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Requests for reprints should be addressed to Nathaniel Smilowitz, MD, MS, The Leon H. Charney Division of Cardiology, Department of Medicine, NYU Langone Health, NYU School of Medicine, 423 East 23rd Street, Room 12020-W, New York, NY 10010.
Leon H. Charney Division of Cardiology, Department of Medicine, New York University School of Medicine, New York, NYVeterans Affairs New York Harbor Health Care System, New York, NY
Frailty is an emerging risk factor for adverse outcomes. However, perioperative frailty assessments derived from electronic health records have not been studied on a large scale. We aim to estimate the prevalence of frailty and the associated incidence of major adverse cardiovascular events (MACE) among adults hospitalized for noncardiac surgery.
Methods
Adults aged ≥45 years hospitalized for noncardiac surgery from 2004-2014 were identified from the National Inpatient Sample. The validated Hospital Frailty Risk Score (HFRS) derived from International Classification of Diseases codes was used to classify patients as low (HFRS <5), medium (5-10), or high (>10) frailty risk. The primary outcome was MACE, defined as myocardial infarction, cardiac arrest, and in-hospital mortality. Multivariable logistic regression was used to estimate the adjusted odds of MACE stratified by age and HFRS.
Results
A total of 55,349,978 hospitalizations were identified, of which 81.0%, 14.4%, and 4.6% had low, medium, and high HFRS, respectively. Patients with higher HFRS had more cardiovascular risk factors and comorbidities. MACE occurred during 2.5% of surgical hospitalizations and was common among patients with high frailty scores (high HFRS: 9.1%, medium: 6.9%, low: 1.3%, P < .001). Medium (adjusted odds ratio [aOR] 2.05; 95% confidence interval [CI], 2.02-2.08) and high (aOR 2.75; 95% CI, 2.70-2.79) HFRS were associated with greater odds of MACE vs low HFRS, with the greatest odds of MACE observed in younger individuals 45-64 years (interaction P value < .001).
Conclusions
The HFRS may identify frail surgical inpatients at risk for adverse perioperative cardiovascular outcomes.
A validated risk score for frailty is associated with an increased risk for the composite of in-hospital mortality, acute myocardial infarction, or cardiac arrest after noncardiac surgery.
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The association between high frailty and surgical outcomes was observed across age groups, with greater odds of cardiac events observed in younger individuals.
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High frailty scores are associated with an increased likelihood of non-home discharge after noncardiac surgery.
Introduction
Each year, over 17 million noncardiac surgeries are performed in the United States, and older adults age ≥65 years constitute nearly half of all surgical inpatients.
Steiner CA, Karaca Z, Moore BJ, Imshaug MC, Pickens G. Surgeries in hospital-based ambulatory surgery and hospital inpatient settings, 2014. In: Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Statistical Brief #223. Rockville, Md: 2017.
Frailty, an aging-related state of decreased functional status and physiological reserve, is associated with poor health outcomes and may be an important risk factor for complications after noncardiac surgery.
Preoperative frailty screening tools have been developed to incorporate functional assessments such as gait speed, mobility tests, and cognitive evaluations.
Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: an observational study.
However, EHR-derived frailty scoring tools have not been applied on a large scale to predict surgical outcomes. Most prior studies did not specifically focus on cardiovascular outcomes, did not stratify by age or evaluate frailty in younger cohorts, and were limited to analyses on a single type of surgery.
The impact of frailty status on survival after transcatheter aortic valve replacement in older adults with severe aortic stenosis: a single-center experience.
The objective of this study was to estimate the prevalence of frailty using a scoring tool based on administrative data and determine associations between frailty scores and the incidence of perioperative major adverse cardiovascular events (MACE) among adults undergoing noncardiac surgery in the United States using a large, nationwide database.
Methods
Study Population
We identified hospitalizations from the Agency for Healthcare Research and Quality's (AHRQ) National Inpatient Sample (NIS), an all-payer administrative database that represents a 20% stratified sample of discharges from participating community hospitals in the United States.
In addition, the database used in this study is naturally de-identified without any patient identifiers, and therefore did not warrant external review from our local ethical committee or Institutional Review Board.
Adults aged 45 years and older who underwent noncardiac surgery between 2004 and 2014 were included if they had a principal International Classification of Diseases Ninth Revision (ICD-9) procedure code corresponding to a major therapeutic operating room procedure (Healthcare Cost and Utilization Project Procedure Class 4), as previously described.
The classification of procedures as diagnostic/therapeutic and major/minor is assigned by AHRQ based on the level of invasiveness and resource utilization for each procedure. Admissions with a primary procedure code for cardiac procedures, cardiac transplantations, bone marrow transplantations, ophthalmologic surgery, radiation therapy, dental surgery, and non-operating room procedures were excluded. Hospitalizations with a primary procedure code for the following noncardiac surgeries were included: breast, endocrine, otolaryngology, general, genitourinary, gynecologic, neurosurgery, obstetrics, orthopedic, skin and burn, thoracic, noncardiac transplant, and vascular surgery.
Frailty Assessment
Frailty was estimated using the previously validated Hospital Frailty Risk Score (HFRS).
Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: an observational study.
This risk score was initially derived using a cluster analysis of patients ≥75 years old discharged from National Health Service hospitals in England between 2013 and 2015. In this derivation study, patients were clustered by International Classification of Diseases, Tenth Revision (ICD-10) codes, length of stay, and hospital costs, and a frail cluster was identified based on the prevalence of pre-established frailty syndromes: cognitive impairment, functional dependence, falls and fractures, anxiety and depression, incontinence, pressure ulcers, and mobility problems (Supplementary Table 1, available online). Next, any ICD-10 diagnosis codes that were at least twice as common in the frail cluster than the remainder of the cohort were identified, and each diagnosis code was assigned a score proportional to how strongly it predicted inclusion in the frail cluster. In a validation cohort, increasing HFRS scores predicted higher 30-day mortality, length of stay, and 30-day readmission.
Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: an observational study.
To adapt this score to our database, we used a standard Center for Medicare and Medicaid Services crosswalk to convert ICD-10 codes associated with frailty to the equivalent ICD-9 codes. Each surgical inpatient was then assigned an HFRS based on ICD-9 diagnosis codes (Supplementary Table 2, available online). To characterize the relationship between HFRS and the study outcomes, patients were stratified into 3 cohorts by HFRS score, indicating low (<5), intermediate (5-10), and high (≥10) risk of frailty. Although the original derivation focused on an older cohort age >75 years with high disease prevalence, we applied this frailty score to a broader cohort of patients undergoing noncardiac surgery to evaluate associations with perioperative outcomes.
Outcomes
The primary endpoint for this study was perioperative MACE, defined as the in-hospital composite of acute myocardial infarction, cardiac arrest, or all-cause mortality during the index surgical hospitalization.
Secondary endpoints included the composite endpoint of death and acute myocardial infarction, and the individual endpoints of mortality, acute myocardial infarction, and cardiac arrest. Stroke was not included as a study endpoint, as ICD-9 codes reflecting neurological deficits contributing to frailty were included in the HFRS. In-hospital mortality was determined from the NIS discharge disposition. Acute myocardial infarction was defined based on ICD-9 diagnosis code for acute ST-segment elevation myocardial infarction (ICD-9 diagnosis codes 410.01 to 410.61, 410.81, and 410.91) and non-ST-segment elevation myocardial infarction (ICD-9 diagnosis code 410.71), as previously described.
Discharge disposition is systematically reported in the NIS database and was included as another clinically relevant study endpoint.
Statistical Analysis
Categorical variables were reported as percentages and compared using chi-square tests. Continuous variables were reported as means and compared using linear regression. Multivariable logistic regression was used to estimate the odds of adverse perioperative cardiovascular events, adjusted for demographics and comorbidities that were not integrated into the frailty scores (Appendix). The incidence of perioperative MACE was evaluated in cohorts characterized by low, medium, and high HFRS. Relationships between HFRS and outcomes were also evaluated in cohorts stratified by age (45-64 years, 65-74 years, ≥75 years). National estimates were generated by applying clustering and sampling weights, as per AHRQ guidance. All data are weighted, unless otherwise specified. Statistical analyses were performed using IBM SPSS 27 (IBM, Armonk, NY). All statistical tests are 2-sided, and statistical significance was defined as P < .05. The authors are prepared to share the raw data from the database that was used in all analyses for this study.
Patient and Public Involvement
This study is an analysis using a retrospective database and therefore, patients and the public were not directly involved in the study for this research in any way.
Results
Patient Characteristics
A total of 11,539,910 hospitalizations for noncardiac surgery among adults aged ≥45 years were identified, corresponding to 55,349,978 hospitalizations nationwide after applying sampling weights. Of these, patients in 44,818,874 (81.0%) hospitalizations were categorized as low frailty risk, 7,949,829 (14.4%) as medium frailty risk, and 2,562,935 (4.6%) as high frailty risk (Table 1, Figure 1). This corresponds to approximately 950,000 surgical hospitalizations each year associated with medium or high frailty risk in the United States. Patients with the highest-risk frailty scores were older, more frequently female, and had a greater burden of comorbidities and cardiovascular diseases, such as hypertension, coronary artery disease, and heart failure (Table 1). Compared with those with low or medium frailty, patients with high frailty scores were more likely to have an urgent surgical admission (elective admissions: high risk 18.1% vs medium risk 31.8% vs low risk 68.1%), and were more likely to undergo neurosurgery, orthopedic, or skin/breast surgery (Table 1).
Table 1Characteristics of Patients Undergoing Noncardiac Surgery, By Frailty Risk
Figure 1Incidence of major adverse cardiovascular events (MACE) after noncardiac surgery, by frailty score. The incidence of MACE in (A) patients undergoing noncardiac surgery and (B) the total number of surgical hospitalizations by frailty score as a continuous variable. The frailty risk score categories are highlighted in (A) as low (green), medium (yellow), and high (red) risk. In (A), the proportion of patients with MACE after noncardiac surgery increased with increasing frailty scores, but plateaus in the high frailty risk group. In (B), it is shown that most patients undergoing noncardiac surgery had low frailty risk scores.
Perioperative MACE occurred during 2.5% of hospitalizations for noncardiac surgery overall, with a higher incidence in patients with high (9.1%) and medium (6.9%) HFRS compared with those with low HFRS (1.3%, P < .001) (Table 2, Figure 1). After adjustment for demographics and clinical covariates (Appendix), medium HFRS (adjusted odds ratio [aOR] 2.05; 95% confidence interval [CI], 2.02-2.08) and high HFRS (aOR 2.75; 95% CI, 2.70-2.80) were associated with increased odds for perioperative MACE compared with those with low HFRS. Associations between HFRS and perioperative MACE were observed across age groups (Figure 2, Figure 3, and Supplementary Table 3, available online). The association between high HFRS and MACE was most striking in younger individuals (45-64 years: aOR 4.39; 95% CI, 4.23-4.56; 65-74 years: aOR 3.15; 95% CI, 3.06-3.23; ≥75 years: aOR 3.15; 95% CI, 3.08-3.22; interaction P value < .001) (Figure 2). Associations between HFRS and perioperative MACE were also observed in cohorts stratified by sex, diabetes mellitus, coronary artery disease, noncardiac surgery subtype, and elective or urgent surgical hospitalization (Supplementary Figures 1-, available online).
Table 2Outcomes and Discharge Disposition After Noncardiac Surgery, by Frailty Score
Low Risk (n = 44,818,874)
Medium Risk (n = 7,949,829)
High Risk (n = 2,562,935)
P Value
In-hospital outcomes
MACE (death, MI, or arrest)
1.3% (575,166)
6.9% (548,442)
9.1% (234,262)
< .001
Death or MI
1.2% (549,370)
6.6% (521,274)
8.6% (220,985)
< .001
All-cause mortality
0.8% (357,940)
4.8% (380,481)
6.3% (161,053)
< .001
Myocardial infarction
0.5% (226,451)
2.3% (178,909)
2.9% (74,823)
< .001
Cardiac arrest
0.2% (77,248)
0.9% (74,104)
1.2% (31,707)
< .001
Discharge disposition
Routine discharge home
62.9% (28,177,146)
30.4% (2,411,227)
14.1% (360,291)
< .001
Short-term hospital
0.6% (289,317)
1.7% (137,721)
2.0% (50,049)
< .001
Skilled nursing facility/ intermediate care facility
17.6% (7,862,504)
44.5% (3,532,288)
63.5% (1,627,428)
< .001
Home health care
18.0% (8,052,951)
18.4% (1,461,675)
13.9% (356,614)
< .001
Unknown
0.0% (6987)
0.1% (4512)
0.1% (2334)
< .001
MACE = major adverse cardiovascular event; MI = myocardial infarction.
Figure 2Adjusted odd ratios for risk of major adverse cardiovascular events (MACE), stratified by frailty and age. Plot of adjusted odds ratios for the risk of postoperative MACE in patients undergoing noncardiac surgery by frailty classification, overall, and stratified by age. The analysis was adjusted for age, sex, race, and multiple comorbidities that are listed in Supplementary Table 1. In both the overall and aged-stratified analysis, higher frailty risk scores were associated with an increasing risk for postoperative MACE. The highest adjusted odds ratios for the risk of postoperative MACE were found in patients aged 45-64 years. HFRS = Hospital Frailty Risk Score.
Figure 3Prevalence of major adverse cardiovascular events (MACE) by frailty risk, stratified by age. The prevalence of MACE and its individual components (death, acute myocardial infarction, and cardiac arrest) in patients undergoing noncardiac surgery are shown stratified by frailty score and age. The incidence of MACE and its individual components increased substantially in the medium- and high-risk frailty score groups. The prevalence of these outcomes also increased with age within the low and medium frailty risk groups, but not within the high frailty risk score group.
The incidence of the individual endpoints of the composite of MACE, including myocardial infarction, cardiac arrest, and all-cause mortality, were higher in patients with elevated HFRS (Table 2, Figure 3, and Supplementary Figure 5, available online). Patients with a high HFRS had the greatest odds for mortality (aOR 2.98; 95% CI, 2.92-3.04), myocardial infarction (aOR 2.12; 95% CI, 2.07-2.16), and cardiac arrest (aOR 3.05; 95% CI, 2.97-3.13) when compared with those with low HFRS (Supplementary Figure 6, Panels A-C, available online). Associations between HFRS and perioperative mortality, myocardial infarction, and cardiac arrest were also observed in cohorts stratified by age.
Supplementary Figure 5Incidence of outcomes in major adverse cardiovascular events (MACE) after noncardiac surgery, by frailty score. The purpose of this figure is to demonstrate the prevalence of (A) mortality, (B) myocardial infarction, and (C) cardiac arrest in patients undergoing noncardiac surgery (in black, left y-axis) and the total number of surgical hospitalizations during the study period (in red, right y-axis), by treating frailty as a continuous variable. These graphs demonstrate that the prevalence of mortality, myocardial infarction, and cardiac arrest increased with higher frailty scores, but plateaus in patients with high frailty risk scores (>10). The graphs also demonstrate that most patients undergoing noncardiac surgery had low frailty risk scores (<5).
Supplementary Figure 6Odds ratios for risk of outcomes in major adverse cardiovascular events (MACE), by frailty and age. The purpose of this figure is to plot the adjusted odds ratios for (A) the risk of mortality, (B) myocardial infarction, and (C) cardiac arrest in patients undergoing noncardiac surgery by frailty score, overall, and stratified by age. The analysis was adjusted for age, sex, race, and multiple comorbidities that are listed in Supplementary Table 1. In both the overall and age-stratified analysis, higher frailty risk scores were associated with an increasing risk for postoperative mortality, myocardial infarction, and cardiac arrest. The highest adjusted odds ratios were found in patients aged 45-64 years for all 3 outcomes.
Discharge disposition after hospitalization varied significantly by HFRS. Surgical hospitalizations with the highest HFRS were least likely to result in a discharge to home (high frailty 14.1%, medium frailty 30.4%, low frailty 62.9%; P < .001) and were more likely to be discharged to a skilled nursing or intermediate care facility (high frailty 63.5%, medium frailty 44.5%, low frailty 17.6%; P < .001) than those with lower frailty scores (Table 2). In all frailty groups, older adults were more likely than younger individuals to be discharged to a skilled nursing or intermediate care facility (Supplementary Figure 7, available online).
Supplementary Figure 7Disposition after noncardiac surgery by frailty score, stratified by age.
The purpose of this figure is to chart the differences in the disposition of patients after noncardiac surgery in each of the frailty risk score categories, stratified by age. The options for disposition include discharges to home, home with health care, short-term care hospital, skilled nursing/intermediate care facility (SNF/ICF), unknown, or death. There were more discharges to SNF/ICF and fewer discharges to home in the medium and high-risk frailty score groups. A similar trend in disposition was observed with older age groups within the frailty risk score categories.
In this analysis of a large, nationwide database of US surgical hospitalizations, nearly one-fifth of all patients undergoing noncardiac surgery were identified as frail, and those with higher frailty risk scores had higher risk for perioperative MACE, including myocardial infarction, cardiac arrest, and all-cause mortality. Frail patients were less likely to be discharged home after surgery and were more likely to require postoperative care in a skilled nursing or intermediate care facility. The findings from our study add to the growing body of literature that highlights the impact of frailty on perioperative outcomes, morbidity, and mortality. The HFRS provides a convenient, standardized approach to systematically identify frail surgical inpatients at risk of adverse outcomes, and has the potential to be an important tool for frailty assessments in the inpatient setting.
In our study, patients with high frailty scores were older and had a higher burden of comorbidities than those with lower scores. Still, frailty was independently associated with MACE after adjustment for relevant demographics and other comorbidities, in the overall cohort and across age strata. These findings suggest that frailty offers a unique measure of physiological capacity that is not captured by age alone. Although the comorbidity profiles of frail patients may differ with age, high frailty scores were associated with adverse events in all age groups. In fact, among younger patients in whom operative risks may be underestimated, frailty assessments may have particularly important prognostic value. Furthermore, recent studies have suggested that frailty may be superior to age when predicting adverse outcomes in patients undergoing noncardiac surgeries.
Therefore, assessment of frailty is an emerging component of the preoperative evaluation for adults across the age spectrum, and based on this and other studies, the HFRS may serve as a valuable tool in addition to other frailty assessments for risk stratification, regardless of age.
Frailty has traditionally been defined as a state of functional decline from both aging and disease-related changes over time. Recent studies suggest that frailty may represent a chronic disease state associated with systemic inflammation, leading to worsening morbidity among affected individuals.
Therefore, frailty may both directly contribute to and result from cardiovascular disease. Frailty is also associated with multimorbidity, and the development of frailty in patients with multiple chronic diseases may also lead to significant disabilities. Although high frailty risk scores were associated with an increased number of comorbidities in our study, frailty was associated with MACE even after robust covariate adjustment.
While the value of frailty assessment in preoperative risk stratification has been demonstrated, implementation challenges remain. Some frailty assessments are based on the phenotypic measures of frailty, such as weakness, weight loss, exhaustion, low physical activity, and slowed walking speed.
In contrast, inpatient-based frailty assessments, such as the Identification Seniors at Risk and Triage Risk Stratification tools, often focus on comorbidity burdens associated with declines in physiologic capability.
Other popular frailty scoring tools, such as the Clinical Frailty Scale, combine clinical judgment with accumulation of comorbidities and may be used in inpatient and outpatient settings. The Frailty Index by Rockwood et al is based on deficit accumulation model.
Integration of frailty assessments, like the HFRS, with other traditional risk stratification tools may optimize the approach to preoperative risk assessment in patients planned for noncardiac surgery.
Comparing three different measures of frailty in medical inpatients: multicenter prospective cohort study examining 30-day risk of readmission or death.
Beyond in-hospital cardiovascular complications of surgery, perioperative frailty assessments may also provide insights into the likely discharge disposition after noncardiac surgery.
In this analysis, nearly 64% of all patients with high frailty risk scores required discharge to short-term acute care, skilled nursing, or intermediate care facilities, vs <18% of patients with low frailty scores. The substantial differences in the need for placement in a skilled nursing or subacute rehabilitation center at discharge were observed by frailty risk score across all age strata. Ultimately, early interventions, such as prehabilitation, physical therapy, and rehabilitation in the perioperative period, may mitigate postoperative care needs. However, the efficacy of interventions targeted at patients with evidence of frailty prior to surgery requires additional investigation in prospective trials.
There are a few limitations in our analysis. First, the NIS is a large administrative inpatient database that is subject to errors in coding and misclassification. Second, the NIS lacks discrete clinical data such as physical examination findings, vital signs, body mass index, 6-minute walk tests, measures of grip strength, and laboratory values. Third, although the original HFRS score was described using ICD-10 codes, for the purpose of these analyses, ICD-10 codes were translated to corresponding ICD-9 codes. Not all ICD-10 codes had an equivalent ICD-9 code. Fourth, we did not include stroke in the primary composite endpoint for MACE, as some of the ICD-9 codes used for stroke were also included in the HFRS to reflect neurological deficits contributing to frailty, and the acuity or chronicity of neurologic findings could not be determined from diagnosis codes. Fifth, the threshold values for risk categories used in our analysis differ slightly from those originally described for the HFRS. However, the lower risk thresholds described herein better fit the distribution of frailty in our large, nationwide cohort of individuals age ≥45 years undergoing noncardiac surgery. Sixth, our analysis was limited to cases from 2004-2014, which may not capture contemporary practices in postsurgical care or outcomes. Seventh, although we report discharge disposition, we do not have data on the prehospital residential status, and therefore changes in residential status (eg, new admission to a nursing facility) could not be determined. Finally, the NIS does not distinguish between outpatient and inpatient diagnoses or present on admission status. While many of the diagnoses relevant to the HFRS were likely made prior to the surgical hospitalization, we are unable to exclude the possibility that some diagnoses were established after an adverse cardiovascular event. We are therefore unable to exclude associations by reverse causality using this dataset. Prospective studies are needed to evaluate the HFRS calculated from preadmission diagnoses at the time of presentation to confirm its potential utility as a preoperative risk stratification tool embedded in the EHR.
In this analysis of a large US database, nearly one-fifth of all patients undergoing noncardiac surgery had a combination of diagnoses indicative of at least moderate frailty defined by the HFRS. Higher frailty scores were associated with increased risks of perioperative MACE, myocardial infarction, cardiac arrest, and all-cause mortality independent of age and other comorbidities. Patients with high vs low HFRS were more likely to be discharged to acute care, skilled nursing, or intermediate care facilities after hospital discharge. While additional prospective studies are needed to validate these results, our findings suggest that the HFRS may identify frail surgical inpatients at risk for adverse perioperative cardiovascular outcomes.
Age Sex Race Tobacco use Obesity Hypertension Diabetes mellitus Coronary artery disease Peripheral vascular disease Pulmonary circulation disorders Valvular disease Any malignancy Any anemia Drug abuse Coagulopathy Rheumatoid arthritis/collagen vascular diseases Acquired immune deficiency syndrome Iron deficiency anemia Blood loss Hypothyroidism Liver disease Neurological disease Psychiatric disease Peptic ulcer disease Weight loss Hospital bed size Hospital location/teaching status Hospital regions Elective admission Surgery type
Steiner CA, Karaca Z, Moore BJ, Imshaug MC, Pickens G. Surgeries in hospital-based ambulatory surgery and hospital inpatient settings, 2014. In: Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Statistical Brief #223. Rockville, Md: 2017.
Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: an observational study.
The impact of frailty status on survival after transcatheter aortic valve replacement in older adults with severe aortic stenosis: a single-center experience.
Comparing three different measures of frailty in medical inpatients: multicenter prospective cohort study examining 30-day risk of readmission or death.
Conflicts of Interest: NRS is supported, in part, by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award Number K23HL150315.
Authorship: All authors have reviewed the manuscript and are in agreement about the submission for publication. ES: Methodology, formal analysis, investigation, writing – original draft, visualization; DB: Conceptualization, writing – review & editing; JSB: Conceptualization, writing – review & editing, supervision; NRS: Conceptualization, investigation, formal analysis, writing – review & editing, supervision, project administration.
All variables with P < .05.
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