Abstract
Background
Autologous blood transfusion (ABT), as a blood conservation strategy, is widely used in surgeries for acute Stanford-A aortic dissection(ATAAD). However, investigations into the correlation between ABT and postoperative 24-hour serum creatinine(Scr) are limited. This study evaluates the relationship between ABT and Scr in patients who underwent ATAAD surgery.
Methods
This retrospective study included 157 ATAAD patients from our center between February 2020 and November 2022. Patients were categorized into a death group(n = 12) and a survival group (n = 145) based on individual prognosis. Main outcome measures included ABT, postoperative-24 h Scr, age and postoperative-24 h albumin (ALB).
Results
The postoperative-24 h Scr in the death group was significantly higher compared to the survival group (328.71 (153.22)umol/L vs. 214.02 (106.46) umol/L). After adjusting for potential confounders(age, sex, hypertension, chronic renal inefficiency (CRI), renal artery compression, hyperlipidemia, cardiopulmonary bypass (CPB), ALB and intraoperative ventilation time(IVT)), a non-linear relationship was detected between ABT and Scr with an inflection point at 814 ml. Subgroup analysis for patients aged under 47 years and ALB levels above 37.7 g/L revealed a positive correlation between Scr and ABT(β = 0.11, 95%CI (0.03, 0.20), β = 0.14, 95%CI (0.05, 0.23), respectively).
Conclusion
The relationship between ABT and Scr in ATAAD patients exhibits a non-linear pattern with a positive correlation noted when ABT was below 814 ml. This trend was consistent in younger patients and those with higher ALB levels. These findings suggest that the dosage of ABT may impact renal function in ATAAD patients; further research is necessary to clarify the underlying mechanisms.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12871-026-03629-x.
Keywords: Autologous blood transfusion, Serum creatinine, Acute Stanford-A aortic dissection, Non-linear relationship
Introduction
Acute aortic dissection (AAD) represents a severe and life-threatening cardiovascular condition characterized by high morbidity and mortality rates, occurring due to a tear in the aortic intimal layer and subsequent separation or dissection of the aortic wall [1].AAD is classified as Stanford-A, involving the ascending aorta and/or the aortic arch, and Stanford-B, affecting the descending aorta and/or the thoracoabdominal aorta [2]. The mortality rate for acute Stanford-A aortic dissection (ATAAD) in China is approximately 10.3% [3]. Previous research has indicated that ATAAD surgery, a complex procedure, is often accompanied by significant blood loss and renal malperfusion [4].Consequently, protecting postoperative renal function is paramount. Renal function is closely linked to intraoperative fluid management. The substantial volume of autologous blood transfusion (ABT) during surgery may influence renal function and impact patient prognosis. Therefore, this study aims to investigate the impact of ABT on postoperative renal function.
Serum creatinine(Scr) levels are commonly used to assess renal function [5]– [6].Despite the critical nature of this assessment, studies examining the relationship between ABT and Scr are sparse. Therefore, the objective of this study is to explore whether ABT benefits renal function in patients undergoing ATAAD surgery.
Materials and methods
Study population
From February 2020 through November 2022, our institution screened 227 individuals who underwent emergency surgery for aortic dissection (AD), ultimately enrolling 157 patients for surgery to treat ATAAD. The criteria for inclusion were as follows: (1) patients aged ≥ 18 years; (2) admission within 72 h of symptom onset; (3) a confirmed imaging-based diagnosis of Stanford-A aortic dissection (TAAD); (4) receipt of surgical treatment. The criteria for exclusion included: (1) Type B aortic dissection (TBAD); (2) subacute and chronic TAAD (≥ 72 h); (3) discharge with a tracheal catheter or unknown outcome; (4) mortality during surgery or within 24 h postoperatively; (5) exclusively interventional procedures; (6) presence of an aortic aneurysm. This retrospective analysis was conducted in accordance with the Declaration of Helsinki, received approval from the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (approval number: ES-2024-K152-01), and was exempt from the requirement for written informed consent due to its retrospective nature(Clinical trial number: not applicable).
Data source
This retrospective study collected data continuously from the electronic medical records of patients who underwent ATAAD surgery from February 2020 to November 2022 in the First Affiliated Hospital of Guangzhou Medical University. Preoperative variables included age, body mass index(BMI), systolic blood pressure (SBP), diastolic blood pressure(DBP), heart rate (HR), sex, and comorbidities such as hypertension, diabetes, cerebrovascular disease, chronic renal inefficiency (CRI), smoking history, renal artery compression, hyperlipidemia, liver dysfunction, and respiratory disorders. Intraoperative details encompassed cardiopulmonary bypass (CPB), intraoperative ventilation time (IVT), aortic arch replacement, temporary pacemaker implantation, ABT, red blood cell (RBC) transfusion, plasma, platelets, and total fluid infusion volume. Postoperative 24-hour outcomes included Scr, urea nitrogen (BUN), direct bilirubin (DB), and albumin (ALB).
Statistical analysis
All statistical evaluations were performed using the R software package provided by The R Foundation [7].Continuous variables are expressed as either means ± standard deviations for normally distributed data or as medians with interquartile ranges for data exhibiting skewness. Categorical variables are depicted as frequencies or percentages. To determine differences between groups, we applied one-way analysis of variance (ANOVA) for normally distributed data, Kruskal-Wallis H test for skewed data, and chi-square tests for categorical variables. We employed a univariate linear regression to explore the association between ABT and Scr. Further, multivariate analyses were conducted to probe deeper into the baseline interactions between ABT and Scr. In compliance with STROBE guidelines [8], models were developed in three tiers: unadjusted, minimally adjusted, and fully adjusted. Generalized additive models(GAM) were utilized for identifying non-linear associations, treating ABT as a continuous variable. Upon detecting non-linearity, a two-piecewise linear regression was implemented to investigate the threshold effects of ABT on Scr according to the smoothing plot. Recursive methods automatically pinpointed the inflection point where maximum model likelihood was achieved when a distinct ratio between ABT and Scr was visible in the smoothed curve [9].Results from logistic regression analyses are presented as regression coefficients(β) alongside 95% confidence intervals (CI). Subgroup analyses were conducted using stratified linear regression models, where adjustments and interactions were verified through likelihood ratio tests to ensure consistency across different demographic groups. A p-value of < 0.05 was considered statistically significant.
Results
Baseline characteristics
From February 2020 to November 2022, 227 patients underwent emergency AD surgery at our facility. After applying exclusion criteria, 70 patients were omitted from the study: 21 due to Type B AD, 15 for subacute and chronic TAAD lasting ≥ 72 h, 24 who were discharged with a tracheal catheter (outcome unknown), one who died during or within 24 h following surgery, three who underwent solely interventional procedures, and six diagnosed with aortic aneurysms. Consequently, 157 patients with ATAAD were included in the analysis, divided into 12 in the death group and 145 in the survival group (Fig. 1).
Fig. 1.
Flow chart of the study. AD = Aortic dissection. TBAD = Type B aortic dissection. TAAD = Stanford type A aortic dissection
Patients were grouped into death and survival categories (Table 1). Members of the death group were notably older (61.75 (12.19) vs. 52.53 (12.84), P = 0.018), with no significant variance in BMI, SBP, DBP, HR, or sex. The death group presented more preoperative comorbidities, including hypertension (n = 8), diabetes (n = 1), renal artery compression (n = 1), and respiratory disorders (n = 1). This group also experienced significantly longer durations of CPB and IVT compared to the survival group, though no significant differences were observed in rates of aortic arch replacement, temporary pacemaker insertion, ABT, RBC, plasma, platelet transfusions, or total fluid infusion volumes. Additionally, the death group displayed significantly higher levels of Scr, DB, and lower ALB compared to the survival group (Tables 2,3,4 and 5).
Table 1.
Baseline characteristics of participants
| Group | Death | Survival | P-value | P-value* |
|---|---|---|---|---|
| N | 12 | 145 | ||
| Baseline characteristics | ||||
| Age(years, mean(SD)) | 61.75 ± 12.19 | 52.53 ± 12.84 | 0.018 | 0.018 |
| BMI(kg/m2,mean (SD)) | 26.62 ± 4.16 | 25.55 ± 3.75 | 0.346 | 0.505 |
| SBP(mmHg, mean (SD)) | 128.67 ± 22.20 | 137.06 ± 31.24 | 0.364 | 0.325 |
| DBP(mmHg, mean (SD)) | 75.83 ± 9.68 | 76.50 ± 17.43 | 0.896 | 0.976 |
| HR(bpm, mean (SD)) | 80.58 ± 16.87 | 80.51 ± 13.87 | 0.986 | 0.583 |
| Sex(n,%) | 0.407 | - | ||
| Male | 8 (66.67%) | 112 (77.24%) | ||
| Female | 4 (33.33%) | 33 (22.76%) | ||
| Comorbidity n(%) | ||||
| Hypertension | 0.752 | - | ||
| No | 4 (33.33%) | 55 (37.93%) | ||
| Yes | 8 (66.67%) | 90 (62.07%) | ||
| Diabetes | 0.291 | 0.332 | ||
| No | 11 (91.67%) | 141 (97.24%) | ||
| Yes | 1 (8.33%) | 4 (2.76%) | ||
| Cerebrovascular disease | 0.347 | - | ||
| No | 12 (100.00%) | 135 (93.10%) | ||
| Yes | 0 (0.00%) | 10 (6.90%) | ||
| CRI | 0.513 | 1.000 | ||
| No | 12 (100.00%) | 140 (96.55%) | ||
| Yes | 0 (0.00%) | 5 (3.45%) | ||
| Smoking history | 0.682 | 1.000 | ||
| No | 12 (100.00%) | 143 (98.62%) | ||
| Yes | 0 (0.00%) | 2 (1.38%) | ||
| Renal artery compressed | 0.994 | - | ||
| No | 11 (91.67%) | 133 (91.72%) | ||
| Yes | 1 (8.33%) | 12 (8.28%) | ||
| Hyperlipidemia | 0.513 | 1.000 | ||
| No | 12 (100.00%) | 140 (96.55%) | ||
| Yes | 0 (0.00%) | 5 (3.45%) | ||
| Hepatic dysfunction | 0.682 | 1.000 | ||
| No | 12 (100.00%) | 143 (98.62%) | ||
| Yes | 0 (0.00%) | 2 (1.38%) | ||
| Respiratory disorders | 0.596 | 0.479 | ||
| No | 11 (91.67%) | 138 (95.17%) | ||
| Yes | 1 (8.33%) | 7 (4.83%) | ||
| Intraoperative details | ||||
| CPB time(min, mean (SD)) | 338.92 ± 113.99 | 269.45 ± 61.73 | < 0.001 | 0.006 |
| IVT(min, mean (SD)) | 651.00 ± 127.03 | 539.36 ± 106.41 | < 0.001 | 0.003 |
| Aortic arch replacement n(%) | 0.436 | 1.000 | ||
| No | 0 (0.00%) | 7 (4.83%) | ||
| Yes | 12 (100.00%) | 138 (95.17%) | ||
| Insertion of temporary pacemakers n(%) | 0.815 | - | ||
| No | 9 (75.00%) | 113 (77.93%) | ||
| Yes | 3 (25.00%) | 32 (22.07%) | ||
| ABT(ml, median (IQR)) | 0.00 (0.00–728.00) | 340.00 (0.00–582.00) | 0.861 | 0.669 |
| RBC(U, median (IQR)) | 3.00 (1.50–6.88) | 2.00 (1.50–4.50) | 0.394 | 0.598 |
| Plasma(ml, median (IQR)) | 700.00 (587.50–1200.00) | 600.00 (500.00–800.00) | 0.025 | 0.152 |
| Platelet(U, median (IQR)) | 1.50 (1.00–4.50) | 1.00 (0.00–2.00) | 0.284 | - |
|
Fluid infusion volume (ml, mean (SD)) |
1399.17 ± 594.99 | 1300.28 ± 564.99 | 0.562 | 0.497 |
| Postoperative 24-hour outcomes | ||||
| Scr(umol/L, mean (SD)) | 328.71 ± 153.22 | 214.02 ± 106.46 | < 0.001 | 0.006 |
| BUN(umol/L, median (IQR)) | 19.10 (12.07–37.58) | 15.80 (12.60–18.60) | < 0.001 | 0.153 |
| DB(umol/L, median (IQR)) | 22.95 (20.25–31.95) | 10.10 (4.90–16.00) | < 0.001 | < 0.001 |
| ALB(g/L, mean (SD)) | 34.38 ± 4.84 | 36.70 ± 4.33 | 0.080 | 0.047 |
Continuous variables that satisfy normal distribution are expressed by mean and standard deviation(SD), and continuous variables that do not satisfy normal distribution are expressed by median and quartile (IQR).Categorical variables are expressed by number and percentage (n(%)). BMI body mass index, SBP systolic blood pressure, DBP diastolic blood pressure, HR heart rate, CPB cardiopulmonary bypass, IVT Intraoperative ventilation time, ABT autologous blood transfusion, RBC red blood cell, CRI chronic renal inefficiency, Scr creatinine, BUN urea nitrogen, DB direct bilirubin, ALB albumin
Table 2.
The results of univariate regression analysis
| Postoperative 24-hour Scr | Statistics | β(95%CI), P value |
|---|---|---|
| Baseline characteristics | ||
| Age(years) | 53.24 ± 12.98 | −0.03 (−1.41, 1.36) 0.9695 |
| BMI(kg/m2) | 25.63 ± 3.78 | 4.59 (−0.11, 9.30) 0.0575 |
| SBP(mmHg) | 136.41 ± 30.66 | 0.15 (−0.44, 0.74) 0.6232 |
| DBP(mmHg) | 76.45 ± 16.95 | 0.49 (−0.57, 1.55) 0.3655 |
| HR(bpm) | 80.52 ± 14.06 | −0.72 (−2.00, 0.55) 0.2677 |
| Sex n(%) | ||
| Male | 120 (76.43%) | 0 |
| Female | 37 (23.57%) | −33.83 (−75.74, 8.07) 0.1156 |
| Comorbidity n(%) | ||
| Hypertension | ||
| No | 59 (37.58%) | 0 |
| Yes | 98 (62.42%) | 12.22 (−24.75, 49.19) 0.5179 |
| Diabetes | ||
| No | 152 (96.82%) | 0 |
| Yes | 5 (3.18%) | −47.95 (−149.77, 53.87) 0.3574 |
| Cerebrovascular disease | ||
| No | 147 (93.63%) | 0 |
| Yes | 10 (6.37%) | −24.26 (−97.57, 49.05) 0.5176 |
| CRI | ||
| No | 152 (96.82%) | 0 |
| Yes | 5 (3.18%) | 29.02 (−72.98, 131.02) 0.5779 |
| Smoking history | ||
| No | 155 (98.73%) | 0 |
| Yes | 2 (1.27%) | 8.63 (−151.24, 168.49) 0.9159 |
| Renal artery compressed | ||
| No | 144 (91.72%) | 0 |
| Yes | 13 (8.28%) | 43.99 (−20.70, 108.67) 0.1845 |
| Hyperlipidemia | ||
| No | 152 (96.82%) | 0 |
| Yes | 5 (3.18%) | −78.36 (−179.71, 22.99) 0.1317 |
| Hepatic dysfunction | ||
| No | 155 (98.73%) | 0 |
| Yes | 2 (1.27%) | 97.05 (−62.08, 256.19) 0.2338 |
| Respiratory disorders | ||
| No | 149 (94.90%) | 0 |
| Yes | 8 (5.10%) | −23.65 (−105.09, 57.79) 0.5700 |
| Intraoperative details | ||
| CPB time(min) | 274.76 ± 69.11 | 0.32 (0.06, 0.57) 0.0166 |
| IVT(min) | 547.89 ± 111.70 | 0.36 (0.21, 0.51) < 0.001 |
| Aortic arch replacement n(%) | ||
| No | 7 (4.46%) | 0 |
| Yes | 150 (95.54%) | 25.12 (−61.66, 111.89) 0.5713 |
| Insertion of temporary pacemakers n(%) | ||
| No | 122 (77.71%) | 0 |
| Yes | 35 (22.29%) | 17.38 (−25.61, 60.37) 0.4293 |
| ABT(ml) | 380.61 ± 413.13 | 0.04 (0.00, 0.09) 0.0424 |
| RBC(U) | 3.34 ± 2.95 | 3.28 (−2.79, 9.35) 0.2914 |
| Plasma(ml) | 673.60 ± 346.20 | 0.04 (−0.01, 0.09) 0.1536 |
| Platelet(U) | 6.90 ± 35.15 | −0.05 (−0.56, 0.47) 0.8591 |
| Fluid infusion volume(ml) | 1307.83 ± 565.97 | 0.02 (−0.01, 0.05) 0.2085 |
| Postoperative 24-hour outcomes | ||
| BUN(umol/L) | 22.95 ± 53.84 | −0.31 (−0.64, 0.02) 0.0662 |
| DB(umol/L) | 15.78 ± 15.56 | −0.62 (−1.77, 0.53) 0.2914 |
| ALB(g/L) | 36.52 ± 4.40 | −5.12 (−9.14, −1.11) 0.0133 |
Scr creatinine, BMI body mass index, SBP systolic blood pressure, DBP diastolic blood pressure, HR heart rate, CPB cardiopulmonary bypass, IVT Intraoperative ventilation time, RBC red blood cell, ABT autologous blood transfusion, CRI chronic renal inefficiency, BUN urea nitrogen, DB direct bilirubin, ALB albumin. β regression coefficient, CI confidence interval
Table 3.
Relationship between ABT and postoperative 24-hour Scr in different models
| Variable | Crude model (β, 95%CI, P) |
Minimally adjusted model (β, 95%CI, P) | Fully adjusted model (β, 95%CI, P) |
|---|---|---|---|
| ABT |
0.04 (0.00, 0.09) 0.042 |
0.04 (0.00, 0.09) 0.048 |
0.04 (0.00, 0.09) 0.049 |
| ABT(ml) | |||
| <100 | Ref | Ref | Ref |
| 100–480 | −21.12 (−63.80, 21.57) 0.334 | −19.06 (−61.77, 23.66) 0.383 | −15.43 (−58.42, 27.56) 0.483 |
| > 480 | 49.14 (6.46, 91.83) 0.025 | 49.09 (6.44, 91.74) 0.026 | 50.20 (7.48, 92.92) 0.023 |
| P for trend | 0.042 | 0.044 | 0.048 |
Crude model: we did not adjust other covariants
Minimally adjusted model: we adjusted age and sex
Fully adjusted model: we adjusted age, sex, hypertension, CRI, renal artery compressed, hyperlipidemia, CPB, ALB and IVT
CRI chronic renal inefficiency, CPB cardiopulmonary bypass, ALB albumin, IVT intraoperative ventilation time
β regression coefficient, CI: confidence interval, Ref: reference
Table 4.
The results of two-piecewise linear regression model
| Inflection point of autologous blood transfusion | Effect size (β) | 95%CI | P value |
|---|---|---|---|
| <814 | 0.07 | 0.00 to 0.13 | 0.041 |
| ≥814 | 0.01 | −0.08 to 0.10 | 0.879 |
Effect: Scr Cause: ABT Adjusted: age, sex, hypertension, CRI, renal artery compressed, hyperlipidemia, CPB, ALB and IVT
CRI chronic renal inefficiency, CPB cardiopulmonary bypass, ALB albumin, IVT intraoperative ventilation time
Table 5.
Effect size of ABT on postoperative 24-hour Scr in prespecified and exploratory subgroups
| Characteristic | No of participants |
Effect size(95%CI) |
P for interaction |
|---|---|---|---|
| Age(years) | |||
| <47 | 50 | 0.11 (0.03, 0.20) | 0.01 |
| ≥47 | 107 | 0.02 (−0.03, 0.07) | 0.41 |
| Sex | |||
| Male | 120 | 0.05 (−0.00, 0.10) | 0.06 |
| Female | 37 | 0.03 (−0.06, 0.12) | 0.52 |
| Hypertension | |||
| No | 59 | 0.07 (0.00, 0.13) | 0.05 |
| Yes | 98 | 0.03 (−0.03, 0.09) | 0.32 |
| CRI | 0.05 | ||
| No | 152 | 0.04(0.00, 0.09) | |
| Yes | 5 | ||
| Hyperlipidemia | 0.05 | ||
| No | 152 | 0.04 (0.00, 0.09) | |
| Yes | 5 | ||
| Renal artery compressed | |||
| No | 144 | 0.05 (0.00, 0.10) | 0.03 |
| Yes | 13 | −0.02 (−0.13, 0.08) | 0.65 |
| CPB time group(min) | |||
| 145–242 | 52 | 0.01 (−0.06, 0.08) | 0.70 |
| 243–286 | 51 | 0.02 (−0.08, 0.12) | 0.73 |
| 288–646 | 54 | 0.06 (−0.01, 0.12) | 0.10 |
| Postoperative 24-hour ALB(g/L) | |||
| <34.4 | 51 | 0.00 (−0.06, 0.06) | 0.99 |
| 34.4–37.7 | 53 | 0.06 (−0.03, 0.15) | 0.23 |
| > 37.7 | 53 | 0.14 (0.05, 0.23) | < 0.01 |
| IVT(min) | |||
| < 480 | 51 | −0.06 (−0.16, 0.03) | 0.20 |
| 485–565 | 49 | 0.09 (−0.00, 0.19) | 0.06 |
| >565 | 57 | 0.01 (−0.05, 0.07) | 0.71 |
CRI chronic renal inefficiency, CPB cardiopulmonary bypass, ALB albumin, IVT intraoperative ventilation time
Note: Above model adjusted for age,sex,hypertension,CRI,renal artery compressed, hyperlipidemia,CPB,ALB and IVT
Univariate regression analysis
The univariate regression analysis revealed positive correlations between CPB time, IVT, and ABT with Scr. Factors such as age, BMI, SBP, DBP, HR, sex, and preoperative comorbid conditions (including hypertension, diabetes, cerebrovascular disease, CRI, smoking history, renal artery compression, hyperlipidemia, liver dysfunction, and respiratory disorders), along with intraoperative details (such as aortic arch replacement, temporary pacemaker insertion, RBC, plasma, platelet, and total fluid infusion volumes), BUN, and DB did not demonstrate associations with Scr. In contrast, ALB was inversely related to Scr levels (Supplementary Table 2).
Multivariate regression analysis
Multivariate regression was applied to explore the relationships between ABT and Scr. The findings, detailed in Supplementary Table 3, include both non-adjusted and adjusted models. The initial, crude model revealed a noteworthy correlation between ABT and Scr (β = 0.04, 95% CI: 0 to 0.09, P = 0.042). This correlation persisted in the minimally adjusted model, which accounted for age and sex (β = 0.04, 95% CI: 0 to 0.09, P = 0.048), and was consistent in the fully adjusted model (β = 0.04, 95% CI: 0 to 0.09, P = 0.049). For a more nuanced analysis, ABT was segmented into tertiles for sensitivity analysis, which confirmed the trend (P for trend = 0.048).
Analysis of non-linear relationship
Our analysis uncovered a non-linear relationship between ABT and Scr, controlled for variables including age, sex, hypertension, chronic renal insufficiency (CRI), renal artery compression, hyperlipidemia, CPB, ALB, and IVT. Employing a two-piece linear regression model, the inflection point was identified at 814. On the left of this point, a positive association was noted (β = 0.07, 95% CI: 0 to 0.13, P = 0.041) (Supplementary Table 4). The stratified fit curve (Fig. 2), distinctly displays an escalation in Scr with increments in ABT. Conversely, on the right side of the inflection point, the effect size, 95% CI, and P value were 0.01, −0.08 to 0.10, and 0.879, respectively.
Fig. 2.
Non-linear relationship between ABT and Scr. A nonlinear relationship was observed between these variables after adjusting for age, sex, hypertension, CRI, renal artery compression, hyperlipidemia, CPB, ALB, and IVT. The blue dashed line depicts the fitted curve, while the solid red line indicates the 95% CI ABT autologous blood transfusion, Scr serum creatinine, CRI chronic renal inefficiency, CPB cardiopulmonary bypass, ALB albumin, IVT intraoperative ventilation time
Subgroup analysis results
Subgroup analysis revealed significant interactions impacting the relationship between ABT and Scr for age, renal artery compression, and ALB (P for interaction = 0.01, 0.03, and 0.003), while interactions for sex, hypertension, CRI, hyperlipidemia, CPB, and IVT were not statistically significant (P values for interactions > 0.05). ABT showed a positive association with Scr in patients younger than 47 years (β = 0.11, 95% CI: 0.03 to 0.20), those with ALB greater than 37.7 g/L (β = 0.14, 95% CI: 0.05 to 0.23), and in individuals without renal artery compression (β = 0.05, 95% CI: 0 to 0.10) (Supplementary Table 5).
Discussion
ATAAD surgeries are high-risk emergency procedures with significant mortality and severe potential complications [10]– [11].Lee TC et al. [12].highlighted that over 90% of ATAAD patients received varying quantities of blood products, as indicated by a recent study from the Society of Thoracic Surgeons (STS) Database. Over the last five years, our center has increasingly implemented ABT during such emergencies, proven to considerably decrease the need for intraoperative blood transfusions [13].However, the impact of ABT on patient mortality, organ functionality, or neurological outcomes in cardiac surgeries remains unclear from existing literature [14].Scr is a recognized metric for assessing renal function; however, the relationship between ABT and postoperative 24-hour Scr levels has been minimally investigated. Our research is designed to elucidate this connection, aiming to refine blood conservation strategies in ATAAD surgical practices.
Previous studies have identified age as an independent predictor of mortality among ATAAD patients [15], with older patients especially susceptible to postoperative deaths from complications like visceral malperfusion and organ ischemia, which are often intensified by severe root-level AD [16]. Moreover, the increased Scr levels observed in the mortality group could predominantly be linked to extensive renal artery involvement. Aligning with our observations, individuals in the mortality group who exhibited higher Scr levels also underwent longer periods of CPB and IVT. According to 2021 The American Association for Thoracic Surgery expert consensus document: Surgical treatment of acute type A aortic dissection [17], the surgical approaches utilized for emergency patients encompassed ascending aortic replacement, modified aortic arch replacement, and the stent - elephant trunk implantation in this study. In surgery, the thoracic cavity is opened via median sternotomy to expose the heart and ascending aorta, and the damaged aorta segment is fully removed and replaced with a prosthetic graft. As Table 1 shows, there’s no significant difference in aortic arch replacement rates between the two groups. Thus, it can be inferred that complex surgeries involving large aortic or arch dissections may lead to longer CPB and IVT times, which involves resecting more diseased vessel segments, implanting more complex artificial vascular structures, or needing extra surgical time due to anatomical complexity [18].Remarkably, our analysis detected significantly elevated postoperative 24-hour DB and reduced ALB levels in the mortality group, likely consequences of severe preoperative dissections affecting the celiac trunk and mesenteric artery branches, leading to malperfusion and subsequent hepatic damage or ischemia, thereby increasing DB levels [16, 19].Additionally, research by Gao Y et al. [20]. supports that diminished ALB levels correlate with heightened postoperative in-hospital mortality for both type A and B AAD, potentially due to systemic inflammation, thrombosis, and oxidative stress-factors known to predict long-term mortality in cardiovascular conditions.
Scr, indicative of inadequate organ perfusion, reflects the severity of ATAAD [4].Our univariate regression analysis revealed that CPB time and IVT were positively correlated with postoperative 24-hour Scr, suggesting that patients with more extensive dissection requiring longer surgeries tend to have higher Scr levels. Additionally, ALB levels decreased significantly as Scr levels increased, confirming that lower ALB is associated with inflammation severity following AD rupture [20]– [21].Our findings also indicated that higher doses of ABT were correlated with increased Scr levels. We hypothesize that ABT may affect Scr due to reduced deformability and shortened lifespan of red blood cells during the autologous blood recovery process or due to cell destruction caused by excessive negative pressure, ultimately leading to kidney damage and increased Scr levels [22]– [23].
In addition, subgroup analyses are pivotal in scientific study [8].This research employed variables such as age, gender, hypertension, chronic renal insufficiency, renal artery compression, hyperlipidemia, CPB duration, postoperative 24-hour ALB, and IVT for stratification. It was noted that the impacts of ABT on Scr varied markedly among different age groups. Existing literature suggests that surgical risks and postoperative challenges, such as renal insufficiency, escalate with age in patients suffering from acute type A aortic dissection [24].Contrarily, significant age disparities (below 47 years) were evident between the groups receiving ABT and those monitored for Scr, indicating that the influence of ABT on Scr post-surgery might overshadow the effects attributable to age differences. Additionally, interaction tests for ALB levels exceeding 37.7 g/L were significant, irrespective of age. We propose that elevated ALB could intensify the burden on renal filtration or excretion and chronic inflammation, potentially deteriorating renal function and heightening postoperative Scr. Continued investigations are required to verify and elucidate the implications of high ALB on renal health [25].Given that previous studies did not report similar results, it is unclear why a linearly increasing trend between ABT and Scr occurred in patients without renal artery compression. Notably, prolonged CPB and IVT have been pinpointed as risk enhancers for Scr elevation in univariate regression analyses; however, interactions between CPB time, ventilation durations, and Scr were non-existent, it may suggest that CPB time and IVT could affect early postoperative Scr levels through alternative mechanisms.
Our findings indicate that the postoperative 24-hour Scr levels remained unchanged across observed ABT volumes between 100 and 400 ml, suggesting minimal impact of ABT within this range on early postoperative Scr levels. These results align with those reported by Kalra et al. [26].However, Scr levels tended to increase incrementally with ABT volumes exceeding 480 ml, while another analysis demonstrated a positive correlation between Scr and ABT when ABT was under 814 ml. Thus, we cannot dismiss the possibility that the dosage of ABT might affect renal function. Probing into the underlying causes, central to the effect of ABT on Scr may be the renal toxicity mechanism mediated by free hemoglobin (FHb) overload, which is caused by red cell destruction during high-speed centrifugation and washing of the recovery of autologous blood [27].In autologous blood transfusion, FHb-derived reactive oxygen species(ROS) induce oxidative stress in renal tubular cells, consume endothelial nitric oxide(NO), and constrict renal vessels. This effect is especially evident during ischemia-reperfusion, leading to Scr variations. And beyond that, Honglan Wang et al. [28]showed that the attention should be paid to renal function in patients receiving autologous blood transfusion of more than 600 ml.This also may imply that there is a dose - dependent association between the the volume of ABT and Scr. In light of the above, it highlights the need for caution regarding ABT’s safety on renal function during surgery, particularly within a volume range of 480–814 ml. Emphasizing effective blood conservation strategies such as ABT therapy, combined with intraoperative and postoperative blood transfusions, and reinforcing renal protection to prevent early postoperative Scr elevation are both crucial and challenging.
The study has inherent limitations, being a single-center trial with a limited number of participants undergoing ATAAD surgery in China. The applicability of these results to other demographic groups warrants additional exploration. Furthermore, initial diagnoses often occurred in local hospitals, complicating the acquisition of accurate data concerning false lumen thrombosis. Consequently, the potential impact of unreported false lumen thrombosis effects on postoperative Scr levels in ATAAD surgical patients is yet to be clarified.
Conclusion
The relationship between ABT and Scr in patients undergoing ATAAD surgery is non-linear. Scr was positively correlated with ABT volumes up to 814 ml. However, this correlation dissipated when ABT exceeded 814 ml. A similar trend was observed in patients under 47 years of age and those with ALB levels exceeding 37.7 g/L. These findings suggest that ABT dosage may impact renal function in ATAAD surgery patients, necessitating further research to clarify the underlying mechanisms. Additionally, these insights provide a basis for refining blood conservation strategies during ATAAD surgical procedures.
Supplementary Information
Acknowledgements
Not applicable.
Authors’ contributions
Zhaomin Huang and Jiayang Li conceived of the study, Yanping Wang and Zhibin Chen participated in its analysis and interpretation of data.All authors helped to draft the manuscript, read and revised the final manuscript.
Funding
Not applicable.
Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
This study was performed in line with the principles of the Declaration of Helsinki.Approval was granted by the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (Approval Number: ES-2024-K152-01). Informed consent was waived by the First Affiliated Hospital of Guangzhou Medical University due to its retrospective nature.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Jiayang Li and Yanping Wang contributed equally as co-first authors.
References
- 1.Yubin C, Kaiyi D, Cheng F, et al. The predictive values of monocyte- lymphocyte ratio in postoperative acute kidney injury and prognosis of patients with Stanford type A aortic dissection. Front Immunol. 2019;24:1195421. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Malaisrie SC, Szeto WY, Halas M, et al. The American association for thoracic surgery expert consensus document:surgical treatment of acute type A aortic dissection. J Thorac Cardiovasc Surg. 2021;16:735–58. [DOI] [PubMed] [Google Scholar]
- 3.Wang W, Duan W, Xue Y, et al. Clinical features of acute aortic dissection from the Registry of Aortic Dissection in China. J Thorac Cardiovasc Surg. 2014;148:2995–3000. [DOI] [PubMed] [Google Scholar]
- 4.Wu ZN, Guan XL, Xu SJ, et al. Does preoperative serum creatinine affect the early surgical outcomes of acute Stanford type A aortic dissection?J. Chin Med Assoc. 2020;83:266–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Wei S, Wei X, Zhaozhuo N, et al. Incidence of acute kidney injury and risk factors of prognosis in patients with acute Stanford type A aortic dissection. Ann Thorac Cardiovasc Surg. 2023;29:249–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Mauro P. Enzymatic assays for creatinine: time for action. Scand J Clin Lab Invest. 2008;68:84–8. [DOI] [PubMed] [Google Scholar]
- 7.Guillermo D, Constanza R, Dali S, et al. Deep learning models for tendinopathy detection: a systematic review and meta-analysis of diagnostic tests. EFORT Open Rev. 2024;9:941–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Yokoyama M, Watanabe T, Otaki Y, et al. Association of the aspartate aminotransferase to alanine aminotransferaseratio with BNP level and cardiovascular mortality in the general population:the Yamagata study 10-year follow-up. Dis Markers. 2016;2016:4857917. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Kernan WN, Viscoli CM, Brass LM, et al. Phenylpropanolamine and the risk of hemorrhagic stroke. N Engl J Med. 2000;343:1826–32. [DOI] [PubMed] [Google Scholar]
- 10.Di Bartolomeo R, Pantaleo A, Berretta P, et al. Frozen elephant trunk surgery in acute aortic dissection. J Thorac Cardiovasc Surg. 2015;149:105–9. [DOI] [PubMed] [Google Scholar]
- 11.Elizabeth LN, Karen MK, Shinichi F, et al. Autologous blood transfusion in acute type A aortic dissection decreased blood product consumption and improved postoperative outcomes. JTCVS Open. 2022;20:20–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Lee TC, Kon Z, Cheema FH, et al. Contemporary management and outcomes of acute type A aortic dissection: an analysis of the STS adult cardiac surgery database. J Card Surg. 2018;33:7–18. [DOI] [PubMed] [Google Scholar]
- 13.Zimmermann E, Zhu R, Ogami T, et al. Intraoperative autologous blood donation leads to fewer transfusions in cardiac surgery. Ann Thorac Surg. 2019;108:1738–44. [DOI] [PubMed] [Google Scholar]
- 14.Martin J, Wang G, Bainbridge D, et al. The efficacy of an intraoperative cell saver during cardiac surgery: A meta-analysis of randomized trials. Anesth Analg. 2009;109:320–30. [DOI] [PubMed] [Google Scholar]
- 15.You KP. Jae HL,Kang MK,et al.Acute type A aortic dissection features and outcomes in octogenarians: a propensity score analysis. Interdisciplinary Cardiovasc Thorac Surg. 2024;38:ivae038. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Immer FF, Grobéty V, Lauten A, et al. Does malperfusion syndrome affect early and mid-term outcome in patients suffering from acute type A aortic dissection? Interact Cardiovasc Thorac Surg. 2006;5:187–90. [DOI] [PubMed] [Google Scholar]
- 17.Christopher Malaisrie,Wilson S, Szeto,Monika Y, Halas et al. 2021 The American Association for Thoracic Surgery expert consensus document: Surgical treatment of acute type A aortic dissection.J Thorac Cardiovasc Surg. 2021,162(3):735–758. [DOI] [PubMed]
- 18.Mikko Uimonen C, Olsson A, Jeppsson, et al. Cardiopulmonary bypass time during surgery for acute type A aortic dissection and Mid-Term survival. J Cardiovasc Dev Dis. 2025;12(4):139. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Xu HD, Lang ZB, Zhao L, et al. Analysis of risk factors for perioperative hyperbilirubinemia in Stanford type A aortic dissection. Chin J Thorac Cardiovasc Surg. 2018;34:650–54. [Google Scholar]
- 20.Gao Y, Li D, Cao Y, et al. Prognostic value of serum albümin for patients with acute aortic dissection: a retrospective cohort study. Medicine(Baltimore). 2019;98:e14486. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Cifani N, Proietta M, Tritapepe L, et al. Stanford-A acute aortic dissection, inflammation, and metalloproteinases: a review. Ann Med. 2015;47:441–6. [DOI] [PubMed] [Google Scholar]
- 22.Schneider SO, Rensing H, Hartmann L, et al. Impact of intraoperatively salvaged and washed blood on stimulated cytokine release in vitro. Transfusion. 2014;54:2782–90. [DOI] [PubMed] [Google Scholar]
- 23.Gueye PM, Bertrand F, Duportail G, et al. Extracellular haemoglobin, oxidative stress and quality of red blood cells relative to perioperative blood salvage. Clin Chem Lab Med. 2010;48:677–83. [DOI] [PubMed] [Google Scholar]
- 24.Rylski B, Hoffmann I, Beyersdorf F, et al. Multicenter prospective observational Study. acute aortic dissection type A: age-related management and outcomes reported in the German registry for acute aortic dissection type A (GERAADA) of over 2000 patients. Ann Surg. 2014;259:598–604. [DOI] [PubMed] [Google Scholar]
- 25.Yusuke O, Yoshitsugu O, Elani S, et al. Serum albumin and hospitalization among pediatric patients with end-stage renal disease who started Dialysis therapy. Pediatr Nephrol. 2019;34:1799–809. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Kalra M, Beech J, Al-Khaffaf M. Autotransfusion in aortic surgery: the haemocell system 350 cell saver. Br J Surg. 1993;80:32–5. [DOI] [PubMed] [Google Scholar]
- 27.Kerchberger VE, Ware LB. The role of circulating cell-free hemoglobin in sepsis-associated acute kidney injury. Semin Nephrol. 2020;40:148–59. https://doi.org/10.1016/j.semnephrol.2020.01.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Wang Honglan, Zhang Meixin, Gu Yu, et al. The effects of transfusion load on renal function in intraoperative salvage autotransfusion: a retrospective cohort study for 200 patients. Front Physiol. 2025;16:1640701. 10.3389/fphys.2025.1640701. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.