Perioperative intravenous fluid for cardiothoracic surgery and acute kidney injury in Korea between 2007 and 2021

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Objective: To describe temporal changes in perioperative intravenous fluid use and to examine associations with acute kidney injury (AKI) and hemodialysis in patients undergoing cardiac or thoracic aorta surgery. Design: Retrospective nationwide cohort study. Setting: Korean National Health Insurance Service (NHIS) database. Patients: Adult patients undergoing cardiac or thoracic aorta surgery in Korea between 2007 and 2021. Interventions: None; perioperative intravenous fluid exposure was assessed using national insurance claims data. Main outcome measures: The primary outcomes were AKI and newly required hemodialysis. Secondary outcomes included in-hospital and 1-year mortality. Results: A total of 112,928 patients were analyzed. AKI occurred in 2.4%, and 1.1% required hemodialysis. From 2007 to 2021, the use of synthetic colloids decreased substantially, whereas acetate-buffered balanced crystalloid use increased to near-universal adoption. Albumin administration and red blood cell transfusion were independently associated with higher odds of AKI and hemodialysis after adjustment for covariates. Over time, the incidence of AKI increased, while the incidence of hemodialysis remained stable. Conclusion: Between 2007 and 2021, the incidence of perioperative AKI increased from 1.4% to 3.1%, whereas the incidence of hemodialysis remained stable at approximately 1%. During the same period, perioperative fluid management changed substantially, with decreased use of synthetic colloids and near-universal adoption of acetate-buffered balanced crystalloids. These findings represent population-level temporal trends and should be interpreted as descriptive rather than causal. acute kidney injury renal insufficiency thoracic surgery mortality fluid therapy colloids Figures Figure 1 Figure 2 Key points Perioperative intravenous fluid practices in cardiothoracic surgery changed substantially in Korea between 2007 and 2021. The use of synthetic colloids decreased, while acetate-buffered balanced crystalloids became nearly universal. The incidence of acute kidney injury increased over time, whereas rates of hemodialysis remained stable. Albumin administration and red blood cell transfusion were associated with higher risks of renal complications and mortality. Introduction Acute kidney injury (AKI) is a common complication following cardiac surgery with a reported incidence ranging from 7.7% to 40% in cardiac surgery and as high as 55% in patients undergoing aorta surgery [ 1 – 3 ]. Cardiopulmonary bypass, aorta cross clamping, and the use of transfusion and vasopressors, may increase the risk of AKI compared to non-cardiac surgery [ 4 ]. Accordingly, postoperative AKI in cardiac surgery patients is not only frequent but also clinically significant, as it has been consistently associated with increased mortality and prolonged hospitalization in critically ill populations [ 5 ]. Fluid therapy protocols have evolved with the adoption of early goal-directed therapy and updates to transfusion guidelines, including a shift toward restrictive transfusion thresholds and less invasive hemodynamic monitoring [ 6 , 7 ]. However, there is limited research on how fluid use has actually changed in clinical practice and its impact on subsequent morbidity and mortality. Therefore, we investigated trends in fluid use and their association with postoperative AKI and mortality. We hypothesized that the incidence of AKI after cardiac or aortic surgery is associated with temporal changes in perioperative fluid administration. A large-scale time-series data analysis using the Korean National Health Insurance Service (NHIS) database was conducted, evaluating patients who underwent cardiac or thoracic aorta surgery. Materials and Methods Ethics approval Ethical approval for this study (IRB No. E-2204-039-1314; chairperson not applicable due to exemption) was provided by the Institutional Review Board of Seoul National University College of Medicine and Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea, on 15 April 2022. The board granted exemption due to the anonymized nature of the data and the minimal risk to patients. Study design and Patient population This retrospective cohort study used data from the Korean National Health Insurance Service (NHIS) database (Research management number: NHIS-2025-03-01-070). The cohort entry period was defined as 2006 to 2020 with an additional year for observation (to 2021). Potential sources of bias, including selection and information bias, were minimized by using a comprehensive nationwide claims database that covers nearly the entire Korean population. The study cohort included adult patients (18 years or older) who underwent cardiac surgery (coronary artery bypass grafting (CABG), valve surgery, or thoracic aorta surgery) between 2007 and 2020. In cases where more than one surgical procedure was performed within a one-year period, only the first episode was selected. Patients who underwent surgery in 2007 but had also received cardiothoracic surgery in 2006 were excluded to ensure that only the first surgery within a one-year period was counted. To rule out pre-existing renal dysfunction, patients who had received hemodialysis within 3 months prior to surgery were excluded. Patients without any fluid claim, including crystalloids, were excluded because these cases were considered to have missing information on the exposure variable. Subgroup analyses were conducted for patients aged 65 years or older. We included all eligible cases in the national database. Therefore, a prior sample size calculation was not required. The patient selection process is illustrated in [Figure 1 ]. Variables and outcomes definition Independent variables included the type of fluid administered, type of surgery performed, demographic data, comorbidities, and red blood cell (RBC) transfusion. Comorbidities were identified based on ICD-10 code and medication history recorded in the NHIS database. Hypertension, dyslipidemia, and diabetes mellitus (DM) were recognized only when there was an accompanying co-prescription history of relevant medications for at least one month within the 3 months prior to surgery. Other comorbidities included chronic kidney disease (CKD), cerebrovascular disease, chronic obstructive pulmonary disease (COPD), chronic hepatitis, and liver cirrhosis. Demographic factors such as age and sex were also included in the analysis. Fluids were categorized into crystalloids, colloids, and blood transfusion, and further subdivided into 0.9% saline, lactated Ringer’s solution, acetate-buffered balanced crystalloid (Brand name in Korea - Plasma solution A (PSA)), hydroxyethyl starch, pentastarch, dextran, albumin, and red blood cells (RBCs). Perioperative fluid exposure was defined as the total amount of fluid administered during the index hospitalization, including intraoperative and immediate postoperative periods. Surgical procedures were classified into on-pump CABG, off-pump CABG, valve surgery, thoracic aorta surgery, and combined surgery. If a patient underwent multiple surgical procedures during a single admission, the case was defined as combined surgery. Fluids and surgical procedures were identified from insurance claims. AKI was defined using the ICD-10 code N17.9 (acute renal failure), and hemodialysis was identified based on procedure codes from O7020 to O7081 in the insurance claims. The primary aim of this study was to evaluate changes in fluid use over time in patients undergoing cardiac or thoracic aorta surgery. Primary outcomes included the incidence of AKI and hemodialysis. Secondary outcomes were in-hospital mortality, 1-year mortality, hospital length of stay, and ICU length of stay. In-hospital mortality was defined as death before discharge, and 1-year mortality as death within one year after surgery. Patients were followed for up to 1 year postoperatively for 1-year mortality. ICU stay was measured based on insurance claim records. We also examined whether temporal changes in fluid use were associated with clinical outcomes such as mortality and length of stay. Statistical analysis and data analysis Continuous variables are presented as means with standard deviations (SD) or medians with interquartile ranges, while categorical variables are expressed as number and percentage. Differences in covariates across study years were assessed using analysis of variance for continuous variables and the chi-square test for categorical variables. Multivariable logistic regression analyses were performed to compute the odds ratios (OR) and 95% confidence intervals (CI) of factors associated with primary (AKI and hemodialysis) and secondary (in-hospital and one-year mortality) outcomes. Covariates associated with the outcomes in univariable analyses (P-value < 0.2) were included in the final multivariable model. Subgroup analyses for primary outcomes were conducted according to age (≥ 65 or < 65 years). All analyses were performed with SAS version 9.4 software (SAS Institute, Cary, NC, USA). Statistical significance was determined at a p value of < 0.05 (two-tailed). Results Patient data The initial cohort included 121,306 patients, all of whom underwent cardiac or thoracic aorta surgery between 2007 and 2021. After applying the exclusion criteria, 112,928 patients were included in the analysis. Baseline characteristics and annual data are presented in [Table 1 ]. The age distribution of patients changed over time. The proportion and number of patients under 50 declined, while those aged 50 and older increased, most notably among those aged 65 or older. Table 1 Patient characteristics by year COPD: chronic obstructive pulmonary disease CABG: coronary artery bypass graft Total 2007–2008 2009–2010 2011–2012 2013–2014 2015–2016 2017–2018 2019–2020 2021 Number of patients 112,928 13,657 13,584 13,258 13,249 15,647 16,918 17,389 9,226 Age (Mean ± SD) 62.79 ± 13.1 59.8 ± 12.9 60.8 ± 13.0 61.6 ± 13.3 62.1 ± 13.4 63.1 ± 13.1 64.1 ± 12.8 64.7 ± 12.6 65.0 ± 12.6 < 40 6,617 (5.9) 1,124 (8.2) 963 (7.1) 907 (6.8) 860 (6.5) 843 (5.4) 776 (4.6) 746 (4.3) 398 (4.3) 40–49 10,256 (9.1) 1,609 (11.8) 1,508 (11.1) 1,357 (10.2) 1,261 (9.5) 1,394 (8.9) 1,375 (8.1) 1,180 (6.8) 572 (6.2) 50–64 38,872 (34.4) 5,096 (37.3) 4,861 (35.8) 4,622 (34.9) 4,576 (34.5) 5,398 (34.5) 5,589 (33.0) 5,794 (33.3) 2,936 (31.8) ≥ 65 57,183 (50.6) 5,828 (42.7) 6,252 (46.0) 6,372 (48.1) 6,552 (49.5) 8,012 (51.2) 9,178 (54.2) 9,669 (55.6) 5,320 (57.7) Sex Male 69,328 (61.4) 8,216 (60.2) 8,091 (59.6) 7,968 (60.1) 8,123 (61.3) 9,577 (61.2) 10,505 (62.1) 10,985 (63.2) 5,863 (63.5) Female 43,600 (38.6) 5,441 (39.8) 5,493 (40.4) 5,290 (39.9) 5,126 (38.7) 6,070 (38.8) 6,413 (37.9) 6,404 (36.8) 3,363 (36.5) Comorbidities Hypertension 62,132 (55.0) 5,032 (36.8) 7,723 (56.9) 7,545 (56.9) 7,525 (56.8) 8,927 (57.1) 9,773 (57.8) 10,162 (58.4) 5,445 (59.0) Dyslipidemia 40,417 (35.8) 2,222 (16.3) 3,687 (27.1) 4,101 (30.9) 4,470 (33.7) 6,118(39.1) 7,108 (42.0) 8,208 (47.2) 4,503 (48.8) Diabetes mellitus 25,814 (22.9) 1,926 (14.1) 2,847 (21.0) 2,924 (22.1) 3,054 (23.1) 3,664 (23.4) 4,180 (24.7) 4,634 (26.6) 2,585 (28.0) Chronic kidney disease 4,680 (4.1) 211 (1.5) 341 (2.5) 432 (3.3) 513 (3.9) 691 (4.4) 884 (5.2) 1,000 (5.8) 608 (6.6) Cerebrovascular disease 19,007 (16.8) 1,280 (9.4) 2,292 (16.9) 2,235 (16.9) 2,228 (16.8) 2,690 (17.2) 3,165 (18.7) 3,323 (19.1) 1,794 (19.4) COPD 7,937 (7.0) 586 (4.3) 1,106 (8.1) 1,067 (8.0) 956 (7.2) 1,139 (7.3) 1,212 (7.2) 1,233 (7.1) 638 (6.9) Chronic hepatitis 6,873 (6.1) 506 (3.7) 875 (6.4) 818 (6.2) 752 (5.7) 817 (5.2) 1,053 (6.2) 1,347 (7.7) 705 (7.6) Liver cirrhosis 1,588 (1.4) 87 (0.6) 151 (1.1) 134 (1.0) 166 (1.3) 234 (1.5) 320 (1.9) 314 (1.8) 182 (2.0) Type of surgery Off-pump CABG 26,169 (23.2) 3,647 (26.7) 3,262 (24.0) 3,145 (23.7) 3,096 (23.4) 3,667 (23.4) 3,782 (22.4) 3,746 (21.5) 1,824 (19.8) On-pump CABG 15,733 (13.9) 2,609 (19.1) 2,386 (17.6) 2,091 (15.8) 1,795 (13.5) 2,113 (13.5) 2,019 (11.9) 1,759 (10.1) 961 (10.4) Valve surgery 30,704 (27.2) 3,348 (24.5) 3,693 (27.2) 3,603 (27.2) 3,811 (28.8) 4,354 (27.8) 4,846 (28.6) 4,638 (26.7) 2,411 (26.1) Thoracic aorta surgery 5,583 (4.9) 594 (4.3) 642 (4.7) 655 (4.9) 680 (5.1) 628 (4.0) 660 (3.9) 862 (5.0) 862 (9.3) Combined surgery 34,739 (30.8) 3,459 (25.3) 3,601 (26.5) 3,764 (28.4) 3,867 (29.2) 4,885 (31.2) 5,611 (33.2) 6,384 (36.7) 3,168 (34.3) Outcomes Acute kidney injury 2,713 (2.4) 198 (1.4) 292 (2.1) 331 (2.5) 282 (2.1) 420 (2.7) 437 (2.6) 471 (2.7) 282 (3.1) Hemodialysis 1,189 (1.1) 125 (0.9) 144 (1.1) 154 (1.2) 129 (1.0) 168 (1.1) 173 (1.0) 194 (1.1) 102 (1.1) Data are presented as N, N (%) or mean SD Changes in fluid use We analyzed national claims data to evaluate temporal changes in fluid usage in Korea from 2007 to 2021. The use of Hartmann’s solution increased during the early 2010s but gradually declined thereafter, whereas acetate-buffered balanced crystalloid steadily increased and reached nearly universal use at 99.95% by 2021. Hydroxyethyl starch use declined markedly from 87.6% in 2007 to 56.6% in 2021, particularly between 2013 and 2014, while albumin use remained consistently high, exceeding 90% in most years. Detailed yearly distribution of each intravenous fluid type is presented in [Figure 2 , Supplementary Table 1]. AKI and hemodialysis The primary outcomes are presented in [Table 2 , 3 ]. AKI occurred in 2,713 of 112,928 patients (2.4%), and 1,189 patients (1.1%) required hemodialysis as a result of severe AKI. The occurrence of AKI increased each year, reaching 3.1% in 2021, whereas the proportion of patients requiring hemodialysis remained stable at approximately 1% across the entire study period. Table 2 Baseline characteristics stratified by acute kidney injury and hemodialysis COPD: chronic obstructive pulmonary disease CABG: coronary artery bypass graft Total Acute kidney injury Hemodialysis Age < 40 6,617 79 (1.2) 27 (0.4) 40–49 10,256 175 (1.7) 71 (0.7) 50–64 38,872 768 (2.0) 350 (0.9) ≥ 65 57,183 1,691 (3.0) 741 (1.3) Sex Male 69,328 1,736 (2.5) 761 (1.1) Female 43,600 977 (2.2) 428 (1.0) Comorbidities Hypertension 62,132 1,865 (3.0) 864 (1.4) Dyslipidemia 40,417 1,195 (3.0) 566 (1.4) Diabetes mellitus 25,814 976 (3.8) 461 (1.8) Chronic kidney disease 4,680 725 (15.5) 516 (11.0) Cerebrovascular disease 19,007 608 (3.2) 285 (1.5) COPD 7,937 228 (2.9) 101 (1.3) Chronic hepatitis 6,873 184 (2.7) 82 (1.2) Liver cirrhosis 1,588 75 (4.7) 32 (2.0) Type of surgery Off-pump CABG 30,704 529 (1.7) 198 (0.6) On-pump CABG 15,733 439 (2.8) 214 (1.4) Valve surgery 26,169 671 (2.6) 356 (1.4) Thoracic aorta surgery 5,583 175 (3.1) 67 (1.2) Combined surgery 34,739 899 (2.6) 354 (1.0) Data are presented as N or N (%). Table 3 Patient outcomes by year Total 2007–2008 2009–2010 2011–2012 2013–2014 2015–2016 2017–2018 2019–2020 2021 Number of patients 112,928 13,657 13,584 13,258 13,249 15,647 16,918 17,389 9,226 Outcomes Acute kidney injury 2,713 (2.4) 198 (1.4) 292 (2.1) 331 (2.5) 282 (2.1) 420 (2.7) 437 (2.6) 471 (2.7) 282 (3.1) Hemodialysis 1,189 (1.1) 125 (0.9) 144 (1.1) 154 (1.2) 129 (1.0) 168 (1.1) 173 (1.0) 194 (1.1) 102 (1.1) Data are presented as N or N (%). Risk factors for AKI and hemodialysis Multivariable logistic regression analyses were presented in [Table 4 ]. Among fluid types, lactated Ringer’s solution was associated with lower odds of AKI and hemodialysis. In contrast, human albumin and RBC transfusion were associated with a higher likelihood of these outcomes, and RBC transfusion increased the risk of hemodialysis by about elevenfold and the risk of AKI by approximately fourfold. Acetate-buffered balanced crystalloid also showed a modest protective effect against hemodialysis, although less pronounced than lactated Ringer’s solution. Table 4 Associations between perioperative fluid/transfusion and postoperative acute kidney injury or hemodialysis Acute kidney injury Hemodialysis Adjusted OR (95% CI) p-value Adjusted OR (95% CI) p-value Isotonic fluid 0.9% saline Reference Reference Lactated Ringer's solution 0.90 (0.82–0.99) 0.029 0.61 (0.54–0.70) < 0.001 Acetate-buffered balanced crystalloid 1.09 (0.94–1.26) 0.239 0.78 (0.64–0.94) 0.010 Synthetic colloid 1.08 (0.98–1.19) 0.142 1.07 (0.92–1.24) 0.372 Human albumin 1.52 (1.32–1.74) < .001 1.60 (1.31–1.96) < .001 RBC transfusion 4.05 (3.26–5.03) < .001 11.72 (6.61–20.78) < .001 We analyzed synthetic colloid individually and collectively, but there were no significant differences in both AKI and hemodialysis outcomes [Supplementary Tables 2, 3]. So, we created the tables representing the synthetic colloid as one variable for simplicity. Mortality and length of stay Overall mortality remained stable from 2007 to 2021. In contrast, the length of hospital stay showed a decreasing trend, with the median value declining from 19 days in 2007 to 16 days in 2021. Both indicators peaked around 2012 before following these respective patterns [Supplementary Tables 4]. Subgroup analysis To explore the potential effects of variables, subgroup analyses were conducted based on age (< 65 vs. ≥65 years) [Supplementary Tables 5 and 6]. The outcomes analyzed were AKI and hemodialysis. Similar trends were observed in both age groups in the subgroup analyses. No significant differences were observed in AKI or hemodialysis outcomes between adjusted analyses 1 and 2, as synthetic colloid was not a significant factor, either individually or collectively. Multivariable Analyses about Secondary outcomes Multivariable analyses were performed to explore factors related to in-hospital mortality [Supplementary Tables 7]. Mortality tended to increase with age and appeared higher for thoracic aorta surgery, roughly six times that of off-pump CABG. Among comorbidities, dyslipidemia was associated with a slightly lower mortality, whereas DM, CKD, cerebrovascular disease, COPD, and liver cirrhosis were linked to higher mortality. Regarding fluid type, lactated Ringer’s solution, synthetic colloids, and human albumin were related to increased mortality, with RBC transfusion appearing to be particularly associated with higher mortality. Discussion Our results showed trends about AKI, severe renal injury requiring hemodialysis, and fluid use. Incidence of perioperative AKI was elevated over time, but the incidence of renal replacement therapy remained unchanged. The use of hydroxyethyl starch declined while isotonic fluids such as acetate-buffered balanced crystalloid and lactated Ringer’s solution became more common. This shift may reflect awareness of prior evidence linking synthetic colloids to acute kidney injury, rather than a direct causal relationship observed in this study [ 8 , 9 ]. Before 2007, AKI incidence after cardiothoracic surgery ranged between 6 ~ 40% [ 1 , 3 ]. In our cohort, the incidence of AKI had increased by approximately 2-fold. Part of the observed increase in AKI may be attributable to greater awareness and the adoption of standardized definitions such as RIFLE and KDIGO. These criteria classify even minor changes, for example a numerical rise in creatinine or a transient decrease in urine output, as AKI. As a result, cases with limited clinical impact are also captured, contributing to the higher reported incidence. The increase in AKI may reflect improved access to healthcare services, earlier diagnosis, and an aging patient population [ 10 – 12 ]. In contrast, the overall incidence in our study was lower than in prior reports, likely due to structural limitations of the database. The incidence of severe renal injury requiring hemodialysis was consistent with prior reports, which ranged from 1.2% to 3.0% [ 13 , 14 ]. Given that our analysis relied on administrative data, discrepancies in the overall incidence of AKI are expected when compared with studies using laboratory criteria. Nevertheless, the incidence of severe AKI requiring hemodialysis was similar to prior reports, which lends credibility to the robustness of our findings. Patients who receive albumin or RBC transfusion generally represent a more severely ill population. Albumin is often administered to patients with hypoalbuminemia, protein loss, or liver cirrhosis. The observed associations with adverse outcomes likely reflect greater underlying illness severity rather than a direct causal effect of albumin administration, consistent with previous controversial findings [ 15 – 17 ]. We performed multivariate logistic regression analysis to adjust for confounding factors, but residual confounding is likely, especially without data on serum albumin concentrations. Several recent studies have reported associations between low serum albumin levels and worse outcomes after cardiac surgery [ 18 – 21 ], suggesting that the observed relationship may reflect the adverse impact of underlying hypoalbuminemia rather than the effect of albumin itself. RBC transfusions are typically given in the setting of massive bleeding, hypotension, low hemoglobin levels, or hypovolemic shock, or when the surgery is complex or difficult. These findings should be interpreted cautiously, as transfusion likely reflects greater baseline severity and surgical complexity rather than a direct causal effect. Prior reports have similarly shown increased mortality and morbidity after transfusion, supporting the interpretation that transfusion serves as an indicator of critical illness rather than a direct cause of adverse outcomes [ 22 , 23 ]. For in-hospital and 1-year mortality, hypertension and DM were confirmed as risk factors. Interestingly, dyslipidemia appeared to be protective. This paradox may reflect the beneficial effects of lipid-lowering therapy, particularly statins, rather than dyslipidemia itself. This study has several limitations that should be considered when interpreting the findings. First, as a retrospective observational study based on administrative claims, the analysis can only describe associations and cannot support causal inference. A principal strength is the large, nationwide NHIS cohort, which provides comprehensive claims-based information on demographics, diagnoses, procedures, and length of stay, thereby improving statistical power and external generalizability. Second, AKI was identified using ICD diagnostic codes from claims data, and we lacked laboratory (creatinine, urine output) and perioperative clinical data. This likely led to under-ascertainment of AKI cases and limited our ability to stage AKI severity. Although our incidence estimates differ from some single-center reports that used laboratory-based definitions, the stable hemodialysis rates are broadly comparable with prior literature. By focusing on cardiac and thoracic aortic surgery, we were able to perform targeted, population-level trend analysis in a high-risk cohort. Third, the claims data did not include important clinical variables such as laboratory values (serum albumin, creatinine-based eGFR), hemodynamic parameters, fluid volumes or timing of administration, and transfusion timing, which precluded adjustment for these potential confounders. Finally, the study may be affected by immortal time bias and survivor bias because patients must survive long enough to accrue exposures (e.g., fluids, transfusions) and to be coded for AKI or hemodialysis. Early perioperative deaths could therefore lead to underestimated associations. Given the observational design and unmeasured confounding, we caution against causal interpretation despite the large sample size. In summary, perioperative AKI incidence increased to 3.1% by 2021 while hemodialysis rates remained stable at around 1%. Between 2007 and 2021, fluid management practices changed substantially: hydroxyethyl starch use decreased, albumin use increased, and acetate-buffered balanced crystalloid became nearly universally adopted. These findings describe temporal trends at the population level and should be interpreted as hypothesis-generating rather than evidence of causality. Prospective studies incorporating laboratory measurements, fluid volumes and timing, and more granular clinical data are required to elucidate potential mechanisms and causal effects. Declarations Conflict of interest No potential conflict of interest relevant to this article was reported. Funding None IRB number Exemption approval from the Institutional Review Board of Seoul National University Hospital (E-2204-039-1314) Research registration number NHIS-2025-03-1-070 Ethics approval and consent to participate This study was approved with exemption by the Institutional Review Board of Seoul National University Hospital (E-2204-039-1314) due to the anonymized nature of the data and minimal risk to participants. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding None. Author contributions Conceptualization: Yoon HC, Ryu HG Data curation: Yoon HC, You SH, Kim HJ, Kim JY, Jung SY, Ryu HG Formal analysis: You SH Methodology: Yoon HC, You SH, Jung SY, Ryu HG Visualization: Yoon HC, You SH, Jung SY Writing – original draft: Yoon HC Writing – review & editing: Yoon HC, Ryu HG References Hobson CE, Yavas S, Segal MS, Schold JD, Tribble CG, Layon AJ, et al. Acute kidney injury is associated with increased long-term mortality after cardiothoracic surgery. Circulation. 2009;119(18):2444–53. 10.1161/CIRCULATIONAHA.108.800011 . Chertow GM, Levy EM, Hammermeister KE, Grover F, Daley J. Independent association between acute renal failure and mortality following cardiac surgery. Am J Med. 1998;104(4):343–8. 10.1016/s0002-9343(98)00058-8 . Antunes PE, Prieto D, Ferrao de Oliveira J, Antunes MJ. Renal dysfunction after myocardial revascularization. Eur J Cardiothorac Surg. 2004;25(4):597–604. 10.1016/j.ejcts.2004.01.010 . 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Association of hydroxyethyl starch administration with mortality and acute kidney injury in critically ill patients requiring volume resuscitation: a systematic review and meta-analysis. JAMA. 2013;309(7):678–88. 10.1001/jama.2013.430 . Myburgh JA, Finfer S, Bellomo R, Billot L, Cass A, Gattas D, et al. Hydroxyethyl starch or saline for fluid resuscitation in intensive care. N Engl J Med. 2012;367(20):1901–11. 10.1056/NEJMoa1209759 . Lameire N, Van Biesen W, Vanholder R. The changing epidemiology of acute renal failure. Nat Clin Pract Nephrol. 2006;2(7):364–77. 10.1038/ncpneph0218 . Rodrigues FB, Bruetto RG, Torres US, Otaviano AP, Zanetta DM, Burdmann EA. Incidence and mortality of acute kidney injury after myocardial infarction: a comparison between KDIGO and RIFLE criteria. PLoS ONE. 2013;8(7):e69998. 10.1371/journal.pone.0069998 . Susantitaphong P, Cruz DN, Cerda J, Abulfaraj M, Alqahtani F, Koulouridis I, et al. World incidence of AKI: a meta-analysis. 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Can J Anaesth. 2021;68(8):1197–213. 10.1007/s12630-021-01991-7 . van Beek DEC, van der Horst ICC, de Geus AF, Mariani MA, Scheeren TWL. Albumin, a marker for post-operative myocardial damage in cardiac surgery. J Crit Care. 2018;47:55–60. 10.1016/j.jcrc.2018.06.009 . Shehabi Y, Balachandran M, Al-Bassam W, Bailey M, Bellomo R, Bihari S, et al. Postoperative 20% Albumin Infusion and Acute Kidney Injury in High-Risk Cardiac Surgery Patients: The ALBICS AKI Randomized Clinical Trial. JAMA Surg. 2025. 10.1001/jamasurg.2025.1683 . Zhang H, Yan S, Bian L, Wang J, Wang T, Liu G, et al. Intraoperative 20% albumin infusion and acute kidney injury in on-pump cardiac surgery: a focus on preoperative albumin levels. Ren Fail. 2025;47(1):2522327. 10.1080/0886022X.2025.2522327 . Coca SG, Jammalamadaka D, Sint K, Thiessen Philbrook H, Shlipak MG, Zappitelli M, et al. Preoperative proteinuria predicts acute kidney injury in patients undergoing cardiac surgery. J Thorac Cardiovasc Surg. 2012;143(2):495–502. 10.1016/j.jtcvs.2011.09.023 . Xu R, Hao M, Zhou W, Liu M, Wei Y, Xu J, et al. Preoperative hypoalbuminemia in patients undergoing cardiac surgery: a meta-analysis. Surg Today. 2023;53(8):861–72. 10.1007/s00595-022-02566-9 . Murphy GJ, Reeves BC, Rogers CA, Rizvi SI, Culliford L, Angelini GD. Increased mortality, postoperative morbidity, and cost after red blood cell transfusion in patients having cardiac surgery. Circulation. 2007;116(22):2544–52. 10.1161/CIRCULATIONAHA.107.698977 . Colson PH, Gaudard P, Meunier C, Seguret F. Impact of Red Blood Cell Transfusion on In-hospital Mortality of Isolated Coronary Artery Bypass Graft Surgery: A Retrospective Observational Study of French Nationwide 3-year Cohort. Ann Surg. 2023;278(1):e184–9. 10.1097/SLA.0000000000005488 . Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8643743","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":590490790,"identity":"fec40c0f-8fe8-41c8-b233-7f4a7c2c841e","order_by":0,"name":"Hee-Chul Yoon","email":"","orcid":"","institution":"Seoul National University","correspondingAuthor":false,"prefix":"","firstName":"Hee-Chul","middleName":"","lastName":"Yoon","suffix":""},{"id":590490791,"identity":"2938da8f-2125-4a87-906d-a4024336a4f3","order_by":1,"name":"Seung-Hun You","email":"","orcid":"","institution":"Chung-Ang University","correspondingAuthor":false,"prefix":"","firstName":"Seung-Hun","middleName":"","lastName":"You","suffix":""},{"id":590490793,"identity":"83414fab-88e8-49af-9a68-a70180505a5c","order_by":2,"name":"Ha-Jung Kim","email":"","orcid":"","institution":"Chung-Ang University","correspondingAuthor":false,"prefix":"","firstName":"Ha-Jung","middleName":"","lastName":"Kim","suffix":""},{"id":590490795,"identity":"c5cc7982-21c5-41c3-a154-b92b30613af6","order_by":3,"name":"Jeong-Yeon Kim","email":"","orcid":"","institution":"Chung-Ang University","correspondingAuthor":false,"prefix":"","firstName":"Jeong-Yeon","middleName":"","lastName":"Kim","suffix":""},{"id":590490796,"identity":"6b49482a-5484-4e27-ba7f-f3966690c1fb","order_by":4,"name":"Sun-Young Jung","email":"","orcid":"","institution":"Chung-Ang University","correspondingAuthor":false,"prefix":"","firstName":"Sun-Young","middleName":"","lastName":"Jung","suffix":""},{"id":590490799,"identity":"30382923-b397-46fc-84e8-50835cd63a80","order_by":5,"name":"Ho-Geol Ryu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYBACAzBZ8N+OHyYiQZwWA+ZkyQZStTBuOECsFnP29osPPhiwMRufP3tMgqHGjkFy9gH8Wix7zhQbzjDg4TO7kZcmwXAsmUGaL4GAw27kpEnzGEgwm93gMZNgYDvAIMdDyC83ctJ/8xgYMG7uPwPU8o8oLenHmHkMEhg3MOSYSTC2HWCQJqjlzBlmyRkGB5IlbuQYWyT2JfNI9hDScrz94YcPFQfs+PvPGN748M1OTuIMAS0MDDwGCHYCkEtQAwMD+wMiFI2CUTAKRsGIBgB45TrzgryEFQAAAABJRU5ErkJggg==","orcid":"","institution":"Seoul National University","correspondingAuthor":true,"prefix":"","firstName":"Ho-Geol","middleName":"","lastName":"Ryu","suffix":""}],"badges":[],"createdAt":"2026-01-20 01:39:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8643743/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8643743/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102738567,"identity":"8f89e9dd-f48c-4c32-a3b2-159b7ffd1362","added_by":"auto","created_at":"2026-02-16 06:59:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":80902,"visible":true,"origin":"","legend":"\u003cp\u003ePopulation flow chart. Enrollment process, exclusions, and final study population\u003c/p\u003e","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8643743/v1/44906936be7f11b4bb12e3d8.png"},{"id":102738568,"identity":"cae5c6a6-b0bc-4907-afdb-b286681035a4","added_by":"auto","created_at":"2026-02-16 06:59:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":68649,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trends in perioperative use of major intravenous fluids from 2007 to 2021\u003c/p\u003e","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8643743/v1/c16a539cb50cceb96ca0d5a0.png"},{"id":106961493,"identity":"4d961167-e9ba-4fd9-a300-a39e3311b1bb","added_by":"auto","created_at":"2026-04-15 09:25:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1226064,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8643743/v1/b1c9af97-ab3e-49e1-aaba-363e5c2d7bec.pdf"},{"id":102738569,"identity":"89768f63-063d-4ba3-a24d-46d1be6eb54b","added_by":"auto","created_at":"2026-02-16 06:59:57","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":256992,"visible":true,"origin":"","legend":"","description":"","filename":"appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-8643743/v1/df15770be0df155f697079c4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Perioperative intravenous fluid for cardiothoracic surgery and acute kidney injury in Korea between 2007 and 2021","fulltext":[{"header":"Key points","content":"\u003cp\u003ePerioperative intravenous fluid practices in cardiothoracic surgery changed substantially in Korea between 2007 and 2021.\u003c/p\u003e\u003cp\u003eThe use of synthetic colloids decreased, while acetate-buffered balanced crystalloids became nearly universal.\u003c/p\u003e\u003cp\u003eThe incidence of acute kidney injury increased over time, whereas rates of hemodialysis remained stable.\u003c/p\u003e\u003cp\u003eAlbumin administration and red blood cell transfusion were associated with higher risks of renal complications and mortality.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eAcute kidney injury (AKI) is a common complication following cardiac surgery with a reported incidence ranging from 7.7% to 40% in cardiac surgery and as high as 55% in patients undergoing aorta surgery [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Cardiopulmonary bypass, aorta cross clamping, and the use of transfusion and vasopressors, may increase the risk of AKI compared to non-cardiac surgery [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Accordingly, postoperative AKI in cardiac surgery patients is not only frequent but also clinically significant, as it has been consistently associated with increased mortality and prolonged hospitalization in critically ill populations [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFluid therapy protocols have evolved with the adoption of early goal-directed therapy and updates to transfusion guidelines, including a shift toward restrictive transfusion thresholds and less invasive hemodynamic monitoring [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, there is limited research on how fluid use has actually changed in clinical practice and its impact on subsequent morbidity and mortality. Therefore, we investigated trends in fluid use and their association with postoperative AKI and mortality.\u003c/p\u003e \u003cp\u003eWe hypothesized that the incidence of AKI after cardiac or aortic surgery is associated with temporal changes in perioperative fluid administration. A large-scale time-series data analysis using the Korean National Health Insurance Service (NHIS) database was conducted, evaluating patients who underwent cardiac or thoracic aorta surgery.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEthics approval\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003e\u003c/strong\u003e \u003cp\u003eEthical approval for this study (IRB No. E-2204-039-1314; chairperson not applicable due to exemption) was provided by the Institutional Review Board of Seoul National University College of Medicine and Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea, on 15 April 2022. The board granted exemption due to the anonymized nature of the data and the minimal risk to patients.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy design and Patient population\u003c/h3\u003e\n\u003cp\u003eThis retrospective cohort study used data from the Korean National Health Insurance Service (NHIS) database (Research management number: NHIS-2025-03-01-070). The cohort entry period was defined as 2006 to 2020 with an additional year for observation (to 2021). Potential sources of bias, including selection and information bias, were minimized by using a comprehensive nationwide claims database that covers nearly the entire Korean population.\u003c/p\u003e \u003cp\u003eThe study cohort included adult patients (18 years or older) who underwent cardiac surgery (coronary artery bypass grafting (CABG), valve surgery, or thoracic aorta surgery) between 2007 and 2020. In cases where more than one surgical procedure was performed within a one-year period, only the first episode was selected. Patients who underwent surgery in 2007 but had also received cardiothoracic surgery in 2006 were excluded to ensure that only the first surgery within a one-year period was counted. To rule out pre-existing renal dysfunction, patients who had received hemodialysis within 3 months prior to surgery were excluded. Patients without any fluid claim, including crystalloids, were excluded because these cases were considered to have missing information on the exposure variable. Subgroup analyses were conducted for patients aged 65 years or older. We included all eligible cases in the national database. Therefore, a prior sample size calculation was not required. The patient selection process is illustrated in [Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eVariables and outcomes definition\u003c/h3\u003e\n\u003cp\u003eIndependent variables included the type of fluid administered, type of surgery performed, demographic data, comorbidities, and red blood cell (RBC) transfusion. Comorbidities were identified based on ICD-10 code and medication history recorded in the NHIS database. Hypertension, dyslipidemia, and diabetes mellitus (DM) were recognized only when there was an accompanying co-prescription history of relevant medications for at least one month within the 3 months prior to surgery. Other comorbidities included chronic kidney disease (CKD), cerebrovascular disease, chronic obstructive pulmonary disease (COPD), chronic hepatitis, and liver cirrhosis. Demographic factors such as age and sex were also included in the analysis.\u003c/p\u003e \u003cp\u003eFluids were categorized into crystalloids, colloids, and blood transfusion, and further subdivided into 0.9% saline, lactated Ringer\u0026rsquo;s solution, acetate-buffered balanced crystalloid (Brand name in Korea - Plasma solution A (PSA)), hydroxyethyl starch, pentastarch, dextran, albumin, and red blood cells (RBCs). Perioperative fluid exposure was defined as the total amount of fluid administered during the index hospitalization, including intraoperative and immediate postoperative periods.\u003c/p\u003e \u003cp\u003eSurgical procedures were classified into on-pump CABG, off-pump CABG, valve surgery, thoracic aorta surgery, and combined surgery. If a patient underwent multiple surgical procedures during a single admission, the case was defined as combined surgery. Fluids and surgical procedures were identified from insurance claims.\u003c/p\u003e \u003cp\u003eAKI was defined using the ICD-10 code N17.9 (acute renal failure), and hemodialysis was identified based on procedure codes from O7020 to O7081 in the insurance claims.\u003c/p\u003e \u003cp\u003eThe primary aim of this study was to evaluate changes in fluid use over time in patients undergoing cardiac or thoracic aorta surgery. Primary outcomes included the incidence of AKI and hemodialysis. Secondary outcomes were in-hospital mortality, 1-year mortality, hospital length of stay, and ICU length of stay.\u003c/p\u003e \u003cp\u003eIn-hospital mortality was defined as death before discharge, and 1-year mortality as death within one year after surgery. Patients were followed for up to 1 year postoperatively for 1-year mortality. ICU stay was measured based on insurance claim records. We also examined whether temporal changes in fluid use were associated with clinical outcomes such as mortality and length of stay.\u003c/p\u003e\n\u003ch3\u003eStatistical analysis and data analysis\u003c/h3\u003e\n\u003cp\u003eContinuous variables are presented as means with standard deviations (SD) or medians with interquartile ranges, while categorical variables are expressed as number and percentage. Differences in covariates across study years were assessed using analysis of variance for continuous variables and the chi-square test for categorical variables.\u003c/p\u003e \u003cp\u003eMultivariable logistic regression analyses were performed to compute the odds ratios (OR) and 95% confidence intervals (CI) of factors associated with primary (AKI and hemodialysis) and secondary (in-hospital and one-year mortality) outcomes. Covariates associated with the outcomes in univariable analyses (P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.2) were included in the final multivariable model. Subgroup analyses for primary outcomes were conducted according to age (\u0026ge;\u0026thinsp;65 or \u0026lt;\u0026thinsp;65 years).\u003c/p\u003e \u003cp\u003eAll analyses were performed with SAS version 9.4 software (SAS Institute, Cary, NC, USA). Statistical significance was determined at a p value of \u0026lt;\u0026thinsp;0.05 (two-tailed).\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePatient data\u003c/h2\u003e \u003cp\u003eThe initial cohort included 121,306 patients, all of whom underwent cardiac or thoracic aorta surgery between 2007 and 2021. After applying the exclusion criteria, 112,928 patients were included in the analysis.\u003c/p\u003e \u003cp\u003eBaseline characteristics and annual data are presented in [Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e]. The age distribution of patients changed over time. The proportion and number of patients under 50 declined, while those aged 50 and older increased, most notably among those aged 65 or older.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient characteristics by year COPD: chronic obstructive pulmonary disease CABG: coronary artery bypass graft\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2007\u0026ndash;2008\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2011\u0026ndash;2012\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2013\u0026ndash;2014\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2015\u0026ndash;2016\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2017\u0026ndash;2018\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2019\u0026ndash;2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112,928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13,584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13,258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13,249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15,647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16,918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17,389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9,226\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.79\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.8\u0026thinsp;\u0026plusmn;\u0026thinsp;13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e62.1\u0026thinsp;\u0026plusmn;\u0026thinsp;13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e63.1\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e64.1\u0026thinsp;\u0026plusmn;\u0026thinsp;12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e64.7\u0026thinsp;\u0026plusmn;\u0026thinsp;12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e65.0\u0026thinsp;\u0026plusmn;\u0026thinsp;12.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,617 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,124 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e963 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e907 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e860 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e843 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e776 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e746 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e398 (4.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,256 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,609 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,508 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,357 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,261 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,394 (8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1,375 (8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1,180 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e572 (6.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38,872 (34.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,096 (37.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,861 (35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,622 (34.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,576 (34.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,398 (34.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5,589 (33.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5,794 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2,936 (31.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57,183 (50.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,828 (42.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,252 (46.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,372 (48.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,552 (49.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,012 (51.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9,178 (54.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9,669 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5,320 (57.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69,328 (61.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,216 (60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,091 (59.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7,968 (60.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,123 (61.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,577 (61.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10,505 (62.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10,985 (63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5,863 (63.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43,600 (38.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,441 (39.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,493 (40.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,290 (39.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,126 (38.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,070 (38.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6,413 (37.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6,404 (36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3,363 (36.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62,132 (55.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,032 (36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,723 (56.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7,545 (56.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,525 (56.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,927 (57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9,773 (57.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10,162 (58.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5,445 (59.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40,417 (35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,222 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,687 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,101 (30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,470 (33.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,118(39.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7,108 (42.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8,208 (47.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4,503 (48.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25,814 (22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,926 (14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,847 (21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,924 (22.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,054 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,664 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4,180 (24.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4,634 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2,585 (28.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,680 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e211 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e341 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e432 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e513 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e691 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e884 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1,000 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e608 (6.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19,007 (16.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,280 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,292 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,235 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,228 (16.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,690 (17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3,165 (18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3,323 (19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1,794 (19.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,937 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e586 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,106 (8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,067 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e956 (7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,139 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1,212 (7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1,233 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e638 (6.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic hepatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,873 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e506 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e875 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e818 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e752 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e817 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1,053 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1,347 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e705 (7.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cirrhosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,588 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e151 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e166 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e234 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e320 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e314 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e182 (2.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOff-pump CABG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26,169 (23.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,647 (26.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,262 (24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,145 (23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,096 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,667 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3,782 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3,746 (21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1,824 (19.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOn-pump CABG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,733 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,609 (19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,386 (17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,091 (15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,795 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,113 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2,019 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1,759 (10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e961 (10.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValve surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30,704 (27.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,348 (24.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,693 (27.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,603 (27.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,811 (28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,354 (27.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4,846 (28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4,638 (26.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2,411 (26.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThoracic aorta surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,583 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e594 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e642 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e655 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e680 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e628 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e660 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e862 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e862 (9.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombined surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34,739 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,459 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,601 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,764 (28.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,867 (29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,885 (31.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5,611 (33.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6,384 (36.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3,168 (34.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute kidney injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,713 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e198 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e292 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e331 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e282 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e420 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e437 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e471 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e282 (3.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemodialysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,189 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e154 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e129 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e168 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e173 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e194 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e102 (1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eData are presented as N, N (%) or mean SD\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eChanges in fluid use\u003c/h3\u003e\n\u003cp\u003eWe analyzed national claims data to evaluate temporal changes in fluid usage in Korea from 2007 to 2021. The use of Hartmann\u0026rsquo;s solution increased during the early 2010s but gradually declined thereafter, whereas acetate-buffered balanced crystalloid steadily increased and reached nearly universal use at 99.95% by 2021. Hydroxyethyl starch use declined markedly from 87.6% in 2007 to 56.6% in 2021, particularly between 2013 and 2014, while albumin use remained consistently high, exceeding 90% in most years. Detailed yearly distribution of each intravenous fluid type is presented in [Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Supplementary Table\u0026nbsp;1].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eAKI and hemodialysis\u003c/h3\u003e\n\u003cp\u003eThe primary outcomes are presented in [Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e]. AKI occurred in 2,713 of 112,928 patients (2.4%), and 1,189 patients (1.1%) required hemodialysis as a result of severe AKI. The occurrence of AKI increased each year, reaching 3.1% in 2021, whereas the proportion of patients requiring hemodialysis remained stable at approximately 1% across the entire study period.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics stratified by acute kidney injury and hemodialysis COPD: chronic obstructive pulmonary disease CABG: coronary artery bypass graft\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAcute kidney injury\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHemodialysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (0.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71 (0.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38,872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e768 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e350 (0.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57,183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,691 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e741 (1.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69,328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,736 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e761 (1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43,600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e977 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e428 (1.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62,132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,865 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e864 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40,417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,195 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e566 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25,814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e976 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e461 (1.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e725 (15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e516 (11.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19,007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e608 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e285 (1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e228 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101 (1.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic hepatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e184 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82 (1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cirrhosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (2.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOff-pump CABG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30,704\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e529 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e198 (0.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOn-pump CABG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e439 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e214 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValve surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26,169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e671 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e356 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThoracic aorta surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67 (1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombined surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34,739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e899 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e354 (1.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are presented as N or N (%).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient outcomes by year\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2007\u0026ndash;2008\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2011\u0026ndash;2012\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2013\u0026ndash;2014\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2015\u0026ndash;2016\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2017\u0026ndash;2018\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2019\u0026ndash;2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112,928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13,584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13,258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13,249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15,647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16,918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17,389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9,226\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute kidney injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,713 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e198 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e292 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e331 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e282 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e420 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e437 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e471 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e282 (3.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemodialysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,189 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e154 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e129 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e168 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e173 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e194 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e102 (1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003eData are presented as N or N (%).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRisk factors for AKI and hemodialysis\u003c/h2\u003e \u003cp\u003eMultivariable logistic regression analyses were presented in [Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e]. Among fluid types, lactated Ringer\u0026rsquo;s solution was associated with lower odds of AKI and hemodialysis. In contrast, human albumin and RBC transfusion were associated with a higher likelihood of these outcomes, and RBC transfusion increased the risk of hemodialysis by about elevenfold and the risk of AKI by approximately fourfold. Acetate-buffered balanced crystalloid also showed a modest protective effect against hemodialysis, although less pronounced than lactated Ringer\u0026rsquo;s solution.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociations between perioperative fluid/transfusion and postoperative acute kidney injury or hemodialysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eAcute kidney injury\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e \u003cp\u003eHemodialysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsotonic fluid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.9% saline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactated Ringer's solution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0.90 (0.82\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0.61 (0.54\u0026ndash;0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcetate-buffered balanced crystalloid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1.09 (0.94\u0026ndash;1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0.78 (0.64\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSynthetic colloid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1.08 (0.98\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.07 (0.92\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.372\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman albumin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1.52 (1.32\u0026ndash;1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.60 (1.31\u0026ndash;1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRBC transfusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e4.05 (3.26\u0026ndash;5.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e11.72 (6.61\u0026ndash;20.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe analyzed synthetic colloid individually and collectively, but there were no significant differences in both AKI and hemodialysis outcomes [Supplementary Tables\u0026nbsp;2, 3]. So, we created the tables representing the synthetic colloid as one variable for simplicity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMortality and length of stay\u003c/h2\u003e \u003cp\u003eOverall mortality remained stable from 2007 to 2021. In contrast, the length of hospital stay showed a decreasing trend, with the median value declining from 19 days in 2007 to 16 days in 2021. Both indicators peaked around 2012 before following these respective patterns [Supplementary Tables\u0026nbsp;4].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis\u003c/h2\u003e \u003cp\u003eTo explore the potential effects of variables, subgroup analyses were conducted based on age (\u0026lt;\u0026thinsp;65 vs. \u0026ge;65 years) [Supplementary Tables\u0026nbsp;5 and 6]. The outcomes analyzed were AKI and hemodialysis. Similar trends were observed in both age groups in the subgroup analyses. No significant differences were observed in AKI or hemodialysis outcomes between adjusted analyses 1 and 2, as synthetic colloid was not a significant factor, either individually or collectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMultivariable Analyses about Secondary outcomes\u003c/h2\u003e \u003cp\u003eMultivariable analyses were performed to explore factors related to in-hospital mortality [Supplementary Tables\u0026nbsp;7]. Mortality tended to increase with age and appeared higher for thoracic aorta surgery, roughly six times that of off-pump CABG. Among comorbidities, dyslipidemia was associated with a slightly lower mortality, whereas DM, CKD, cerebrovascular disease, COPD, and liver cirrhosis were linked to higher mortality. Regarding fluid type, lactated Ringer\u0026rsquo;s solution, synthetic colloids, and human albumin were related to increased mortality, with RBC transfusion appearing to be particularly associated with higher mortality.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur results showed trends about AKI, severe renal injury requiring hemodialysis, and fluid use. Incidence of perioperative AKI was elevated over time, but the incidence of renal replacement therapy remained unchanged. The use of hydroxyethyl starch declined while isotonic fluids such as acetate-buffered balanced crystalloid and lactated Ringer\u0026rsquo;s solution became more common. This shift may reflect awareness of prior evidence linking synthetic colloids to acute kidney injury, rather than a direct causal relationship observed in this study [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBefore 2007, AKI incidence after cardiothoracic surgery ranged between 6\u0026thinsp;~\u0026thinsp;40% [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In our cohort, the incidence of AKI had increased by approximately 2-fold. Part of the observed increase in AKI may be attributable to greater awareness and the adoption of standardized definitions such as RIFLE and KDIGO. These criteria classify even minor changes, for example a numerical rise in creatinine or a transient decrease in urine output, as AKI. As a result, cases with limited clinical impact are also captured, contributing to the higher reported incidence. The increase in AKI may reflect improved access to healthcare services, earlier diagnosis, and an aging patient population [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In contrast, the overall incidence in our study was lower than in prior reports, likely due to structural limitations of the database. The incidence of severe renal injury requiring hemodialysis was consistent with prior reports, which ranged from 1.2% to 3.0% [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Given that our analysis relied on administrative data, discrepancies in the overall incidence of AKI are expected when compared with studies using laboratory criteria. Nevertheless, the incidence of severe AKI requiring hemodialysis was similar to prior reports, which lends credibility to the robustness of our findings.\u003c/p\u003e \u003cp\u003ePatients who receive albumin or RBC transfusion generally represent a more severely ill population. Albumin is often administered to patients with hypoalbuminemia, protein loss, or liver cirrhosis. The observed associations with adverse outcomes likely reflect greater underlying illness severity rather than a direct causal effect of albumin administration, consistent with previous controversial findings [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. We performed multivariate logistic regression analysis to adjust for confounding factors, but residual confounding is likely, especially without data on serum albumin concentrations. Several recent studies have reported associations between low serum albumin levels and worse outcomes after cardiac surgery [\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], suggesting that the observed relationship may reflect the adverse impact of underlying hypoalbuminemia rather than the effect of albumin itself.\u003c/p\u003e \u003cp\u003eRBC transfusions are typically given in the setting of massive bleeding, hypotension, low hemoglobin levels, or hypovolemic shock, or when the surgery is complex or difficult. These findings should be interpreted cautiously, as transfusion likely reflects greater baseline severity and surgical complexity rather than a direct causal effect. Prior reports have similarly shown increased mortality and morbidity after transfusion, supporting the interpretation that transfusion serves as an indicator of critical illness rather than a direct cause of adverse outcomes [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor in-hospital and 1-year mortality, hypertension and DM were confirmed as risk factors. Interestingly, dyslipidemia appeared to be protective. This paradox may reflect the beneficial effects of lipid-lowering therapy, particularly statins, rather than dyslipidemia itself.\u003c/p\u003e \u003cp\u003eThis study has several limitations that should be considered when interpreting the findings. First, as a retrospective observational study based on administrative claims, the analysis can only describe associations and cannot support causal inference. A principal strength is the large, nationwide NHIS cohort, which provides comprehensive claims-based information on demographics, diagnoses, procedures, and length of stay, thereby improving statistical power and external generalizability.\u003c/p\u003e \u003cp\u003eSecond, AKI was identified using ICD diagnostic codes from claims data, and we lacked laboratory (creatinine, urine output) and perioperative clinical data. This likely led to under-ascertainment of AKI cases and limited our ability to stage AKI severity. Although our incidence estimates differ from some single-center reports that used laboratory-based definitions, the stable hemodialysis rates are broadly comparable with prior literature. By focusing on cardiac and thoracic aortic surgery, we were able to perform targeted, population-level trend analysis in a high-risk cohort.\u003c/p\u003e \u003cp\u003eThird, the claims data did not include important clinical variables such as laboratory values (serum albumin, creatinine-based eGFR), hemodynamic parameters, fluid volumes or timing of administration, and transfusion timing, which precluded adjustment for these potential confounders.\u003c/p\u003e \u003cp\u003eFinally, the study may be affected by immortal time bias and survivor bias because patients must survive long enough to accrue exposures (e.g., fluids, transfusions) and to be coded for AKI or hemodialysis. Early perioperative deaths could therefore lead to underestimated associations. Given the observational design and unmeasured confounding, we caution against causal interpretation despite the large sample size.\u003c/p\u003e \u003cp\u003eIn summary, perioperative AKI incidence increased to 3.1% by 2021 while hemodialysis rates remained stable at around 1%. Between 2007 and 2021, fluid management practices changed substantially: hydroxyethyl starch use decreased, albumin use increased, and acetate-buffered balanced crystalloid became nearly universally adopted. These findings describe temporal trends at the population level and should be interpreted as hypothesis-generating rather than evidence of causality. Prospective studies incorporating laboratory measurements, fluid volumes and timing, and more granular clinical data are required to elucidate potential mechanisms and causal effects.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo potential conflict of interest relevant to this article was reported.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIRB number\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExemption approval from the Institutional Review Board of Seoul National University Hospital (E-2204-039-1314)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch registration number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNHIS-2025-03-1-070\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved with exemption by the Institutional Review Board of Seoul National University Hospital (E-2204-039-1314) due to the anonymized nature of the data and minimal risk to participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Yoon HC, Ryu HG\u003c/p\u003e\n\u003cp\u003eData curation: Yoon HC, You SH, Kim HJ, Kim JY, Jung SY, Ryu HG\u003c/p\u003e\n\u003cp\u003eFormal analysis: You SH\u003c/p\u003e\n\u003cp\u003eMethodology: Yoon HC, You SH, Jung SY, Ryu HG\u003c/p\u003e\n\u003cp\u003eVisualization: Yoon HC, You SH, Jung SY\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; original draft: Yoon HC\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; review \u0026amp; editing: Yoon HC, Ryu HG\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHobson CE, Yavas S, Segal MS, Schold JD, Tribble CG, Layon AJ, et al. 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Ann Surg. 2023;278(1):e184\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/SLA.0000000000005488\u003c/span\u003e\u003cspan address=\"10.1097/SLA.0000000000005488\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"acute kidney injury, renal insufficiency, thoracic surgery, mortality, fluid therapy, colloids","lastPublishedDoi":"10.21203/rs.3.rs-8643743/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8643743/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground:\u003c/p\u003e\n\u003cp\u003eAlthough fluid therapy in cardiothoracic surgery has been widely studied, how restrictions on synthetic colloids have influenced practice and kidney outcomes remain unclear.\u003c/p\u003e\n\u003cp\u003eObjective:\u003c/p\u003e\n\u003cp\u003eTo describe temporal changes in perioperative intravenous fluid use and to examine associations with acute kidney injury (AKI) and hemodialysis in patients undergoing cardiac or thoracic aorta surgery.\u003c/p\u003e\n\u003cp\u003eDesign:\u003c/p\u003e\n\u003cp\u003eRetrospective nationwide cohort study.\u003c/p\u003e\n\u003cp\u003eSetting:\u003c/p\u003e\n\u003cp\u003eKorean National Health Insurance Service (NHIS) database.\u003c/p\u003e\n\u003cp\u003ePatients:\u003c/p\u003e\n\u003cp\u003eAdult patients undergoing cardiac or thoracic aorta surgery in Korea between 2007 and 2021.\u003c/p\u003e\n\u003cp\u003eInterventions:\u003c/p\u003e\n\u003cp\u003eNone; perioperative intravenous fluid exposure was assessed using national insurance claims data.\u003c/p\u003e\n\u003cp\u003eMain outcome measures:\u003c/p\u003e\n\u003cp\u003eThe primary outcomes were AKI and newly required hemodialysis. Secondary outcomes included in-hospital and 1-year mortality.\u003c/p\u003e\n\u003cp\u003eResults:\u003c/p\u003e\n\u003cp\u003eA total of 112,928 patients were analyzed. AKI occurred in 2.4%, and 1.1% required hemodialysis. From 2007 to 2021, the use of synthetic colloids decreased substantially, whereas acetate-buffered balanced crystalloid use increased to near-universal adoption. Albumin administration and red blood cell transfusion were independently associated with higher odds of AKI and hemodialysis after adjustment for covariates. Over time, the incidence of AKI increased, while the incidence of hemodialysis remained stable.\u003c/p\u003e\n\u003cp\u003eConclusion:\u003c/p\u003e\n\u003cp\u003eBetween 2007 and 2021, the incidence of perioperative AKI increased from 1.4% to 3.1%, whereas the incidence of hemodialysis remained stable at approximately 1%. During the same period, perioperative fluid management changed substantially, with decreased use of synthetic colloids and near-universal adoption of acetate-buffered balanced crystalloids. These findings represent population-level temporal trends and should be interpreted as descriptive rather than causal.\u003c/p\u003e","manuscriptTitle":"Perioperative intravenous fluid for cardiothoracic surgery and acute kidney injury in Korea between 2007 and 2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-16 06:59:52","doi":"10.21203/rs.3.rs-8643743/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a130bf39-9011-4f4f-8bbc-e18b5bdc6739","owner":[],"postedDate":"February 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-15T07:43:21+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-16 06:59:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8643743","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8643743","identity":"rs-8643743","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}