Sex Differences in Post-Noncardiac Surgery Risks Assessed Using the Revised Cardiac Risk Index　― A Nationwide Retrospective Cohort Study ―

Abstract

Background: The Revised Cardiac Risk Index (RCRI) has been incorporated into preoperative assessment guidelines and is used for simple preoperative screening; however, validation studies within large populations are limited. Moreover, although sex differences in perioperative risk are recognized, their effect on the performance of the RCRI remains unclear. Therefore, in this study we evaluated whether sex differences exist in the risks within the strata classified by the RCRI.

Methods and Results: The Japan Medical Data Center database based on claim and health examination data in Japan between January 2005 and April 2021 was used. A total of 161,359 noncardiac surgeries performed during hospitalization were analyzed. The main outcome was the 30-day risk of major adverse cardiovascular events. Although there was no significant sex difference among those with an RCRI ≥1, males had a significant hazard rate (1.32 [95% confidence interval, 1.03–1.68]) of postoperative events in the low-risk group with an RCRI of 0. However, this significant difference was not detected in the population excluding those who underwent breast and gynecological surgeries.

Conclusions: The RCRI achieved reasonable risk stratification in validation using Japanese real-world data regardless of sex. Although further detailed analysis is necessary to determine the sex differences, the validity of using the RCRI for screening purposes is supported at this stage.

The number of surgical procedures and the importance of collateral complications are increasing worldwide.^1,2 Stratification of the risk of postoperative cardiovascular complications in noncardiac surgeries and the scope for intervention are important topics, and several clinical guidelines, such as those by the American College of Cardiology and American Heart Association,³ European Society of Cardiology,⁴ Canadian Cardiovascular Society,⁵ and Japanese Circulation Society,⁶ have provided recommendations for specific assessments and interventions. The incidence of postoperative cardiovascular events is influenced by patient-specific factors and inherent risks associated with the surgical procedure itself.^7–11 Consequently, it is essential to conduct individualized preoperative assessments and stratify the risk of each patient accordingly.

A detailed assessment of the risk of perioperative cardiovascular complications is complex because perioperative risk involves both the risk of the procedure itself and patient factors.^12,13 Many attempts have been made to stratify these factors in clinical practice, and many assessment tools have been developed.^1,14–20 Among these, the Revised Cardiac Risk Index (RCRI)¹⁶ has been a long-standing tool in clinical practice for stratifying the risk of perioperative cardiovascular events in patients undergoing noncardiac surgeries.²¹ Although imperfections in predictive performance have been reported, including decreased accuracy for vascular surgery,^14,17,20 the RCRI has been integrated into preoperative guidelines for noncardiac surgeries and serves as a risk evaluation algorithm.^3–6 It stratifies patients based on the likelihood of a composite outcome of myocardial infarction, cardiac arrest or death by assigning scores to 6 independent predictors. Patients with a score of 0 who do not have any of these 6 risk factors (elevated-risk surgery, history of ischemic heart disease, history of congestive heart failure, history of cerebrovascular disease, history of diabetes requiring preoperative insulin use, and preoperative creatinine level >2 mg/dL) are identified by the RCRI as low risk for cardiac complications.^2,16,22–33

Recently, the importance of recognizing sex biases in the cardiovascular field is increasingly recognized.³⁴ Sex differences in cardiovascular risk exist in various ways, and an understanding of the clinical significance of these biases is important.^35–41 It is important to assess bias with respect to the RCRI because it is currently used as a risk assessment tool in clinical practice. Previous studies investigating sex differences in the incidence of postoperative events among patients undergoing noncardiac surgeries have typically observed a higher postoperative risk in males than in females.^42–45 However, when using the RCRI for risk stratification, the extent to which risk is influenced by sex within each stratified patient group remains unclear. Consequently, in this study we aimed to ascertain the risk stratification capability of the RCRI and the magnitude of sex bias within patient groups stratified by risk in the evaluation of the postoperative risk of noncardiac surgeries.

Methods

Study Design and Population

We used the Japan Medical Data Center (JMDC) claims database, which contains information on medical claims and health examinations in Japan.^46–49 The database, which is accessible for purchase from the JMDC, encompasses data on approximately 11.6 million individuals from January 2005 to April 2021. It comprises diagnostic information based on the International Classification of Diseases, 10th Revision (ICD-10), prescription data according to the Anatomical Therapeutic Chemical (ATC) classification system, medical practice details based on the receipt of electronic processing codes, and results of specific medical examinations.

For this analysis, codes corresponding to noncardiac surgeries were extracted from the medical practice data alongside classification codes indicating surgery (K-codes), resulting in 3,797,257 codes. From these, only the codes recorded during hospitalization were selected. The selection was further refined to surgeries in which general or spinal anesthesia was administered on the same day. The analysis was limited to individuals aged ≥18 years. When multiple K-codes were recorded on the same day, the code with the highest reimbursement score was retained as the primary surgery, and duplicate K-codes on the same day were excluded. Patients with no recorded postoperative data were excluded from the study. The final study included patients with creatinine levels measured during physical examination within 1 year prior to surgery.

Ethics Approval

The study was conducted in accordance with the principles of the Declaration of Helsinki. Although this study used anonymized data and was outside the scope of the guidelines for research involving human subjects in Japan, it was conducted after registration with the Ethics Committee of the University of Tokyo Hospital (Approval No. 2024105NIe).

Measurements

In this study, K-codes, which represent the classification numbers of electronic receipt processing codes in Japan, were used to identify noncardiac and cardiac surgeries, addition codes, and blood transfusion codes that were excluded from the analysis. General and spinal anesthesia administrations were identified from the electronic receipt processing codes. Previous ischemic heart disease was defined as ICD-10 codes I20–I25 or multiple prescriptions for abortive nitroglycerin prior to surgery. A history of stroke was defined according to ICD-10 codes I60–I64 and G459. A history of heart failure was determined using ICD-10 codes I50 and I110. Diabetes requiring insulin administration was defined as the coexistence of ICD-10 codes E10–E14 and ATC code A10A in the prescription information. High-risk surgeries were identified using codes corresponding to abdominal, thoracic, and vascular surgeries performed above the inguinal region. Creatinine levels >2.0 mg/dL were established using values from physical examinations conducted within 1 year prior to surgery. Patients in whom creatinine levels were not recorded within the year prior to surgery were excluded from the analysis. The RCRI was calculated based on these items. In line with previous validation studies, we divided the nonsurgical cases into 4 groups based on the RCRI (0, 1, 2, and ≥3).⁵⁰

For detailed disease definitions used in the sensitivity analysis, a combination of ICD-10 and medical practice codes was used with reference to validation studies.^51–53 Specifically, previous ischemic heart disease was defined using ICD-10 codes I20–I23 with same-day percutaneous coronary intervention or coronary artery bypass grafting performed within 7 days. Additionally, cases in which the patients were administered antiplatelet agents within 2 days, in conjunction with ICD-10 codes I20–I23, were also classified as a history of ischemic heart disease. Heart failure was defined using ICD-10 codes I50 and I110, combined with the administration of intravenous diuretics within 2 days of the diagnosis. Cerebral infarction was defined using ICD-10 codes I60, I61, I63, G45.8, and G45.9, in combination with a computed tomography or magnetic resonance imaging evaluation performed on the same day as the diagnosis.

Sensitivity Analysis

Breast and gynecological surgeries are procedures specific to females, with breast surgery, in particular, being associated with a low perioperative cardiovascular risk.⁵⁴ In the sensitivity analysis, we evaluated a cohort that excluded breast and gynecological surgeries (sensitivity analysis 1). Additionally, a separate sensitivity analysis was performed on a cohort that excluded urological surgeries, alongside breast and gynecological surgeries (sensitivity analysis 2), as urologic procedures are predominantly specific to males. Similar analyses were conducted in a cohort utilizing a detailed history definition that integrated ICD-10 codes with medical procedure codes (sensitivity analyses 3–5). Additionally, similar analyses were conducted in a cohort utilizing a detailed history and outcome definition with ICD-10 codes and procedure codes (sensitivity analyses 6–8).

Outcomes

The outcome of this study was defined as the occurrence of major adverse cardiovascular events (MACE) within 30 days of surgery, based on ICD-10 codes: myocardial infarction (ICD-10 codes: I21–I22), heart failure (ICD-10 codes: I50 and I110), stroke (ICD-10 codes: I60–I64 and G459), arrest (ICD-10 code: I46), and death. Follow-up was defined as the period from the date of surgery to the date of death or the last recorded entry into the insurance database, whichever came first. For the sensitivity analysis using detailed disease definitions, the definitions of ischemic heart disease, heart failure, and stroke were combined with medical practice codes, following the methodology outlined in the Measurements section above.

Statistical Analysis

Categorical variables are presented as percentages and were tested using the chi-square test. Continuous variables are presented as mean and standard deviation and tested using the Student’s t-test. Incidence rates were calculated per 100 persons over 30 days. The Kaplan-Meier method was used to the cumulative incidence plots, and the log-rank test was used for statistical testing. Cox proportional hazards analysis was used to calculate the hazard rate for males relative to females; in the Cox proportional hazards analysis, age was included in the model as an adjustment factor. Statistical analyses were performed using R version 4.3.3.

Results

Patients’ Characteristics and Outcomes

A total of 161,359 surgeries were included in the analysis (Figure 1, Table 1). MACE within 30 days after surgery occurred in 987 cases (Table 2). The mean age of the patients at surgery was approximately 48 years. Male patients had a significantly higher mean age, body mass index, and serum creatinine levels. Significant sex differences were observed in the number of breast, gynecological, and urological surgeries. Additionally, significant sex differences were noted in the occurrence of events in abdominal, breast, and ear, nose, and throat/neck surgeries (Supplementary Table 1).

Figure 1.

Flowchart of patient selection. JMDC, Japan Medical Data Center.

Table 1.

Patients’ Clinical Background Information

Variables	Overall	Male	Female	P value
N	161,359	90,382	70,977
Age, mean (SD), years	48.63 (11.29)	50.22 (11.44)	46.60 (10.75)	<0.001
BMI, mean (SD), kg/m2	23.35 (3.89)	24.14 (3.68)	22.34 (3.91)	<0.001
Serum creatinine, mean (SD), μmol/L	0.79 (0.52)	0.91 (0.62)	0.63 (0.27)	<0.001
Type of surgery (%)
Abdominal	39,052 (24.2)	29,606 (32.8)	9,446 (13.3)	<0.001
Breast	8,258 (5.1)	96 (0.1)	8,162 (11.5)
Dermatologic	2,214 (1.4)	1,599 (1.8)	615 (0.9)
ENT/neck	13,456 (8.3)	9,149 (10.1)	4,307 (6.1)
Gynecologic	30,550 (18.9)	2 (0.0)	30,548 (43.0)
Neurological	5,206 (3.2)	3,323 (3.7)	1,883 (2.7)
Ophthalmic	834 (0.5)	601 (0.7)	233 (0.3)
Oral	401 (0.2)	332 (0.4)	69 (0.1)
Orthopedic	39,364 (24.4)	27,948 (30.9)	11,416 (16.1)
Plastic	1,322 (0.8)	713 (0.8)	609 (0.9)
Thoracic	5,172 (3.2)	3,840 (4.2)	1,332 (1.9)
Urologic	13,818 (8.6)	12,050 (13.3)	1,768 (2.5)
Vascular	1,712 (1.1)	1,123 (1.2)	589 (0.8)
History of ischemic heart disease (%)	10,935 (6.8)	7,809 (8.6)	3,126 (4.4)	<0.001
History of congestive heart failure (%)	9,249 (5.7)	6,409 (7.1)	2,840 (4.0)	<0.001
History of cerebrovascular disease (%)	5,831 (3.6)	4,018 (4.4)	1,813 (2.6)	<0.001
Preoperative treatment with insulin (%)	4,147 (2.6)	3,266 (3.6)	881 (1.2)	<0.001
Preoperative creatinine >2 mg/dL (%)	718 (0.4)	616 (0.7)	102 (0.1)	<0.001
Elevated-risk surgery (%)	44,850 (27.8)	33,898 (37.5)	10,952 (15.4)	<0.001
RCRI group (%)
0	100,871 (62.5)	46,605 (51.6)	54,266 (76.5)	<0.001
1	48,957 (30.3)	34,768 (38.5)	14,189 (20.0)
2	8,534 (5.3)	6,426 (7.1)	2,108 (3.0)
≥3	2,997 (1.9)	2,583 (2.9)	414 (0.6)

BMI, body mass index; ENT, ear, nose, and throat; RCRI, Revised Cardiac Risk Index; SD, standard deviation.

Table 2.

Development of MACE Within 30 Days After Surgery

	Overall		Male		Female
	Event (−)	Event (+)	Event (−)	Event (+)	Event (−)	Event (+)
Total (n)	160,372	987	89,705	677	70,667	310
RCRI group (%)
0	100,590 (62.7)	281 (28.5)	46,448 (51.8)	157 (23.2)	54,142 (76.6)	124 (40.0)
1	48,576 (30.3)	381 (38.6)	34,501 (38.5)	267 (39.4)	14,075 (19.9)	114 (36.8)
2	8,338 (5.2)	196 (19.9)	6,281 (7.0)	145 (21.4)	2,057 (2.9)	51 (16.5)
≥3	2,868 (1.8)	129 (13.1)	2,475 (2.8)	108 (16.0)	393 (0.6)	21 (6.8)

MACE, major adverse cardiac events; RCRI, Revised Cardiac Risk Index.

Survival Analysis

The overall MACE occurrence after surgery analyzed by the RCRI showed that significant stratification was achieved when the cumulative event occurrence was evaluated by the cumulative incidence plots with the Kaplan-Meier method (Figure 2). Similar stratification was achieved in the calculation of event rates, with 4.50 MACE events (per 100-person, month) in the group with an RCRI ≥3 (Table 3). An RCRI of 0 showed a significantly higher incidence of MACE in males than in females (Figure 3, Table 4). There was no significant difference in event rates by sex for groups other than those with an RCRI of 0. In the Cox proportional hazards analysis adjusted for age, the hazard rate for males compared with females was significantly higher only in the group with an RCRI of 0 (Table 5).

Figure 2.

Cumulative incidence plots with the Kaplan-Meier method showing the cumulative incidence of postoperative MACE occurrence stratified by RCRI group. MACE, major adverse cardiovascular event; RCRI, Revised Cardiac Risk Index.

Table 3.

Overall MACE Incidence After Surgery Stratified by RCRI

RCRI	N	Event n (%)	Incidence (events, per 100 person – 30 days)	Incidence 95% CI
All	161,359	987 (0.6)	0.63	0.59–0.67
0	100,871	281 (0.3)	0.29	0.25–0.32
1	48,957	381 (0.8)	0.80	0.72–0.89
2	8,534	196 (2.3)	2.38	2.06–2.73
≥3	2,997	129 (4.3)	4.50	3.75–5.34

CI, confidence interval; MACE, major adverse cardiovascular event; RCRI, Revised Cardiac Risk Index.

Figure 3.

Cumulative incidence plots with Kaplan-Meier method showing the cumulative incidence of postoperative MACE occurrence stratified by RCRI group and sex. (A) RCRI of 0, (B) RCRI of 1, (C) RCRI of 2, and (D) RCRI ≥3. P values display the results of the log-rank test. MACE, major adverse cardiovascular event; RCRI, Revised Cardiac Risk Index.

Table 4.

MACE Incidence After Surgery Stratified by Sex and RCRI

RCRI	Male				Female				P value
	N	Event, n (%)	Incidence (events, per 100 person – 30 days)	Incidence, 95% CI	N	Event, n (%)	Incidence (events, per 100 person – 30 days)	Incidence, 95% CI
All	90,382	677 (0.7)	0.77	0.71–0.83	70,977	310 (0.4)	0.45	0.40–0.50	<0.001
0	46,605	157 (0.3)	0.34	0.29–0.40	54,266	124 (0.2)	0.24	0.20–0.28	<0.005
1	34,768	267 (0.8)	0.79	0.70–0.89	14,189	114 (0.8)	0.83	0.68–1.00	0.67
2	6,426	145 (2.3)	2.33	1.97–2.75	2,108	51 (2.4)	2.51	1.87–3.30	0.65
≥3	2,583	108 (4.2)	4.36	3.58–5.27	414	21 (5.1)	5.34	3.31–8.17	0.40

Abbreviations as in Table 3.

Table 5.

Age-Adjusted Hazard Rate for Males Relative to Females Based on Cox Proportional Hazards Analysis

RCRI	Age-adjusted HR	Age-adjusted HR 95% CI	P value for interaction
All	1.30	1.06–1.59	<0.005
0	1.32	1.03–1.68
1	0.94	0.75–1.17
2	0.90	0.65–1.24
≥3	0.83	0.52–1.33

CI, confidence interval; HR, hazard ratio; RCRI, Revised Cardiac Risk Index.

Sensitivity Analysis

Details of the cohorts in the sensitivity analysis are shown in Supplementary Table 2 and Supplementary Table 3. The results of analysis excluding sex-specific surgeries (sensitivity analyses 1 and 2) demonstrated that although the stratification performance of the RCRI remained consistent, there were no significant differences in incidence or significant hazard ratios between sex across any of the risk strata (Supplementary Tables 4–7). Similarly, the significant sex differences observed in the RCRI 0 group within the cohort with detailed history definition (sensitivity analysis 3) were not detected in the cohort excluding sex-specific surgeries (sensitivity analyses 4 and 5). In the analysis of all surgical cases with the cohort with detailed history and outcome definition (sensitivity analysis 6), the adjusted hazard ratios were predominantly >1 for both the RCRI 0 and 1 groups. However, in separate analyses excluding sex-specific surgeries (sensitivity analyses 7 and 8), the significance of the hazard ratio by sex was no longer observed in the RCRI 0 group, but remained significant in the RCRI 1 group.

Discussion

In this study, we assessed the validity of the RCRI and investigated the effect of sex differences using a large dataset of claims data from Japan. This study was a descriptive analysis of whether sex differences existed within strata defined according to the RCRI, using data obtained from real-world Japanese patients. Although males are known to have a higher incidence of MACE after noncardiac surgeries,⁵⁵ our main analysis suggested that the RCRI achieved appropriate risk stratification, and that the sex difference was limited to the group with an RCRI of 0. Although the RCRI was published more than 20 years ago,¹⁶ it continues to be utilized for screening in clinical practice owing to its simplicity.^3–6 In our validation, the number of surgeries with an RCRI of 0 accounted for the majority of surgeries in the analysis. Considering that >200 million surgeries are performed annually worldwide,⁵⁶ and that the group with an RCRI of 0 represents more than half of all noncardiac surgeries, the sex difference in incidence rates in this group is likely to produce a fairly large difference in the number of postoperative MACE events. However, in the cohort excluding sex-specific surgeries, a significant sex difference was not observed in the low-risk group, suggesting that the previously identified significant difference may be attributable to the sex-specific nature of the surgical procedures. The findings after excluding sex-specific surgeries were replicated in the cohort where a detailed history definition was applied to improve the positive predictive value of disease identification in the sensitivity analysis. Conversely, in the sensitivity analysis with the cohort with detailed history and outcome definition, the age-adjusted hazard ratio remained significantly greater than 1 in the group with an RCRI of 1, even after the exclusion of sex-specific surgeries. Consequently, it remains inconclusive whether a significant sex difference with a clinically significant effect exists within this group. Based on the incidence of events observed in both the main and sensitivity analyses for the RCRI 1 group (Tables 3,4, Supplementary Tables 4,5), it is unlikely that any such difference would have a clinically significant effect that would undermine the utility of screening. However, further rigorous validation using diverse databases will be required to enhance the robustness of the RCRI 1 group in confirming the absence of clinically meaningful sex differences.

The incidence rate in the population analyzed in this study was slightly lower than that reported in previous validation studies.^32,33,50 The JMDC database used in this study was constructed based on health insurance claims and health checkup data provided by insurers; therefore, it does not include populations with different insurance systems. A critical feature of the JMDC database is that older adults aged ≥75 years in Japan are not included because of the different insurance systems in Japan. Additionally, it is important to note that the JMDC data was primarily sourced from corporate health insurance associations, which predominantly cover young to middle-aged workers and their families. These demographic limitations may affect the generalizability of the analysis results.⁵⁷ Because risk stratification by the RCRI was adequately reproduced in the population analyzed in this study and the deviation from previously reported postoperative event rates was small, the results of sex bias obtained in this study may have a certain degree of reliability, despite the limitation of being a retrospective cohort study. However, this study does not entirely rule out the possibility of sex differences within the RCRI framework. To determine the presence of such differences, further detailed analysis of specific groups will be necessary in future research.

Study Limitations

This was a retrospective study with several limitations, one of which was that due to the nature of the database, the surgeries analyzed did not include cases in which the patient’s age at the time of surgery was ≥75 years. Second, because the study was based on claims data, it is impossible to ascertain whether an event occurred before or after the surgery on the day of the surgery; therefore, such events were not included as outcomes. Consequently, there may be a bias in this study regarding the occurrence of cardiovascular events due to these factors. Furthermore, the analysis relied on information recorded for reimbursement, which may introduce bias regarding the reflection of actual clinical conditions. Disease definitions based solely on ICD-10 codes may exhibit higher sensitivity but lower positive predictive values, whereas definitions combining ICD-10 codes with medical practice codes may enhance positive predictive values at the expense of sensitivity.⁵¹ Additionally, the definition of MACE by ICD10 codes has not been standardized, and there is a problem of variation among studies; this study is no exception to this problem.⁵⁸ Third, creatinine values were based on periodic medical examinations within 1 year prior to surgery, and bias may exist. In addition, because a missing creatinine value indicates that the patient did not undergo a periodic medical examination within the past year, there may be a selection bias due to the exclusion of these cases from the analysis.

Conclusions

The validity of the RCRI and sex differences in the incidence of postoperative cardiovascular events were assessed using a large Japanese dataset. At this stage, no significant sex differences requiring clinical consideration were detected, and the results of this study support the validity of screening using the RCRI.

Acknowledgments

The authors thank all the staff and graduate students of the Department of Healthcare Information Management at the University of Tokyo Hospital for providing an opportunity to continue this research. This work was supported by Cross-ministerial Strategic Innovation Promotion Program (SIP) on “Integrated Health Care System” (Grant Number JPJ012425).

Disclosures

Y.K. belongs to the Artificial Intelligence and Digital Twin Development in Healthcare, Graduate School of Medicine, The University of Tokyo, which is an endowment department. However, the sponsors had no influence over the interpretation, writing, or publication of this work.

IRB Information

The Ethics Committee of the University of Tokyo Hospital (Approval No. 2024105NIe).

Data Availability

The data underlying the findings of this study are provided by JMDC Inc. but were accessed under a license exclusively for this research; therefore, they are subject to restrictions and are not publicly available. For inquiries about accessing the dataset utilized in this study, please contact JMDC (https://www.jmdc.co.jp).

Supplementary Files

Please find supplementary file(s);

https://doi.org/10.1253/circj.CJ-24-0846

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