion criteria: (1) patients aged < 18 years old; (2) patients with missing information of sodium, potassium, glucose, urea and AKI; (3) patients diagnosed as end-stage renal disease upon ICU admission; (4) length of ICU stay less than 24 h; (5) estimated glomerular filtration rate (eGFR) < 15 mL/min/1.73m2. For individuals who have experienced multiple ICU and hospital admissions, we only considered data from their initial ICU stay and first admission to the hospital. Figure 1 shows a flow chart of population selection.

Fig. 1
figure 1

Flow chart of population selection

Full size image

Definition of deteriorating renal function and serum osmolality

The primary outcome for this analysis was deteriorating renal function of AMI patients. Secondary outcomes included the new-onset of AKI and progress of AKI. The diagnosis of AKI was based on the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines: an increase in creatinine level by 0.3 mg/dL within 48 h, or an increase in creatinine serum creatinine, which is known or presumed to have occurred within the prior 7 days, or a urine volume of < 0.5 mL/kg/h for 6 h [13]. The baseline creatinine was defined as the lowest level of creatinine measured during the 7-day period prior to each AKI assessment, or as the first creatinine value after ICU admission for patients without a pre-admission creatinine measurement [14]. Deteriorating renal function was defined as new-onset or progress of AKI between 24 h after ICU admission and the follow-up endpoint [15]. New-onset of AKI was defined as the identification of AKI between 24 h and follow-up endpoint of ICU stay in those AMI patients who did not have AKI recognized within the first 24 h. The progress of AKI referred to an increase in AKI stage during the subsequent follow-up, including patients who already had AKI at admission and those who experienced further worsening during their ICU stay. Serum osmolality (mmol/L) was determined using the formula: (Na + K) × 2 + (glucose/18) + (urea/2.8) [16]. The Na, K, glucose and urea levels were collected within the first 24 h after ICU admission. For this analysis, the optimal serum osmolality cutoff point of 293.2725 mmol/L was determined using the maximally selected rank statistics method [17], and serum osmolality was categorized into two groups: low serum osmolality (< 293.2725 mmol/L) and high serum osmolality (≥ 293.2725 mmol/L).

Data collection

We collected patient-related information, including age, gender, ethnicity, insurance, marital status, AMI type, diabetes, hypertension, cardiogenic shock, urine output within 24 h (mL), weight (kg), simplified acute physiology score-II (SAPS-II), heart rate (bpm), respiratory rate (bpm), systolic blood pressure (SBP, mmHg), diastolic blood pressure (DBP, mmHg), temperature (℃), pulse oxygen saturation (SPO2), white blood cell count (WBC, K/uL), platelet count (K/uL), hemoglobin (g/dL), red cell distribution width (RDW, %), hematocrit (%), creatinine (mg/dL), international normalized ratio (INR), prothrombin time (PT), calcium (mmol/L), chloride (mEq/L), bicarbonate (mEq/L), coronary artery bypass grafting (CABG), percutaneous coronary intervention (PCI), contrast agent, thrombolysis, antiplatelet, anticoagulation, vasopressor, ventilation, diuretic, statin, acetylcysteine, length of ICU stay (days), eGFR (mL/min/1.73m2).

Statistical analysis

Continuous variables were presented as mean ± standard deviation (SD) or median and interquartile range [M (Q₁, Q₃)] based on their distribution. To assess differences between groups, a t-test/t'-test was employed for normally distributed data, while a Wilcoxon rank sum test was utilized for non-normally distributed data. Categorical variables were expressed as numbers and percentages, and Chi-square or Fisher's exact probability test were used for comparison between groups. The random forest interpolation method was employed to fill in the missing values for variables with a missing ratio of less than 15%. Subsequently, the interpolated data was utilized for conducting difference analysis. Univariate logistic regression was adopted to screen for possible confounding factors, and bidirectional stepwise regression was further used to identify confounding factors. Univariate and multivariate logistic regression models were used to explore the associations between serum osmolality and the development of deteriorating renal function, the new-onset of AKI and progress of AKI among AMI patients. Odds ratio (OR) with 95% confidence interval (CI) was calculated. Subgroup analysis was conducted based on age (< 65, ≥ 65), AMI type, cardiogenic shock, and eGFR (< 60 mL/min/1.73m2, ≥ 60 mL/min/1.73m2). P < 0.05 was considered statistically significant. All statistical analyses in the present study were performed using Python 3.9.12 and R version 4.3.1 (2023–06-16 ucrt).

Results

Characteristics of patients

A total of 3,885 eligible AMI patients were enrolled for this study. Table 1 briefly summarized the characteristics of AMI patients. All patients’ mean age was 69.66 years old. There were 2,464 (63.42%) male patients, and 1,421 (36.58%) female patients. 1,393 AMI patients developed deteriorating renal function. In addition, 3,024 AMI patients had low serum osmolality (< 293.2725 mmol/L) and 861 had high serum osmolality (≥ 293.2725 mmol/L). We compared the characteristics between low serum osmolality group and high serum osmolality group. There are some significant differences of characteristics between the low serum osmolality group and the high serum osmolality group, such as age, gender, ethnicity, insurance, AMI type, cardiogenic shock, urine output within 24 h, weight, SAPS-II, heart rate, respiratory rate, SBP, DBP, temperature, SPO2, platelet, RDW, creatinine, calcium, chloride, thrombolysis, antiplatelet, anticoagulation, vasopressor, statin, length of ICU stay, osmolality, and eGFR. The proportion of deteriorating renal function was higher in the high serum osmolality group compared to the low serum osmolality group (42.16% vs 34.06%).

Table 1 The characteristics of AMI patients between low serum osmolality group and high serum osmolality group
Full size table

Relationship between serum osmolality and outcomes

As shown in Supplemental Table 1, cardiogenic shock, urine output within 24 h, weight, SAPSII, SPO2, RDW, INR, BUN, Na, calcium, chloride, CABG, anticoagulation, vasopressor, ventilation, and statin were confounding factors related to deteriorating renal function. In the univariate logistic model (Model 1), high serum osmolality was a risk factor for the development of deteriorating renal function (Table 2; OR = 1.41, 95% CI: 1.21–1.65, P < 0.001). After adjusting all confounding factors related to deteriorating renal function, high serum osmolality was still associated with increased risk of deteriorating renal function for AMI patients (Table 2; OR = 1.47, 95% CI: 1.22–1.78, P < 0.001). When considering serum osmolality as continuous variable, a positive relationship between serum osmolality and deteriorating renal function was observed in the fully adjusted model. Restricted cubic-spline analysis indicated that there may not exist a nonlinear relationship between serum osmolality and deteriorating renal function (Supplemental Fig. 1).

Table 2 Relationship between serum osmolality and outcomes
Full size table

Similarly, AMI type, diabetes, cardiogenic shock, SAPSII, hematocrit, RDW, PT, CABG, vasopressor, ventilation, diuretic, and statin were found to be confounding factors related to new-onset of AKI (Supplemental Table 2). After adjusting all confounding factors related to new-onset of AKI, high serum osmolality was linked with an increased risk of new-onset of AKI for AMI patients (Table 2; Model 2: OR = 1.31, 95% CI: 1.01–1.69, P = 0.040). Additionally, we also observed that there was positive correlation between high serum osmolality and progress of AKI risk among AMI patients in the fully adjusted model (Table 2; OR = 1.26, 95% CI: 1.01–1.59, P = 0.043). Supplemental Table 3 presents the possible confounding factors related to progress of AKI. When considering serum osmolality as continuous variable, there was no significant difference observed between serum osmolality and new-onset/ progress of AKI in the fully adjusted model.

Subgroup analysis

Figure 2 indicates the stability of the correlation between serum osmolality and deteriorating renal function in patients with AMI across subgroups. When the stratified analysis was performed for age, AMI type, cardiogenic shock, and eGFR, the forest plot (Fig. 2) showed that high serum osmolality was risk factor for the risk of deteriorating renal function among patients aged 65 years or older, without cardiogenic shock, and with an eGFR ≥ 60 mL/min/1.73m2.

Fig. 2
figure 2

Forest plot of stratified analysis based on age, AMI type, cardiogenic shock, and eGFR

Full size image

Discussion

From this retrospective cohort study based on MIMIC-IV, we found the association between serum osmolality and deteriorating renal function for AMI patients. AMI patients with higher serum osmolarity were more likely to develop deteriorating renal function. In addition, high serum osmolality was also positively associated with both new-onset of AKI and progress of AKI risk among AMI patients compared with low serum osmolality.

AKI is a syndrome characterized by the rapid loss of excretory function in the kidneys, and it has been found to be a serious complication in critically ill patients [18]. Cardiac disease and renal injury may be intricately connected through a complex web of organ interactions, resulting in the phenomenon known as “cardio-renal syndrome”, which encompasses a range of acute or chronic heart and kidney disorders characterized by mutual deterioration [19, 20]. AKI is common in patients with AMI undergoing percutaneous coronary intervention (PCI) [21]. Meraz-Muñoz et al. suggested that AKI was associated with less frequent dispensing of the combination of angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker, β-blocker, and statin within 1 year of hospital discharge among patients with a history of AMI [22]. It is crucial to identify AMI patients at high risk of AKI in the ICU to improve their prognosis. Serum osmolality is a typical indicator of fluid balance and renal function, and is commonly determined based on the concentrations of Na, K, glucose, and urea [23]. Previous several studies have demonstrated that serum osmolality holds significant prognostic value in various diseases [7,8,9,10]. Few studies have elucidated about the prognostic meaning of osmolality in deteriorating renal function for AMI patients. In this study, we used the maximally selected rank statistics method to identify the optimal serum osmolality cutoff point, and low serum osmolality < 293.2725 mmol/L was defined as low level, and serum osmolality ≥ 293.2725 mmol/L as high level. After adjusting all confounding factors, high serum osmolality was independently related to an increased risk of developing deteriorating renal function taking low serum osmolality as reference. The underlying mechanisms about the relationship between osmolality and deteriorating renal function are not clear. Kidney, being a vital organ involved in maintaining fluid and electrolyte balance, commonly exhibits water imbalances and alterations in serum electrolyte levels in cases of renal insufficiency [24]. Increased osmolality induces symptoms such as osmotic diuresis, thereby exacerbating dehydration and electrolyte imbalances, which in turn may contribute to the development of renal insufficiency [25]. A retrospective cohort study conducted by El-Sharkawy et al., it was discovered that hospitalized older adults with hyperosmolar dehydration (serum osmolarity > 300 mOsm/kg) had a four-fold increased risk of developing AKI after admission compared with the euhydrated group [26]. Hyperosmolar dehydration may serve as an early predictor for the development of AKI. Serum osmolality (mmol/L) was determined using the formula: (Na + K) × 2 + (glucose/18) + (urea/2.8). Relevant studies also found the relationship of Na, K, glucose and urea level and renal function of patients [27,28,29,30,31,32]. Further investigation is needed to explore the more detailed mechanisms. about the relationship of serum osmolality and deteriorating renal function.

Additionally, our study found that in critically ill patients with AMI who aged 65 years or older, without cardiogenic shock, and with an eGFR ≥ 60 mL/min/1.73m2, high serum osmolality was still related to the risk of deteriorating renal function, which also indicated that we should pay more attention to the serum osmolality level of these patients.

Overall, this study used a large and publicly available critical-care database to first assess the relationship between serum osmolality and the risk of deteriorating renal function in patients with AMI. Clinicians should pay heightened attention to the AMI patients with serum osmolality ≥ 293.2725 mmol/L, as they are at a higher risk of experiencing deteriorating renal function. However, there were some limitations for this analysis. Firstly, serum osmolality in this study was calculated by formula rather than directly measured; however, serum osmolality level obtained through the utilized calculation equation has been proven to be highly accurate and easily obtainable, thereby facilitating its application in clinical practice. Secondly, the study participants consisted of patients in the ICU, and further validation is required to determine the applicability of serum osmolality in AMI patients admitted to general wards. Thirdly, MIMIC-IV did not collect information regarding the duration of interventional procedures, contrast volume and the type of contrast administered, which may potentially impact our findings [33, 34]. Additionally, brain natriuretic peptide (BNP) was also considered as an important indicator for critical cardiac illness [35]. Due to the significant missing data regarding BNP in the MIMIC-IV database, we did not include it in our study. Fourthly, the median duration of ICU stay for the patients included in this study was less than 3 days, thus potentially underestimating the occurrence rate of renal function deterioration by not considering reversals and relapses [36, 37]. Lastly, the present study was conducted at a single center, which may introduce potential bias. Therefore, it is imperative to validate the findings through multicenter trials.

Conclusion

Higher serum osmolality was independently associated with deteriorating renal function, new-onset of AKI and progress of AKI risk among AMI patients. Large prospective studies are needed to further confirm our results.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available in the MIMIC-IV database, https://mimic.mit.edu/docs/iv/.

Abbreviations

AMI:

Acute myocardial infarction

ICUs:

Intensive care units

AKI:

Acute kidney injury

ICU:

Intensive care unit

MIMIC-IV:

Medical Information Mart for Intensive Care IV

ICD-9:

International Classification of Diseases, Ninth Revision

eGFR:

Estimated glomerular filtration rate

SBP:

Systolic blood pressure

DBP:

Diastolic blood pressure

WBC:

White blood cell count

RDW:

Red cell distribution width

INR:

International normalized ratio

PT:

Prothrombin time

CABG:

Coronary artery bypass grafting

PCI:

Percutaneous coronary intervention

SD:

Standard deviation

OR:

Odds ratio

CI:

Confidence interval

References

  1. Saito Y, Oyama K, Tsujita K, Yasuda S, Kobayashi Y. Treatment strategies of acute myocardial infarction: updates on revascularization, pharmacological therapy, and beyond. J Cardiol. 2023;81:168–78.

    Article  PubMed  Google Scholar 

  2. Jin G, Seong SW, Kim MJ, Ahn KT, Jin SA, Hahn JY, et al. Prevalence and prognostic implications of worsening renal function after acute myocardial infarction. Am J Cardiol. 2023;200:40–6.

    Article  PubMed  Google Scholar 

  3. Sun L, Zhu W, Ji Y, Zou A, Mao L, Chi B, et al. Association of plasma free triiodothyronine levels with contrast-induced acute kidney injury and short-term survival in patients with acute myocardial infarction. Endocr Connect. 2022;11:e220120.

  4. Pei Y, Chen W, Mao X, Zhu J. Serum Cystatin C, Klotho, and neutrophil gelatinase-associated lipocalin in the risk prediction of acute kidney injury after acute myocardial infarction. Cardiorenal Med. 2020;10:374–81.

    Article  CAS  PubMed  Google Scholar 

  5. Büyükkaragöz B, Bakkaloğlu SA. Serum osmolality and hyperosmolar states. Pediatr Nephrol. 2023;38:1013–25.

    Article  PubMed  Google Scholar 

  6. Feehally J, Khosravi M. Effects of acute and chronic hypohydration on kidney health and function. Nutr Rev. 2015;73(Suppl 2):110–9.

    Article  PubMed  Google Scholar 

  7. Yang J, Cheng Y, Wang R, Wang B. Association between serum osmolality and acute kidney injury in critically Ill patients: a retrospective cohort study. Front Med (Lausanne). 2021;8:745803.

    Article  PubMed  Google Scholar 

  8. Kuwabara M, Hisatome I, Roncal-Jimenez CA, Niwa K, Andres-Hernando A, Jensen T, et al. Increased Serum Sodium and Serum Osmolarity Are Independent Risk Factors for Developing Chronic Kidney Disease; 5 Year Cohort Study. PLoS ONE. 2017;12:e0169137.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Rohla M, Freynhofer MK, Tentzeris I, Farhan S, Wojta J, Huber K, et al. Plasma osmolality predicts clinical outcome in patients with acute coronary syndrome undergoing percutaneous coronary intervention. Eur Heart J Acute Cardiovasc Care. 2014;3:84–92.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Holtfreter B, Bandt C, Kuhn SO, Grunwald U, Lehmann C, Schütt C, et al. Serum osmolality and outcome in intensive care unit patients. Acta Anaesthesiol Scand. 2006;50:970–7.

    Article  CAS  PubMed  Google Scholar 

  11. He Y, Xu J, Shang X, Fang X, Gao C, Sun D, et al. Clinical characteristics and risk factors associated with ICU-acquired infections in sepsis: A retrospective cohort study. Front Cell Infect Microbiol. 2022;12:962470.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Lu Z, Tao G, Sun X, Zhang Y, Jiang M, Liu Y, et al. Association of blood glucose level and glycemic variability with mortality in sepsis patients during ICU hospitalization. Front Public Health. 2022;10:857368.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Kellum JA, Lameire N, KDIGO AKI Guideline Work Group. Diagnosis, evaluation, and management of acute kidney injury: a KDIGO summary (Part 1). Crit Care. 2013;17:204.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Liang M, Ren X, Huang D, Ruan Z, Chen X, Qiu Z. The association between lactate dehydrogenase to serum albumin ratio and the 28-day mortality in patients with sepsis-associated acute kidney injury in intensive care: a retrospective cohort study. Ren Fail. 2023;45:2212080.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Peng Y, Wu B, Xing C, Mao H. Increased mean perfusion pressure variability is associated with subsequent deterioration of renal function in critically ill patients with central venous pressure monitoring: a retrospective observational study. Ren Fail. 2022;44:1976–84.

    Article  PubMed  Google Scholar 

  16. Heavens KR, Kenefick RW, Caruso EM, Spitz MG, Cheuvront SN. Validation of equations used to predict plasma osmolality in a healthy adult cohort. Am J Clin Nutr. 2014;100:1252–6.

    Article  CAS  PubMed  Google Scholar 

  17. Zhang W, Tang J, Tang H, et al. Different computed tomography parameters for defining myosteatosis in patients with advanced non-small cell lung cancer. Clin Nutr. 2023;42:2414–21.

    Article  PubMed  Google Scholar 

  18. Bellomo R, Kellum JA, Ronco C. Acute kidney injury. Lancet. 2012;380:756–66.

    Article  PubMed  Google Scholar 

  19. Lee TH, Fan PC, Chen JJ, et al. A validation study comparing existing prediction models of acute kidney injury in patients with acute heart failure. Sci Rep. 2021;11:11213.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Chen JJ, Lee TH, Kuo G, et al. Acute kidney disease after acute decompensated heart failure. Kidney Int Rep. 2022;7:526–36.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Rigattieri S, Cristiano E, Tempestini F, et al. Acute kidney injury in patients with acute myocardial infarction undergoing percutaneous coronary intervention: the role of vascular access site. J Clin Med. 2024;13:2367.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Meraz-Muñoz AY, Jeyakumar N, Luo B, et al. Cardiovascular drug use after acute kidney injury among hospitalized patients with a history of myocardial infarction. Kidney Int Rep. 2022;8:294–304.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Ebonwu EO, Nagel SE, Repsold L, Pillay TS. Critical evaluation of equations for serum osmolality: Proposals for effective clinical utility. Clin Chim Acta. 2020;510:79–87.

    Article  CAS  PubMed  Google Scholar 

  24. Yan LJ. Redox Imbalance and Mitochondrial Abnormalities in Kidney Disease. Biomolecules. 2022;12:476.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Hu T, Li C, Wang T, Liu H, Geng J, Gong A. Serum osmolality was non-linearly associated with the risk of all-cause and cardiovascular mortality in patients with diabetes. BMJ Open Diabetes Res Care. 2023;11:e003826.

    Article  PubMed  PubMed Central  Google Scholar 

  26. El-Sharkawy AM, Devonald MAJ, Humes DJ, Sahota O, Lobo DN. Hyperosmolar dehydration: A predictor of kidney injury and outcome in hospitalised older adults. Clin Nutr. 2020;39:2593–9.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Lombardi G, Ferraro PM, Naticchia A, Gambaro G. Serum sodium variability and acute kidney injury: a retrospective observational cohort study on a hospitalized population. Intern Emerg Med. 2021;16:617–24.

    Article  PubMed  Google Scholar 

  28. Clase CM, Carrero JJ, Ellison DH, Grams ME, Hemmelgarn BR, Jardine MJ, et al. Potassium homeostasis and management of dyskalemia in kidney diseases: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference. Kidney Int. 2020;97:42–61.

    Article  CAS  PubMed  Google Scholar 

  29. Elfassy T, Zhang L, Raij L, Bibbins-Domingo K, Lewis CE, Allen NB, et al. Results of the CARDIA study suggest that higher dietary potassium may be kidney protective. Kidney Int. 2020;98:187–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Moriyama N, Ishihara M, Noguchi T, Nakanishi M, Arakawa T, Asaumi Y, et al. Admission hyperglycemia is an independent predictor of acute kidney injury in patients with acute myocardial infarction. Circ J. 2014;78:1475–80.

    Article  CAS  PubMed  Google Scholar 

  31. Pundir CS, Jakhar S, Narwal V. Determination of urea with special emphasis on biosensors: A review. Biosens Bioelectron. 2019;123:36–50.

    Article  CAS  PubMed  Google Scholar 

  32. Seki M, Nakayama M, Sakoh T, Yoshitomi R, Fukui A, Katafuchi E, et al. Blood urea nitrogen is independently associated with renal outcomes in Japanese patients with stage 3–5 chronic kidney disease: a prospective observational study. BMC Nephrol. 2019;20:115.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Sudarski D, Naami R, Shehadeh F, Elias A, Kerner A, Aronson D. Risk of worsening renal function following repeated exposures to contrast media during percutaneous coronary interventions. J Am Heart Assoc. 2021;10:e021473.

    Article  PubMed  Google Scholar 

  34. Gray DE, Eisenack M, Gawenda M, Torsello G, Majd P, Brunkwall J, Osada N, Donas KP. Repeated contrast medium application after endovascular aneurysm repair and not the type of endograft fixation seems to have deleterious effect on the renal function. J Vasc Surg. 2017;65:46–51.

    Article  PubMed  Google Scholar 

  35. Fiorentino M, Tohme FA, Murugan R, Kellum JA. Plasma biomarkers in predicting renal recovery from acute kidney injury in critically Ill patients. Blood Purif. 2019;48:253–61.

    Article  CAS  PubMed  Google Scholar 

  36. Peerapornratana S, Fiorentino M, Priyanka P, Murugan R, Kellum JA. Recovery after AKI: Effects on outcomes over 15 years. J Crit Care. 2023;76:154280.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Kellum JA, Sileanu FE, Bihorac A, Hoste EA, Chawla LS. Recovery after acute kidney injury. Am J Respir Crit Care Med. 2017;195:784–91.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

Not applicable.

Funding

 This study was supported by A project to improve the social first aid skills of teenagers in Sichuan and Tibet (2024JDKP0030).

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Author notes

  1. Xiaojia Luo and Yong Tang contributed to the work equally and should be considered as co-first authors.

Authors and Affiliations

  1. Department of Cardiology, Chengdu Second People’s Hospital, No.10 Qingyunnan Street, Jinjiang District, Chengdu, Sichuan Province, 610017, China

    Xiaojia Luo, JianXiong Liu & Zhengbing Lv

  2. Department of Emergency Medicine, Chengdu Second People’s Hospital, Chengdu, Sichuan Province, 610017, China

    Yong Tang, Yanzhang Shu & Baoli Xu

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  1. Xiaojia Luo
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Contributions

XL, JL, and ZL designed the study. XL wrote the manuscript. YT, YS, BX, and JL collected, analyzed, and interpreted the data. ZL critically reviewed, edited, and approved the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to JianXiong Liu or Zhengbing Lv.

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Ethics approval and consent to participate

The requirement of ethical approval for this was waived by the Institutional Review Board of Chengdu Second People's Hospital, because the data was accessed from MIMIC-IV (a publicly available database). The need for written informed consent was waived by the Institutional Review Board of Chengdu Second People's Hospital due to retrospective nature of the study. All methods were performed in accordance with the relevant guidelines and regulations.

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The authors declare no competing interests.

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Luo, X., Tang, Y., Shu, Y. et al. Association between serum osmolality and deteriorating renal function in patients with acute myocardial infarction: analysis of the MIMIC- IV database. BMC Cardiovasc Disord 24, 490 (2024). https://doi.org/10.1186/s12872-024-04159-5

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  • DOI: https://doi.org/10.1186/s12872-024-04159-5

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BMC Cardiovascular Disorders

ISSN: 1471-2261

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