Abstract
Background
Partial hepatectomy (PH) may increase the risk of myocardial injury after non-cardiac surgery (MINS), a complication associated with substantial perioperative morbidity and mortality. Direct comparisons of MINS incidence between PH and other major abdominal surgeries (MAS) remain limited. This study evaluated whether PH confers greater risk of postoperative MINS compared with other MAS.
Methods
We conducted a retrospective propensity score-matched cohort study using the INSPIRE database. Adult patients undergoing PH or other MAS between 2011 and 2020 were identified. After 1:2 propensity score matching to minimize confounding, 163 PH patients were compared with 267 matched controls. The primary outcome was MINS incidence. Secondary outcomes included myocardial infarction, heart failure, in-hospital mortality, ICU admission, and hospital length of stay.
Results
Following propensity matching, PH patients exhibited significantly higher MINS incidence than controls (44.2% vs. 34.5%; OR = 1.51, 95% CI: 1.01–2.24, P = 0.044). This association was particularly marked in overweight patients, among whom MINS occurred in more than half of PH cases versus approximately one-quarter of controls (52.3% vs. 26.9%; OR = 2.97, 95% CI: 1.37–6.45, P = 0.006). No significant differences emerged in myocardial infarction, heart failure, in-hospital mortality, ICU admission, or hospital length of stay between groups.
Conclusion
Partial hepatectomy is associated with significantly increased risk of postoperative myocardial injury compared with other major abdominal procedures, particularly among overweight patients.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12876-025-04495-6.
Keywords: Partial hepatectomy, Myocardial injury after non-cardiac surgery, Propensity score matching
Introduction
Partial hepatectomy (PH) is an important surgical procedure for treating primary and metastatic liver cancer, with perioperative mortality rates significantly reduced to 3%−5% [1, 2]. However, postoperative cardiovascular complications remain one of the major factors affecting long-term patient prognosis, among which myocardial injury after non-cardiac surgery (MINS) is the most common [3, 4]. The incidence of MINS in major abdominal surgeries(MAS) is approximately 8%−19%, and is significantly associated with all-cause mortality within 30 days after surgery [4–7]. Therefore, identifying high-risk populations for MINS and understanding its potential mechanisms are crucial for optimizing perioperative management [8].
PH involves complex physiological changes that may trigger systemic inflammatory responses and oxidative stress [9–11], which affects the prognosis of various clinical conditions. Previous studies have suggested that major surgical procedures may impact remote organs through multiple mechanisms, such as coronary microcirculation dysfunction, myocardial cell metabolic disorders, and autonomic nervous system imbalance [12–14]. Subgroup analysis revealed that this risk was particularly significant in overweight patients. Although basic research has revealed the potential damaging effects of ischemia-reperfusion injury (IRI) on the myocardium at molecular and cellular levels, there is currently a lack of clinical studies directly comparing the impact of PH versus other MAS on the incidence of MINS.
Furthermore, individual patient characteristics (such as obesity) and surgical approaches may further modulate the impact of PH on the myocardium [15, 16]. The chronic low-grade inflammatory state in obese patients may exacerbate the systemic effects of PH, while open surgery may further aggravate the remote myocardial injury from PH by increasing intraoperative traumatic stress and hemodynamic fluctuations [17]. However, no studies have systematically evaluated the modifying effects of these factors on the risk of MINS.
This study compared the incidence of postoperative MINS between PH and other MAS, aiming to elucidate the correlation between PH and MINS, while exploring the potential modifying effects of individual patient characteristics and surgical approaches on MINS risk. The findings of this study will provide important evidence-based foundation for optimizing perioperative cardiac protection strategies.
Methods
Data source
This retrospective cohort study utilized data from the INSPIRE database [18, 19], which is hosted on the PhysioNet platform [20]. The INSPIRE database is a publicly available single-center electronic medical record database containing detailed patient information, including demographic characteristics, preoperative comorbidities, perioperative management data, and postoperative outcomes. The data used in this study encompass patients who underwent PH and other MAS between 2011 and 2020, selected from the perioperative medicine database (version 1.3). All data in the INSPIRE database were approved by the Institutional Review Board (IRB) of Seoul National University Hospital (IRB number: H-2210-078-1368). Due to the retrospective design of this study, the IRB waived the requirement for informed consent. Additionally, the Institutional Data Review Board (DRB) of Seoul National University Hospital approved the public release of the dataset after reviewing and determining that it had been sufficiently de-identified (DRB number: BD-R-2022-11-02). Data on surgery and anesthesia-related variables, diagnoses, vital signs, laboratory results, and medication prescriptions were extracted from the clinical data warehouse of Seoul National University Hospital. Vital signs and related parameters from the operating room and ICU were recorded at fixed intervals. Diagnoses were recorded according to the International Classification of Diseases, 10th revision, Clinical Modification (ICD-10-CM) [21].
Research population
The inclusion criteria were: (1) patients who underwent PH or other MAS under total intravenous anesthesia; (2) patients with at least one postoperative cardiac troponin (cTn) measurement record. Exclusion criteria included: (1) patients younger than 18 years or older than 90 years of age on the day of surgery; (2) patients with more than 30% missing data. For patients who underwent multiple surgeries or had multiple hospitalizations, only the first surgical record was analyzed. A detailed flow diagram of patient inclusion and exclusion is presented in Fig. 1.
Fig. 1.
Flow chart of patient selection. PH, Partial hepatectomy; MAS, major abdominal surgeries
Exposure and outcomes
The exposure variable was the type of surgery, categorized into two groups: the PH group and the MAS group. MAS was defined as an intraperitoneal operation with no primary involvement of the thorax, involving either luminal resection and/or resection of a solid organ associated with the gastrointestinal tract, with operative duration exceeding 2 h and blood loss greater than 200 ml [22, 23]. The classification of surgical procedures was determined using the International Classification of Diseases, Tenth Revision, Procedure Coding System (ICD-10-PCS) codes.
The primary outcome was MINS, defined as: (1) a postoperative cTn measurement ≥ 30 ng/L (exceeding the 99th percentile upper reference limit); (2) representing an absolute increase of at least 30 ng/L from preoperative baseline values; and (3) with no evidence of non-ischemic causes for the elevation [4, 5, 24].
Secondary outcomes included: (1) postoperative myocardial infarction rate; (2) postoperative heart failure rate; (3) in-hospital mortality rate; (4) ICU admission rate; (5) postoperative length of hospital stay.
Statistical analysis
The between-group differences in the primary outcome (MINS) were calculated using logistic regression models to determine odds ratios (OR) and 95% confidence intervals (CI). For secondary outcomes, binary variables were analyzed using logistic regression models, while continuous variables were analyzed using the Hodges-Lehmann estimator to calculate median differences (MD) and 95% CI.
Propensity score matching (PSM) was employed to mitigate the impact of confounding factors. Covariates for the propensity score model were selected based on their established clinical relevance to both surgical procedure selection and postoperative cardiac outcomes. Demographic factors included age (categorized as < 65 or ≥ 65 years to reflect increased cardiovascular risk in older patients), gender, and BMI (classified according to WHO criteria as underweight, normal, overweight, and obese) [25]. Preoperative comorbidities (hypertension, coronary heart disease, diabetes, and chronic kidney disease) were incorporated based on their association with perioperative cardiovascular complications and influence on surgical planning [26, 27]. Intraoperative factors included hypotension (defined as duration of mean arterial pressure < 65 mmHg) and operation duration, both reflecting procedural complexity and hemodynamic stability associated with myocardial injury [28]. Surgical approach (open versus laparoscopic) was included as a determinant of surgical trauma and postoperative inflammatory response that may influence myocardial injury [29].
Propensity scores were calculated using a logistic regression model incorporating these covariates. Matching was performed using the nearest neighbor method with a 1:2 matching ratio and a caliper width of 0.2 standard deviations. The 1:2 ratio was selected to maximize statistical power while maintaining adequate balance between groups. After matching, the balance of covariates between the PH and control groups was assessed using standardized mean differences (SMD), with SMD < 0.1 considered as well-balanced, thereby reducing selection bias and strengthening causal inference.
Continuous variables were presented as mean (standard deviation), and between-group comparisons were conducted using independent samples t-test or Mann-Whitney U test. Categorical variables were expressed as frequencies and percentages, and between-group comparisons were performed using χ² test or Fisher’s exact test.
To evaluate potential selection bias due to the exclusion of patients lacking postoperative troponin data, baseline characteristics were compared between the included cohort (N = 864) and excluded patients (N = 6,632). Categorical variables were analyzed using the Chi-square test, and standardized mean differences (SMD) were calculated to assess the magnitude of between-group imbalances. An SMD greater than 0.1 was interpreted as a meaningful difference (Table S1).
Subgroup analysis
Subgroup analyses were performed based on the following variables: (1) BMI classification (normal vs. overweight/obese); (2) surgical approach (open vs. laparoscopic). Effect differences between subgroups were evaluated using logistic regression models. All statistical analyses were conducted using R software (version 4.2.3; R Foundation for Statistical Computing, Vienna, Austria), and a two-sided P < 0.05 was considered statistically significant.
Results
Baseline characteristics of the study cohort
The initial cohort comprised 864 patients, including 680 who underwent MAS and 184 who underwent partial hepatectomy (PH). Prior to propensity score matching, substantial baseline differences existed between groups, with standardized mean differences exceeding 0.25 for multiple variables, including age (SMD = 0.385), preoperative ischemic cardiomyopathy (SMD = 0.278), surgery duration (SMD = 0.718), and surgical approach (SMD = −0.846) (Table 1).
Table 1.
Baseline covariates before and after matching
| Variables | Level | Before Matching | After Matching | ||||
|---|---|---|---|---|---|---|---|
| Other abdominal surgeries | Partial liver resection surgery | SMD△ | Other abdominal surgeries | Partial liver resection surgery | SMD△ | ||
| n | 680 | 184 | 267 | 163 | |||
| Age (%) | < 65 | 243 (35.7) | 101 (54.9) | 0.385 | 137 (51.3) | 90 (55.2) | −0.012 |
| ≥ 65 | 437 (64.3) | 83 (45.1) | −0.385 | 130 (48.7) | 73 (44.8) | 0.012 | |
| Gender (%) | Female | 214 (31.5) | 44 (23.9) | −0.177 | 64 (24.0) | 41 (25.2) | 0.058 |
| Male | 466 (68.5) | 140 (76.1) | 0.177 | 203 (76.0) | 122 (74.8) | −0.058 | |
| BMI_category (%) | Normal | 354 (52.1) | 96 (52.2) | 0.002 | 137 (51.3) | 86 (52.8) | 0.031 |
| Obese | 47 (6.9) | 19 (10.3) | 0.112 | 22 (8.2) | 16 (9.8) | 0.010 | |
| Overweight | 179 (26.3) | 51 (27.7) | 0.031 | 78 (29.2) | 44 (27.0) | −0.027 | |
| Underweight | 100 (14.7) | 18 (9.8) | −0.166 | 30 (11.2) | 17 (10.4) | −0.021 | |
| Preoperative hypertension(%) | 0 | 583 (85.7) | 167 (90.8) | 0.174 | 245 (91.8) | 150 (92.0) | 0.032 |
| 1 | 97 (14.3) | 17 (9.2) | −0.174 | 22 (8.2) | 13 (8.0) | −0.032 | |
| Preoperative ischemic cardiomyopathy (%) | 0 | 589 (86.6) | 172 (93.5) | 0.278 | 247 (92.5) | 151 (92.6) | −0.025 |
| 1 | 91 (13.4) | 12 (6.5) | −0.278 | 20 (7.5) | 12 (7.4) | 0.025 | |
| Preoperative diabetes mellitus (%) | 0 | 563 (82.8) | 161 (87.5) | 0.142 | 232 (86.9) | 144 (88.3) | 0.056 |
| 1 | 117 (17.2) | 23 (12.5) | −0.142 | 35 (13.1) | 19 (11.7) | −0.056 | |
| Preoperative chronic kidney disease (%) | 0 | 643 (94.6) | 175 (95.1) | 0.025 | 253 (94.8) | 154 (94.5) | −0.028 |
| 1 | 37 (5.4) | 9 (4.9) | −0.025 | 14 (5.2) | 9 (5.5) | 0.028 | |
|
Surgery duration (mean (SD)) |
3.12 (1.54) | 4.45 (1.85) | 0.718 | 3.68 (1.84) | 4.21 (1.72) | 0.114 | |
| Intraoperative hypotension (%) | 0 | 97 (14.3) | 10 (5.4) | −0.389 | 22 (8.2) | 10 (6.1) | −0.027 |
| 1 | 583 (85.7) | 174 (94.6) | 0.389 | 245 (91.8) | 153 (93.9) | 0.027 | |
|
Surgical Approach (%) |
Minimally Invasive | 253 (37.2) | 20 (10.9) | −0.846 | 33 (12.4) | 20 (12.3) | 0.059 |
| Open | 427 (62.8) | 164 (89.1) | 0.846 | 234 (87.6) | 143 (87.7) | −0.059 | |
△Standardized Mean Difference
Following propensity score matching, 430 patients were retained for analysis, consisting of 267 patients in the MAS group and 163 in the PH group. The matching procedure effectively balanced baseline characteristics between groups, with post-matching SMDs reduced to less than 0.1 for all variables except surgery duration (SMD = 0.114). Specifically, SMDs decreased to −0.012 for age, 0.025 for preoperative ischemic cardiomyopathy, and 0.059 for surgical approach, indicating adequate covariate balance and mitigation of selection bias (Table 1).
Primary and secondary outcomes
Primary and secondary outcomes for the matched cohort are presented in Table 2. Myocardial injury after non-cardiac surgery, the primary outcome, occurred in 72 of 163 patients (44.2%) in the PH group compared with 92 of 267 patients (34.5%) in the MAS group. Multivariate analysis demonstrated that patients undergoing PH had significantly higher odds of developing MINS than those undergoing MAS (odds ratio [OR], 1.51; 95% confidence interval [CI], 1.01–2.24; P = 0.044).
Table 2.
Subgroup analysis of myocardial injury risk
| Outcome | Other abdominal surgeries (N = 267) |
Partial liver resection surgery (N = 163) |
Multivariate model | |
|---|---|---|---|---|
| OR | P-value | |||
| Primary outcome | ||||
| Myocardial injury after non-cardiac surgery | 92 (34.5) | 72 (44.2) | 1.51 (1.01–2.24) | 0.044 |
| Secondary outcomes | ||||
| Myocardial infarction after surgery | 15 (5.6) | 10 (6.1) | 1.10 (0.48–2.52) | 0.456 |
| Heart failure after surgery | 4 (1.5) | 3 (1.8) | 1.23 (0.27–5.58) | 0.786 |
| Death in hospital | 14 (5.2) | 12 (7.4) | 1.44 (0.65–3.19) | 0.372 |
| ICU after surgery | 102 (38.2) | 70 (42.9) | 1.22 (0.82–1.82) | 0.331 |
Secondary outcomes did not differ significantly between groups. Myocardial infarction occurred in 6.1% of PH patients versus 5.6% of MAS patients (OR, 1.10; 95% CI, 0.48–2.52; P = 0.456), while postoperative heart failure developed in 1.8% and 1.5%, respectively (OR, 1.23; 95% CI, 0.27–5.58; P = 0.786). In-hospital mortality was 7.4% in the PH group and 5.2% in the MAS group (OR, 1.44; 95% CI, 0.65–3.19; P = 0.372). Postoperative ICU admission rates were 42.9% for PH patients and 38.2% for MAS patients (OR, 1.22; 95% CI, 0.82–1.82; P = 0.331).
Subgroup analyses for the risk of MINS
Subgroup analyses were performed to assess the consistency of the association between surgery type and MINS risk across patient strata (Table 3). The surgical group demonstrated no significant interactions with age, gender, BMI, preoperative ischemic cardiomyopathy, preoperative hypertension, preoperative diabetes mellitus, preoperative chronic kidney disease, or intraoperative hypotension (P for interaction > 0.05 for all).
Table 3.
Primary and secondary outcomes between surgical groups
| Subgroup | Other abdominal surgeries | Partial liver resection surgery | OR (95% CI) | P value | P for interaction |
|---|---|---|---|---|---|
| Overall | 92/267 (34.5) | 72/163 (44.2) | 1.51 (1.01–2.24) | 0.044 | |
| Age | 0.553 | ||||
| < 65 | 50/137 (36.5) | 44/90 (48.9) | 1.66 (0.97–2.86) | 0.065 | |
| ≥ 65 | 42/130 (32.3) | 28/73 (38.4) | 1.30 (0.72–2.37) | 0.385 | |
| Gender | 0.241 | ||||
| Female | 16/64 (25.0) | 18/41 (43.9) | 2.35 (1.02–5.42) | 0.046 | |
| Male | 76/203 (37.4) | 54/122 (44.3) | 1.33 (0.84–2.09) | 0.224 | |
| BMI | 0.181 | ||||
| Normal | 55/137 (40.1) | 38/86 (44.2) | 1.18 (0.68–2.04) | 0.552 | |
| Obese | 4/22 (18.2) | 5/16 (31.2) | 2.05 (0.45–9.29) | 0.354 | |
| Overweight | 21/78 (26.9) | 23/44 (52.3) | 2.97 (1.37–6.45) | 0.006 | |
| Underweight | 12/30 (40.0) | 6/17 (35.3) | 0.82 (0.24–2.81) | 0.75 | |
| Preoperative ischemic cardiomyopathy | 0.995 | ||||
| 0 | 84/247 (34.0) | 66/151 (43.7) | 1.51 (0.99–2.28) | 0.053 | |
| 1 | 8/20 (40.0) | 6/12 (50.0) | 1.50 (0.35–6.35) | 0.582 | |
| Preoperative hypertension | 0.302 | ||||
| 0 | 86/245 (35.1) | 65/150 (43.3) | 1.41 (0.93–2.14) | 0.103 | |
| 1 | 6/22 (27.3) | 7/13 (53.8) | 3.11 (0.74–13.11) | 0.122 | |
| Preoperative diabetes mellitus | 0.226 | ||||
| 0 | 77/232 (33.2) | 65/144 (45.1) | 1.66 (1.08–2.54) | 0.021 | |
| 1 | 15/35 (42.9) | 7/19 (36.8) | 0.78 (0.25–2.45) | 0.668 | |
| Preoperative chronic kidney disease | 0.15 | ||||
| 0 | 83/253 (32.8) | 68/154 (44.2) | 1.62 (1.07–2.45) | 0.022 | |
| 1 | 9/14 (64.3) | 4/9 (44.4) | 0.44 (0.08–2.46) | 0.353 | |
| Intraoperative hypotension | 0.825 | ||||
| 0 | 6/22 (27.3) | 4/10 (40.0) | 1.78 (0.37–8.59) | 0.474 | |
| 1 | 86/245 (35.1) | 68/153 (44.4) | 1.48 (0.98–2.24) | 0.063 | |
| Surgical Approach | 0.067 | ||||
| Minimally Invasive | 6/33 (18.2) | 10/20 (50.0) | 4.50 (1.30–15.63.30.63) | 0.018 | |
| Open | 86/234 (36.8) | 62/143 (43.4) | 1.32 (0.86–2.01) | 0.203 | |
Within specific subgroups, notable variations emerged despite the absence of significant interactions. The association between PH and MINS reached statistical significance among females (OR, 2.35; 95% CI, 1.02–5.42; P = 0.046) but not males (OR, 1.33; 95% CI, 0.84–2.09; P = 0.224), though the interaction test remained non-significant (P for interaction = 0.241). When stratified by BMI, overweight patients demonstrated a significantly elevated risk of MINS (OR, 2.97; 95% CI, 1.37–6.45; P = 0.006), whereas other BMI categories showed no significant association, with the overall BMI interaction remaining non-significant (P for interaction = 0.181). Stratification by surgical approach revealed a pronounced association between PH and MINS among patients undergoing minimally invasive procedures (OR, 4.50; 95% CI, 1.30–15.63; P = 0.018), while the open surgery subgroup showed no significant association (OR, 1.32; 95% CI, 0.86–2.01; P = 0.203). The interaction between surgical group and surgical approach approached but did not achieve conventional statistical significance (P for interaction = 0.067).
Discussion
This study employed PSM to systematically compare the incidence of myocardial injury after non-cardiac surgery between patients undergoing partial hepatectomy and those undergoing other major abdominal surgeries. The analysis revealed that PH was associated with a significantly higher risk of MINS (44.2% vs. 34.5%; P = 0.044). This observation suggests that liver-specific ischemia–reperfusion injury (IRI) may contribute to postoperative myocardial injury through systemic inflammatory and oxidative stress–mediated pathways [9, 30]. Notably, subgroup analyses indicated that this association was most pronounced among overweight patients, in whom PH conferred an almost threefold increase in MINS risk compared with other MAS (OR = 2.97, 95% CI 1.37–6.45, P = 0.006), underscoring BMI as a potential effect modifier in this relationship.
A critical consideration in interpreting our findings concerns the observed divergence between elevated biomarker-defined outcomes (MINS) and the absence of statistically significant differences in clinically manifest endpoints, including postoperative myocardial infarction, heart failure, and in-hospital mortality. This apparent discordance merits careful examination. The most parsimonious explanation involves statistical power limitations; while our study possessed adequate power to detect differences in MINS (with incidence exceeding 30%), it was likely underpowered to identify significant variations in less frequent events such as in-hospital mortality or overt myocardial infarction, which occurred at rates below 7%. Moreover, the prognostic implications of MINS characteristically extend beyond the immediate postoperative period. Seminal investigations, particularly the VISION trial, have established that MINS predominantly influences 30-day and 1-year mortality rather than immediate in-hospital outcomes. Consequently, the absence of significant differences in our short-term, in-hospital data does not preclude potential long-term adverse sequelae. The detected myocardial injury may represent a sentinel marker heralding future cardiovascular risk.
Engaging with contemporary debates in perioperative medicine, MINS following PH may constitute a distinct pathophysiological entity. Unlike MINS arising from acute plaque rupture, hepatectomy-associated MINS may be predominantly mediated by systemic inflammatory responses to hepatic IRI, culminating in transient, subclinical myocardial injury through supply-demand imbalance or cytokine-mediated cardiotoxicity. Although this injury pattern may not precipitate immediate catastrophic events, it nonetheless signifies substantial myocardial stress and represents an established harbinger of long-term cardiovascular morbidity.
It is noteworthy that the incidence of MINS in this study (34%−44%) was higher than previously reported rates for MAS [4, 5]. This discrepancy may be related to study design and diagnostic criteria selection. First, only patients who underwent postoperative cardiac troponin (cTn) measurement were included, a subgroup that typically exhibits higher baseline cardiovascular risk, such as advanced age or multiple preoperative comorbidities. Our analysis supports this, showing that patients included in the final cohort differed significantly from those excluded due to missing troponin data (Table S1). Specifically, the included cohort was older (60.2% vs. 42.5% aged ≥ 65 years; SMD = − 0.36) and had a higher prevalence of preoperative hypertension (SMD = 0.11), ischemic cardiomyopathy (SMD = 0.19), and diabetes (SMD = 0.16). Consequently, younger patients or those without major comorbidities may have been underrepresented, potentially leading to an overestimation of MINS incidence. Second, the diagnostic criteria for MINS were based on postoperative cTn levels exceeding the 99th percentile with dynamic changes, a sensitive standard that may result in higher detection rates [4, 5]. However, the same diagnostic criteria were applied to both surgical types in this study, ensuring comparability of results between groups. Additionally, the IRI specific to PH may further increase the risk of MINS, which could be an important factor contributing to the elevated MINS incidence [9].
Compared with previous studies, this research further validates the high-risk characteristics of PH and provides support for the potential mechanistic role of hepatic IRI in the occurrence of MINS [9, 31]. Previous studies have demonstrated that MINS is a common complication following non-cardiac surgery, with its incidence significantly associated with 30-day all-cause mortality [4, 32]. However, research on the relationship between PH and MINS has been limited. Our findings suggest that hepatic IRI, by activating systemic inflammatory responses and oxidative stress, may lead to coronary microcirculation dysfunction, myocardial cellular metabolic disorders, and autonomic nervous system dysfunction, thereby increasing the risk of myocardial injury [12, 31, 33]. Research by Clavien et al. indicated that the severity of hepatic IRI is closely related to intraoperative ischemia duration and reperfusion intensity, factors that are particularly significant in PH [9]. Additionally, the chronic low-grade inflammatory state in obese patients may synergize with IRI, further exacerbating the risk of MINS [16].
Regarding surgical approach, a notable pattern emerged. The association between PH and MINS was substantially stronger among patients undergoing minimally invasive procedures (OR = 4.50; 95% CI, 1.30–15.63), whereas no significant association was observed in the open surgery subgroup (OR = 1.32; 95% CI, 0.86–2.01). Although the interaction term did not reach statistical significance (P for interaction = 0.067), this trend likely reflects limited statistical power within subgroups, particularly given the small sample size in the minimally invasive PH cohort (n = 20) [34].
The results of this study have important, albeit nuanced, clinical implications. First, partial hepatectomy should be regarded as a significant risk factor for MINS, with the association being most robust among overweight patients [35]. Cardiac monitoring should be enhanced for these patients during the perioperative period. For example, dynamic monitoring of postoperative cTn levels can facilitate early identification and intervention for myocardial injury [17]. Furthermore, optimizing intraoperative hemodynamic management (such as maintaining mean arterial pressure ≥ 65 mmHg), reducing ischemia-reperfusion time, and early postoperative interventions (such as using β-blockers or statins) may effectively reduce the incidence of related complications [17]. Second, this study suggests the need to develop new intervention strategies targeting hepatic IRI mechanisms. In recent years, anti-inflammatory and antioxidant therapies have shown potential in alleviating IRI in animal experiments, such as using N-acetylcysteine (NAC) or statins to inhibit oxidative stress and inflammatory responses [36, 37]. Additionally, preoperative conditioning (such as ischemic postconditioning) has been proven to reduce the remote effects of IRI by modulating the ischemic tolerance of both liver and myocardium [38].
Limitations
Several limitations warrant consideration. First, selection bias arose from requiring postoperative troponin measurement, yielding an analytic cohort skewed toward older, higher-risk patients with greater cardiovascular comorbidity (Table S1). Thus, our findings primarily reflect this subgroup, and the reported MINS incidence should be interpreted accordingly. Second, restriction to in-hospital follow-up precluded assessment of 30-day and 1-year mortality—critical endpoints given MINS’s long-term prognostic implications. While our study identifies increased short-term myocardial injury, we cannot determine whether this translates to differences in long-term survival. Third, generalizability is limited by our single-center South Korean cohort, which may not represent Western populations with different demographics, liver disease patterns, and perioperative protocols. Fourth, the borderline significance (P = 0.044) with confidence interval approaching unity (OR = 1.51, 95% CI: 1.01–2.24) suggests our finding is hypothesis-generating rather than definitive. Finally, despite propensity matching, unmeasured confounding persists. Variables absent from our model—liver disease severity indices, resection extent, surgical expertise, and anesthetic techniques—are strong outcome predictors that may influence results. Collectively, these limitations underscore the need for multicenter prospective studies with extended follow-up to validate the association between partial hepatectomy and MINS across diverse populations and confirm its clinical implications.
Conclusions
This study systematically compared the risk of MINS following PH versus other MAS using propensity score matching. The findings revealed that PH significantly increased MINS incidence (44% vs. 34%), particularly in overweight patients.
Supplementary Information
Supplementary Material 1. Table S1. Baseline characteristics: included versus excluded patients. Comparison of demographic and clinical characteristics between patients included in the final analysis (n=864) and those excluded due to missing postoperative troponin data (n=6,632). Data are presented as number (percentage) for categorical variables. SMD, standardized mean difference.
Acknowledgements
We gratefully acknowledge the INSPIRE dataset, provided by Leerang Lim and Hyung-Chul Lee, for its invaluable contribution to our research in perioperative medicine. Our sincere thanks also extend to PhysioNet for hosting this important resource.
Authors’ contributions
Zheng Zhang: Conceptualization, Statistical Analysis (Propensity Score Matching), Data Extraction from INSPIRE Database, Writing – Original Draft Preparation.Yi Duan: Methodology Validation, Writing – Review & Editing, Experimental Design Refinement.Hongyu Huo: Figure Preparation, Data Visualization Design.Yuze Wang: Data Analysis Support, Results Interpretation, Statistical Review.Zhifeng Gao: Supervision, Quality Control, Study Design, Final Manuscript Approval.
Funding
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
Data availability
The datasets analyzed in this study are available in the INSPIRE database and can be accessed at https://physionet.org/content/inspire/1.3/ under the terms and conditions of use.
Declarations
Ethics approval and consent to participate
This study was conducted using de-identified data from the publicly available INSPIRE database, which was approved by the Institutional Review Board (IRB) of Seoul National University Hospital (IRB number: H-2210-078-1368). The IRB waived the requirement for informed consent due to the retrospective nature of the study and use of de-identified data. The Institutional Data Review Board (DRB) also approved public release of the dataset (DRB number: BD-R-2022-11-02).
Consent for publication
Not applicable. This study used fully de-identified data from the publicly available INSPIRE database, and no individual person’s identifiable data (including images or clinical details) were included.
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.
Zheng Zhang and Yi Duan contributed equally to this work and should be considered co-first authors.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Material 1. Table S1. Baseline characteristics: included versus excluded patients. Comparison of demographic and clinical characteristics between patients included in the final analysis (n=864) and those excluded due to missing postoperative troponin data (n=6,632). Data are presented as number (percentage) for categorical variables. SMD, standardized mean difference.
Data Availability Statement
The datasets analyzed in this study are available in the INSPIRE database and can be accessed at https://physionet.org/content/inspire/1.3/ under the terms and conditions of use.