This retrospective cohort analysis enrolled 363 patients diagnosed with ATAAD complicated by extensive aortic arch pathology who underwent emergency type Ⅱ hybrid aortic arch repair (HAR) at a single center between January 2021 and February 2024. Eligibility criteria for inclusion comprised the following: (1) Age > 18 years; (2) diagnosis of ATAAD confirmed by computed tomography angiography (CTA) with extensive aortic arch pathology; and (3) performance of emergency surgical intervention within 14 days of symptom onset. The exclusion criteria were: (1) Chronic aortic dissection or surgery > 14 days after symptom onset; (2) Death within 24 h after surgery; (3) Iatrogenic or traumatic aortic dissection; (4) Severe organ dysfunction (e.g., hepatic or renal failure); (5) Diseases affecting initial blood cell counts or in-hospital mortality (e.g., malignancies, hematological diseases, infectious diseases); (6) Use of drugs affecting complete blood count (CBC) parameters; (7) Data of incomplete cases. This retrospective study was approved by the Ethics Committee of The First Affiliated Hospital of Soochow University (IRB No. 2025392) with a waiver of informed consent and conducted in accordance with the Declaration of Helsinki (2013 revision).

The clinical data of the enrolled patients were retrieved from the electronic medical record system, including demographic details (age, sex, etc), admission blood pressure, preoperative comorbid conditions (hypertension, diabetes, coronary heart disease, etc.), time from symptom onset to admission. Imaging findings (aortic valve regurgitation, pericardial and pleural effusions, etc) and preoperative laboratory tests were also recorded. Intraoperative details such as total operative time, cardiopulmonary bypass (CPB) duration, aortic cross-clamp time, and surgical technique were documented. Postoperative data comprised intensive care unit (ICU) stay time, mechanical ventilation time, and the occurrence of postoperative complications. CBC parameters were obtained within 1 h of hospital admission using automated hematology analyzers. Other biochemical markers were measured within 24 h of admission. A follow-up was conducted to document all-cause mortality.

Malperfusion Syndrome (MPS) was identified in patients with reduced perfusion or complete arterial obstruction as evidenced by preoperative CTA, in combination with clinical manifestations such as coma, limb paralysis, or abdominal pain, or supported by elevated cardiac enzyme levels. Preoperative hypotension was defined as a systolic blood pressure <.90 mmHg. Severe AKI was defined as AKI stage III per Kidney Disease: Improving Global Outcomes (KDIGO) criteria (25): serum creatinine (SCr) ≥ 3 times baseline or ≥ 4.0 mg/dL (353.6 μmol/L), or initiation of continuous renal replacement therapy (CRRT) within 1 week postoperatively. Postoperative acute respiratory distress syndrome (ARDS) was diagnosed by a PaO2/FiO2 ratio ≤ 200 mmHg within 24 h after surgery. Mechanical ventilation time was the total duration of tracheal intubation-assisted ventilation.

The primary endpoint of this study was the onset of PAEs during hospitalization, while secondary endpoints included short- and mid-term all-cause deaths. As per the consensus statement issued by the International Aortic Arch Surgery Study Group regarding the grading of complications after aortic arch surgery (26), PAEs were recognized as clinical events corresponding to grade III or higher complications. In this study, PAEs included: (1) CVD complications [malignant arrhythmias, myocardial ischemia, and heart failure needed support with intra-aortic balloon pump (IABP) or extracorporeal membrane oxygenation (ECMO)], (2) respiratory complications (ARDS, reintubation, tracheostomy), (3) new-onset severe AKI, (4) gastrointestinal hemorrhage, (5) wound-related problems needed reoperation for hemostasis or additional surgical therapeutics, (6) death after surgery.

Under general anesthesia, emergency one-stage total arch replacement using the type Ⅱ HAR technique was performed through a standard median sternotomy. Femoral arterial cannulation was employed to establish CPB in all patients, with venous drainage via a right atrial two-stage cannula. Our cerebral protection strategy included temperature management, cerebral oximetry, and intraoperative transcranial Doppler (TCD) monitoring. Based on TCD findings, particularly for patients with dissection involving the arch vessels, an additional arterial cannula was selectively placed in the right axillary artery to create a dual-arterial cannulation strategy, ensuring adequate cerebral perfusion. The ascending aorta was replaced by an anastomosing four-branched prosthetic graft to the sinotubular junction. The aortic arch was transected just proximal to the origin of the innominate artery, and the distal end of the prosthesis was sutured in an end-to-end manner to the distal aortic arch. Further sequential anastomosis of the graft branches to the left common carotid artery, left subclavian artery, and innominate artery was performed. Endovascular stent grafting was completed by advancing the endograft retrogradely through the femoral artery access site. The proximal portion of the endograft was anchored to the distal segment of the prosthetic graft, thus completing the arch reconstruction. Surgical management of the aortic root included procedures such as the Bentall procedure, David procedure, Wheat procedure, isolated ascending aortic replacement, or a combination with coronary artery bypass grafting (CABG) and/or other concomitant cardiac valve procedures. Postoperatively, patients were transferred to the ICU for monitoring until clinical stabilization.

Statistical analysis was statistically quantified via SPSS v25.0 and R software v4.3.3. Continuous data are presented as mean ± SD (normally distributed) or median (IQR) (non-normally distributed), compared using Student's t-test or Mann–Whitney U-test, respectively. Categorical variables are summarized as percentages and analyzed by χ² test. Patients were stratified into low and high PWR groups based on the median value to ensure balanced group sizes. Receiver operating characteristic (ROC) curve analysis was initially used to examine the discriminative ability of PWR in predicting PAEs among patients with ATAAD. The association between the PWR and PAEs was evaluated using a series of multivariable logistic regression models. A stepwise selection algorithm based on the Akaike Information Criterion (AIC) was employed to optimize model parsimony and performance. To avoid multicollinearity, variables with a variance inflation factor (VIF) ≥ 5 were excluded. The modeling strategy comprised a crude (unadjusted) model, followed by sequentially adjusted models: Model 1 (demographics and comorbidities: age, sex, BMI, hypertension, diabetes); Model 2 (Model 1 + clinical and operative factors: preoperative hypotension, MPS, operative time, CPB duration); and Model 3 (Model 2 + laboratory markers: hemoglobin, AST, SCr, D-dimer). Subgroup analyses (age, sex, BMI, hypertension, time from symptom onset to admission, AST, SCr, D-dimer and CPB duration) assessed effect modification, testing interactions for significance. Kaplan–Meier survival analysis was employed to construct survival curves, with comparative analysis between groups using the log-rank test. The association between PWR and short- and mid-term postoperative mortality was further evaluated using Cox proportional hazards regression analysis. A value of p < 0.05 was considered to be statistically significant.

Approximately 426 patients diagnosed between January 2021 and February 2024 were initially assessed for eligibility. Exclusion criteria were applied to 17 patients with chronic aortic dissection, four individuals died within 24 h postoperatively, three cases involving iatrogenic or traumatic aortic dissection, ten patients presenting with severe organ dysfunction, three patients with conditions affecting baseline hematological parameters or associated with in-hospital mortality, five cases with the use of drugs affecting CBC values, and 21 patients with incomplete clinical records. After these exclusions, 363 patients were ultimately enrolled in the analysis (Figure 1). Of these, 312 were men (85.95%) and 51 were women (14.05%). The median age was 50 years, and hypertension emerged as the most prevalent comorbidity (68.87%).

All patients were assigned to two groups as per the median PWR: the low PWR group (<13.259, n = 181) and the high PWR group (≥ 13.259, n = 182). As shown in Table 1. Patients in the Low PWR group had higher proportions of preoperative hypotension and MPS, and had a significantly shorter time from symptom onset to admission. The WBC, hemoglobin, ALT, AST, SCr, PT, Fibrinogen, D-dimer, Hs-cTn, and Myoglobin levels were remarkably higher in the low PWR group, while the PLT and CRP level between the two groups was the opposite, and the difference was statistically significant.

As shown in Table 2, Patients with ATAAD in the low PWR group had significantly higher rates of PAEs than the high PWR group (41.99% vs. 21.43%; p < 0.001), particularly ARDS, severe AKI, CRRT requirement, and spinal cord injury. Moreover, the duration of mechanical ventilation was significantly prolonged in the low PWR cohort (median 44.40 vs. 37.20 h, p < 0.001). No statistically significant variations were found between both groups in the case of the incidence of postoperative myocardial ischemia, ventricular arrhythmia, use of IABP or ECMO, secondary endotracheal intubation, tracheostomy, cerebrovascular accident, gastrointestinal hemorrhage, septic shock, or extended ICU stay (all p ≥ 0.05).

Univariate logistic regression analysis identified preoperative PWR as an effective predictor of PAEs in patients with ATAAD (OR: 2.65, 95%CI: 1.67–4.21, p < 0.001). To further explore this association, multivariate logistic regression models were adjusted for potential confounding variables (Table 3). After this adjustment, low preoperative PWR remained independently associated with an increased risk of PAEs. In Model 1, the OR was 2.98 (95% CI: 1.83–4.84, p < 0.001); in Model 2, the OR was 2.55 (95% CI: 1.51–4.30, p < 0.001); and in Model 3, the OR was 2.20 (95% CI: 1.24–3.91, p = 0.007).

To explore whether the link between PWR and the risk of PAEs varied across clinical subgroups, stratified analyses were carried out by age, sex, BMI, hypertension status, time from symptom onset to admission, AST, SCr, D-dimer levels, and CPB duration (Figure 2), and no statistically significant interactions were identified among the subgroups (all p > 0.05).

To evaluate the prognostic utility of the PWR, ROC curve analysis was compared with commonly used clinical markers of inflammatory activity (WBC, CRP) and coagulation status (PLT, D-dimer). Among these indicators, PWR demonstrated higher predictive performance for PAEs. The areas under the curve (AUC) for PWR was 0.705 (95% CI: 0.649–0.760), suggesting moderate discriminative ability (Figure 3).

The 1-year follow-up achieved a complete survival data acquisition rate of 100%. Patients classified in the low PWR group demonstrated markedly elevated rates of in-hospital mortality (13.81% vs. 3.30%, p = 0.001), 90-day mortality (14.36% vs. 4.40%, p < 0.001), and all-cause mortality at one year (16.38% vs. 5.56%, p = 0.001) in comparison to individuals in the higher PWR group.

Similarly, K-M survival analyses revealed significant differences in overall survival probabilities between the low and high PWR groups across all evaluated endpoints. As depicted in Figures 4A–C, the low PWR group showed considerably higher risks of hospitalized (p < 0.001), 90-day (p < 0.001), and 1-year (p = 0.001) deaths.

To further examine the link between PWR and early to mid-term mortality, Cox proportional hazards regression models were applied, as summarized in Table 4. In comparison to the high PWR group, patients in the low PWR group showed significantly elevated hazard ratios (HR) across all mortality endpoints. For in-hospital mortality, the crude model reported an HR of 4.24 (95% CI: 1.74–10.34, p = 0.002), whereas the fully adjusted model indicated an HR of 4.02 (95% CI: 1.54–10.45, p = 0.004). Analogous associations were detected for 90-day and 1-year mortality outcomes, thus highlighting the prognostic relevance of low preoperative PWR as a distinct predictor of short- and mid-term mortality in ATAAD patients.

Firstly, the calculation of the PWR relies solely on parameters derived from standard complete blood count tests, eliminating the need for specialized equipment and enhancing applicability in resource-limited settings. Secondly, this study found that PWR is primarily associated with PAEs, such as ARDS, severe AKI, CRRT requirement, and spinal cord injury, further analysis can be conducted to explore the predictive role of PWR in these complications. Particularly, the subgroup analysis confirmed that reduced PWR consistently predicted the incidence of PAEs across all predefined strata (age, sex, BMI, time from symptom onset to admission, hepatic and renal function, CPB duration; p > 0.05 for interaction). This indicates that the prognostic value of low PWR reflects an inherent pathophysiological state, independent of surgical complexity or baseline organ function.

Despite providing compelling evidence for the association between the PWR and surgical outcomes in ATAAD patients, this study has limitations. First, its retrospective, single-center design risks selection bias and limits generalizability, while residual confounding may persist despite adjusted models. Second, the modest sample size reduced power to detect associations with rare complications or conduct thorough subgroup analyses. Third, the absence of longitudinal PWR data precludes assessment of dynamic fluctuations and their prognostic relevance. Fourth, due to the relatively short follow-up period and the inherent challenges in retrospectively capturing complete rehospitalization information, we were unable to perform a competing risk analysis using the Cumulative Incidence Function (CIF) to evaluate rehospitalization with death as a competing risk. Future multicenter prospective studies with larger cohorts and longer follow-up are needed to validate these findings. Comprehensive research should also focus on exploring the role of PWR in clinical staging (e.g., preoperative diagnosis) and its underlying molecular mechanisms, while incorporating systematic rehospitalization data and advanced methods like CIF to definitively establish its prognostic utility for long-term outcomes.