
==== Front
BMC Cardiovasc Disord
BMC Cardiovasc Disord
BMC Cardiovascular Disorders
1471-2261
BioMed Central London

4159
10.1186/s12872-024-04159-5
Research
Association between serum osmolality and deteriorating renal function in patients with acute myocardial infarction: analysis of the MIMIC- IV database
Luo Xiaojia 1
Tang Yong 2
Shu Yanzhang 2
Xu Baoli 2
Liu JianXiong 18908178061@163.com

1
Lv Zhengbing lvzhbbb@outlook.com

1
1 https://ror.org/02q28q956 grid.440164.3 0000 0004 1757 8829 Department of Cardiology, Chengdu Second People’s Hospital, No.10 Qingyunnan Street, Jinjiang District, Chengdu, Sichuan Province 610017 China
2 https://ror.org/02q28q956 grid.440164.3 0000 0004 1757 8829 Department of Emergency Medicine, Chengdu Second People’s Hospital, Chengdu, Sichuan Province 610017 China
13 9 2024
13 9 2024
2024
24 4902 1 2024
2 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-024-04159-5.

Keywords

Acute myocardial infarction
Serum osmolality
Deteriorating renal function
Acute kidney injury
Association
issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
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pmcBackground

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 [2–4]. 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 Flow chart of population selection

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

Variables	Total (n = 3885)	Low serum osmolality group (n = 3024)	High serum osmolality group (n = 861)	P	
Age, Mean (± SD)	69.66 (± 12.96)	68.71 (± 12.71)	73.02 (± 13.27)	 < 0.001	
Gender, n (%)	0.002	
 Female	1421 (36.58)	1066 (35.25)	355 (41.23)		
 Male	2464 (63.42)	1958 (64.75)	506 (58.77)		
Ethnicity, n (%)	 < 0.001	
 Black	254 (6.54)	175 (5.79)	79 (9.18)		
 Others	426 (10.97)	349 (11.54)	77 (8.94)		
 Unknown	645 (16.6)	521 (17.23)	124 (14.4)		
 White	2560 (65.89)	1979 (65.44)	581 (67.48)		
Insurance, n (%)	 < 0.001	
 Medicaid	157 (4.04)	124 (4.1)	33 (3.83)		
 Medicare	2061 (53.05)	1547 (51.16)	514 (59.7)		
 Others	1667 (42.91)	1353 (44.74)	314 (36.47)		
Marital status, n (%)	0.095	
 Married	1908 (49.11)	1513 (50.03)	395 (45.88)		
 Non-married	1545 (39.77)	1183 (39.12)	362 (42.04)		
 Unknown	432 (11.12)	328 (10.85)	104 (12.08)		
AMI type, n (%)	 < 0.001	
 NSTEMI	782 (20.13)	659 (21.79)	123 (14.29)		
 STEMI	756 (19.46)	627 (20.73)	129 (14.98)		
 Unknown	2347 (60.41)	1738 (57.47)	609 (70.73)		
Diabetes, yes, n (%)	1609 (41.42)	1259 (41.63)	350 (40.65)	0.633	
Hypertension, yes, n (%)	2556 (65.79)	2003 (66.24)	553 (64.23)	0.291	
Cardiogenic shock, yes, n (%)	538 (13.85)	399 (13.19)	139 (16.14)	0.031	
Urine output within 24 h, mL, Mean (± SD)	1862.70 (± 1171.00)	1899.19 (± 1158.15)	1734.55 (± 1207.03)	 < 0.001	
Weight, kg, Mean (± SD)	81.59 (± 18.74)	82.47 (± 18.78)	78.53 (± 18.27)	 < 0.001	
SAPSII, score, Mean (± SD)	37.93 (± 13.40)	36.79 (± 13.05)	41.91 (± 13.85)	 < 0.001	
Heart rate, bpm, Mean (± SD)	85.92 (± 17.42)	85.19 (± 16.78)	88.51 (± 19.29)	 < 0.001	
SBP, mmHg, Mean (± SD)	121.14 (± 22.85)	120.37 (± 22.56)	123.86 (± 23.64)	 < 0.001	
DBP, mmHg, Mean (± SD)	66.19 (± 16.83)	65.59 (± 16.53)	68.28 (± 17.67)	 < 0.001	
Respiratory rate, bpm, Mean (± SD)	18.65 (± 5.42)	18.13 (± 5.26)	20.49 (± 5.60)	 < 0.001	
Temperature, ℃, Mean (± SD)	36.59 (± 0.56)	36.57 (± 0.55)	36.67 (± 0.58)	 < 0.001	
SPO2, %, Mean (± SD)	97.13 (± 3.25)	97.32 (± 3.17)	96.46 (± 3.41)	 < 0.001	
WBC, K/uL, M (Q₁, Q₃)	11.8 (8.8, 15.8)	11.9 (8.9, 15.8)	11.7 (8.4, 15.8)	0.175	
Platelet, K/uL, Mean (± SD)	206.54 (± 93.72)	204.81 (± 92.71)	212.61 (± 97.00)	0.031	
Hemoglobin, g/dL, Mean (± SD)	10.84 (± 2.40)	10.87 (± 2.43)	10.74 (± 2.30)	0.150	
RDW, %, Mean (± SD)	14.57 (± 1.97)	14.38 (± 1.87)	15.23 (± 2.18)	 < 0.001	
Hematocrit, %, Mean (± SD)	32.79 (± 7.04)	32.71 (± 7.09)	33.06 (± 6.86)	0.190	
Creatinine, mg/dL, Mean (± SD)	1.29 (± 0.74)	1.18 (± 0.65)	1.68 (± 0.90)	 < 0.001	
BUN, Mean (± SD)	27.57 (± 19.42)	23.77 (± 15.26)	40.92 (± 25.62)	 < 0.001	
Na, Mean (± SD)	137.13 (± 4.82)	135.51 (± 3.74)	142.80 (± 3.78)	 < 0.001	
INR, ratio, M (Q₁, Q₃)	1.3 (1.1, 1.5)	1.3 (1.1, 1.5)	1.26 (1.1, 1.5)	0.165	
PT, seconds, M (Q₁, Q₃)	14.32 (12.8, 16.3)	14.37 (12.8, 16.3)	14.21 (12.5, 16.3)	0.141	
Calcium, mmol/L, Mean (± SD)	7.37 (± 2.50)	7.31 (± 2.49)	7.57 (± 2.53)	0.008	
Chloride, mEq/L, M (Q₁, Q₃)	104 (101, 107)	103 (100, 106)	107 (104, 110)	 < 0.001	
Bicarbonate, mEq/L, Mean (± SD)	22.53 (± 4.10)	22.60 (± 3.81)	22.31 (± 4.98)	0.120	
CABG, yes, n (%)	65 (1.67)	56 (1.85)	9 (1.05)	0.140	
PCI, yes, n (%)	47 (1.21)	36 (1.19)	11 (1.28)	0.976	
Contrast agent, yes, n (%)	6 (0.15)	4 (0.13)	2 (0.23)	0.620	
Thrombolysis, yes, n (%)	31 (0.8)	19 (0.63)	12 (1.39)	0.044	
Antiplatelet, yes, n (%)	3308 (85.15)	2663 (88.06)	645 (74.91)	 < 0.001	
Anticoagulation, yes, n (%)	2005 (51.61)	1485 (49.11)	520 (60.39)	 < 0.001	
Vasopressor, yes, n (%)	1804 (46.44)	1480 (48.94)	324 (37.63)	 < 0.001	
Ventilation, yes, n (%)	3424 (88.13)	2665 (88.13)	759 (88.15)	1.000	
Diuretic, yes, n (%)	1435 (36.94)	1136 (37.57)	299 (34.73)	0.138	
Statin, yes, n (%)	3045 (78.38)	2451 (81.05)	594 (68.99)	 < 0.001	
Acetylcysteine, yes, n (%)	8 (0.21)	4 (0.13)	4 (0.46)	0.078	
Length of ICU stay, days, M (Q₁, Q₃)	2.72 (1.68, 4.7)	2.48 (1.58, 4.35)	3.08 (2.05, 5.53)	 < 0.001	
Osmolality, mmol/L, Mean (± SD)	286.97 (± 10.03)	283.26 (± 6.99)	300.00 (± 8.00)	 < 0.001	
EGFR, mL/min/1.73m2, M (Q₁, Q₃)	69.02 (± 27.53)	73.28 (± 26.36)	54.06 (± 26.32)	 < 0.001	
Deterioration, yes, n (%)	1393 (35.86)	1030 (34.06)	363 (42.16)	 < 0.001	
Survival, n (%)	3369 (86.72)	2699 (89.25)	670 (77.82)	 < 0.001	
AMI acute myocardial infarction, NSTEMI non-ST-segment elevation myocardial infarction, STEMI ST-segment elevation myocardial infarction, SAPS-II simplified acute physiology score-II, SBP systolic blood pressure, DBP diastolic blood pressure, SPO2 pulse oxygen saturation, 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, ICU intensive care units, eGFR estimated glomerular filtration rate

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

Variables	Outcomes	Outcome/Total	Model 1	Model 2	
OR (95% CI)	P	OR (95% CI)	P	
Serum osmolality	Deteriorating renal function (n = 3885)	1393/3885	1.01 (1.00–1.01)	0.045	1.01 (1.00–1.02)	0.040	
Serum osmolality						
Low level	993/2913	Ref		Ref		
High level	400/972	1.41 (1.21–1.65)	 < 0.001	1.47 (1.22–1.78)	 < 0.001	
Serum osmolality	New-onset of AKI (n = 1747)	766/1747	1.00 (0.99–1.01)	0.459	1.00 (0.99–1.01)	0.841	
Serum osmolality						
Low level	563/1334	Ref		Ref		
High level	203/413	1.46 (1.16–1.84)	0.001	1.31 (1.01–1.69)	0.040	
Serum osmolality	Progress of AKI (n = 2138)	627/2138	1.01 (1.00–1.02)	0.021	1.00 (0.99–1.01)	0.567	
Serum osmolality						
Low level	430/1579	Ref		Ref		
High level	197/559	1.45 (1.17–1.80)	0.001	1.26 (1.01–1.59)	0.043	
AKI acute kidney injury, OR odds ratio, CI confidence interval, Ref reference

Model 1: univariate logistic analysis

Model 2: adjusted cardiogenic shock, urine output within 24 h, weight, simplified acute physiology score-II (SAPS-II), pulse oxygen saturation (SPO2), red cell distribution width (RDW), INR, BUN, Na, calcium, chloride, coronary artery bypass grafting (CABG), anticoagulation, vasopressor, ventilation, statin (for deteriorating renal function); adjusted AMI type, diabetes, cardiogenic shock, SAPS-II, RDW, hematocrit, prothrombin time, CABG, vasopressor, ventilation, diuretic, statin (for new-onset of AKI); adjusted gender, cardiogenic shock, urine output within 24 h, weight, SAPSII, SPO2, platelet, RDW, hematocrit, diuretic (for progress of AKI)

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

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 [7–10]. 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 [27–32]. 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.

Supplementary Information

Supplementary Material 1.

Supplementary Material 2.

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

Acknowledgements

Not applicable.

Authors’ 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.

Funding

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

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/.

Declarations

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.

Cosent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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