Abstract
Background/Aims
Patients undergoing ERCP with chronic kidney disease (CKD), congestive heart failure (CHF), or liver cirrhosis (LC) often experience worse outcomes. It is unclear whether these are driven by procedure-related events or underlying comorbidity.
Methods
We analyzed the National Inpatient Sample to identify adult ERCP cases. High-risk comorbidities were defined as CKD, CHF, or LC. Primary outcomes were inpatient mortality and morbidity.
Results
Among 1,171,973 ERCP admissions, 267,739 (22.8%) were high-risk. Compared with lower-risk patients, high-risk patients had higher inpatient mortality (3.8% vs 0.8%, P < 0.001) and morbidity (71.8% vs 35.7%, P < 0.001). They also had longer LOS (8.5 vs 5.3 days, P < 0.001) and higher charges ($122,635 vs $81,984, P < 0.001). In adjusted models, high-risk comorbidities independently predicted mortality (OR 3.80, 95% CI 3.66–3.94) and morbidity (OR 3.22, 95% CI 3.18–3.26). LC was the strongest predictor of mortality (OR 4.53), while CHF was most associated with morbidity (OR 2.84). Predictive models showed good discrimination (AUC 0.76 for mortality; 0.73 for morbidity).
Conclusions
High-risk comorbidities are present in nearly one-quarter of ERCP admissions and strongly predict worse inpatient outcomes. Most adverse events are likely driven by underlying illness rather than ERCP-specific complications. Our validated predictive models may inform counseling, triage, and peri-procedural management.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1007/s10620-026-10026-4.
Keywords: Endoscopic retrograde cholangiopancreatography, ERCP outcomes, High-risk comorbidities, Chronic kidney disease, Congestive heart failure, Liver cirrhosis, Predictive modeling, Mortality, Morbidity, Risk stratification, National inpatient sample
Introduction
Endoscopic retrograde cholangiopancreatography (ERCP) is a cornerstone intervention for a range of pancreaticobiliary disorders, including choledocholithiasis, pancreatitis, malignant and benign biliary obstruction, and bile duct injury [1, 2]. Compared with diagnostic endoscopy, ERCP is technically more complex, often requires deep sedation, and carries a higher risk of adverse events such as pancreatitis, hemorrhage, perforation, and cardiopulmonary instability [3–6]. These risks are particularly relevant in patients with significant chronic comorbidities, who frequently require ERCP for urgent or complex indications.
Chronic kidney disease (CKD), congestive heart failure (CHF), and liver cirrhosis (LC) represent systemic conditions marked by inflammation, metabolic derangements, and reduced physiologic reserve. Each has been independently associated with higher perioperative morbidity and mortality across a wide range of invasive procedures [7–9]. Because of overlapping pathophysiology and increased likelihood of hepatobiliary disease, patients with these comorbidities are disproportionately represented among those needing ERCP.
Prior work has largely focused on cirrhosis in isolation, consistently demonstrating increased post-ERCP complications and mortality, particularly in decompensated disease [10–12]. Meta-analyses report complication rates approaching 15–16% in cirrhotic patients, with sepsis, bleeding, and hepatic decompensation being particularly common [13]. By contrast, CHF and CKD, despite their high prevalence and their well-established impact on perioperative outcomes, remain understudied in the ERCP setting. Furthermore, most available studies are retrospective or predate the widespread adoption of ICD-10 coding, involve modest sample sizes, and do not account for the frequent coexistence of multiple comorbidities [14, 15].
These gaps limit our ability to provide accurate risk stratification and patient counseling in real-world practice. In contemporary hospital settings, medically complex patients often present with more than one of these conditions, compounding their vulnerability to adverse outcomes. It is therefore clinically important to examine their combined impact. Modern inpatient datasets, such as the Nationwide Inpatient Sample (NIS), together with ICD-10 coding, allow for improved precision in identifying comorbidities, procedural indications, and complications [16, 17].
The present study sought to use a nationally representative cohort to evaluate the impact of CKD, CHF, and LC (individually and in combination) on inpatient outcomes following ERCP. Our objectives were twofold: first, to assess the association of these comorbidities with inpatient mortality, morbidity, length of stay, and hospital resource utilization; and second, to develop and internally validate predictive models for adverse outcomes. By integrating multiple high-risk conditions into a unified analysis, we aimed to better reflect real-world populations, clarify whether adverse outcomes reflect comorbidity burden versus ERCP-specific complications, and provide practical tools for pre-procedure counseling, triage, and peri-procedural management.
Methods
Data Source
We analyzed the Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) from 2016 to 2022 [16]. The NIS captures approximately 20% of all inpatient discharges across U.S. community hospitals and is weighted to generate nationally representative estimates. More than 40 million hospitalizations are included annually, with patient demographics, hospital characteristics, diagnoses, procedures, outcomes, and resource utilization abstracted from discharge data. Adult patients undergoing ERCP were identified using International Classification of Diseases, 10th Revision, Clinical Modification and Procedure Coding System (ICD-10-CM/PCS) codes (Supplemental Fig. 1).
Fig. 1.
Rates of individual complications in patients undergoing ERCP with and without high-risk comorbidities (chronic kidney disease, chronic heart failure, or liver cirrhosis). Complications include neurological, cardiovascular, respiratory, gastrointestinal, infectious, wound, hematological, venous thromboembolism, and renal categories
This study was exempt from institutional review board approval because it used de-identified, publicly available data. Reporting followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cohort studies [18].
Study Population
All adult patients (≥ 18 years) who underwent ERCP during an inpatient admission between January 2016 and December 2022 were eligible. High-risk comorbidities was defined as the presence of ≥ 1 of the following comorbidities: chronic kidney disease (CKD), congestive heart failure (CHF), or liver cirrhosis (LC). These were identified using validated ICD-10-CM codes (Supplemental Table 1). We chose this population since there is yet to be a broad characterization of higher risk populations which the literature cites amongst patients undergoing ERCP [7–9]. This analysis will also inform clinicians about the associated risk for patients with higher risk comorbidities.
Table 1.
Baseline characteristics of patients undergoing ERCP in the National Inpatient Sample (2016–2022), weighted for sample design, stratified by high-risk comorbidity status*
| Variable | No high-risk comorbidity n = 904,234 | High-risk comorbidity n = 267,739 | p-value |
|---|---|---|---|
| Demographics | |||
| Female sex | 540,244 (59.7) | 120,674 (45.1) | < 0.001 |
| Age, mean ± SD (y) | 57.6 ± 19.6 | 71.8 ± 13.7 | < 0.001 |
| Medicare | 375,294 (41.5) | 196,664 (73.5) | < 0.001 |
| Medicaid | 154,709 (17.1) | 22,194 (8.3) | < 0.001 |
| Private insurance | 295,164 (32.6) | 39,294 (14.7) | < 0.001 |
| Residence—large metropolitan | 495,749 (54.8) | 142,714 (53.3) | < 0.001 |
| Residence—small city/micropolitan | 271,674 (30.0) | 81,139 (30.3) | 0.01 |
| Residence—small town | 133,929 (14.8) | 43,139 (16.1) | < 0.001 |
| Elective admission | 64,079 (7.1) | 16,444 (6.1) | < 0.001 |
| Primary ERCP diagnosis | |||
| Pancreatic cancer | 75,669 (8.4) | 21,364 (8.0) | < 0.001 |
| Choledocholithiasis | 434,779 (48.1) | 135,344 (50.6) | < 0.001 |
| Chronic pancreatitis | 10,049 (1.1) | 14,119 (5.3) | < 0.001 |
| Comorbidities | |||
| Charlson comorbidity index, mean ± SD | 1.5 ± 2.4 | 4.2 ± 2.7 | < 0.001 |
| Type 2 diabetes | 187,109 (20.7) | 115,709 (43.2) | < 0.001 |
| Hyperlipidemia | 278,484 (30.8) | 133,889 (50.0) | < 0.001 |
| Obstructive sleep apnea | 52,294 (5.8) | 30,589 (11.4) | < 0.001 |
| Chronic obstructive pulmonary disease | 51,824 (5.7) | 37,234 (13.9) | < 0.001 |
| Class III + obesity | 63,269 (7.0) | 20,204 (7.5) | < 0.001 |
| Chronic kidney disease† | – | 152,649 (57.0) | < 0.001 |
| Chronic heart failure† | – | 117,609 (43.9) | < 0.001 |
| Liver cirrhosis† | – | 64,074 (23.9) | < 0.001 |
*High-risk comorbidity defined as presence of chronic kidney disease, chronic heart failure, or liver cirrhosis
†By study definition, high-risk group only
Values are n (%) unless otherwise indicated
Additional comorbidities (e.g., diabetes, chronic obstructive pulmonary disease, obstructive sleep apnea, gastroesophageal reflux disease) were recorded, and comorbidity burden was quantified using the Charlson Comorbidity Index [19]. Procedural indications, such as choledocholithiasis, pancreatic cancer, acute necrotizing pancreatitis, bile duct perforation, choleperitonitis, chronic pancreatitis, and ductal malignancy, were also identified through ICD-10-CM codes.
Demographic variables included age, sex, race/ethnicity, primary insurance (Medicare, Medicaid, private, self-pay), median household income by ZIP code, and hospital urban–rural location. Hospital-level characteristics included teaching status, bed size, and U.S. census region.
Outcome Measures
The primary outcomes were inpatient mortality, and composite morbidity, defined as the occurrence of at least one complication within cardiovascular, respiratory, infectious, hematologic, or renal categories. Complications were identified through ICD-10-CM codes (Supplemental Table 2). Secondary outcomes included length of stay (LOS), total hospital charges, and total costs. LOS was reported as mean days, and costs were adjusted for inflation using the U.S. Bureau of Economic Analysis Healthcare Price Index. All outcomes represent a wide range of complications which may have not just been related to the procedure, but also baseline patient risk profiles.
Statistical Analysis
Weighted national estimates were generated using HCUP discharge weights to reflect national-level outcomes. Baseline characteristics were compared between high- and lower-risk cohorts using chi-square tests for categorical variables and weighted Student’s t-tests for continuous variables.
Univariate logistic regression was performed to assess associations between high-risk comorbidities and outcomes. Clinically relevant factors and variables with P < 0.001 on univariate analysis were entered into multivariable binomial logistic regression models. Adjusted odds ratios (OR) with 95% confidence intervals (CI) were calculated for inpatient mortality and morbidity. Interaction terms were not included to assist clinical interpretation and the simplicity of the model. Additionally, to calculate a composite risk score multiply the odds ratios in the model by the status of that patient for each value since we assume each strata to be independently associated.
Predictive models were developed using multivariable logistic regression. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUC), and calibration was evaluated with Hosmer–Lemeshow goodness-of-fit testing. An 80/20 train-test split was applied for internal validation.
All analyses were performed in Python version 3.12 (Python Software Foundation, Wilmington, DE, USA) using pandas, polars, statsmodels, and scikit-learn packages. Two-sided P values < 0.05 were considered statistically significant.
Results
Patient Characteristics
A weighted total of 1,171,973 inpatient ERCP procedures were identified between 2016 and 2022. Of these, 267,739 (22.8%) patients were classified as high-risk, having at least one of the following comorbidities: CKD, CHF, or LC (Fig. 1).
Among high-risk patients, CKD was most prevalent (57.0%), followed by CHF (43.9%) and LC (23.9%). Compared with lower-risk patients, high-risk patients were significantly older (71.8 ± 13.7 vs. 57.6 ± 19.6 years), more frequently male (54.9% vs. 40.3%), and more often Medicare-insured (73.5% vs. 41.5%, all P < 0.001). They also had higher mean Charlson Comorbidity Index scores (4.2 ± 2.7 vs. 1.5 ± 2.4, P < 0.001) and higher rates of diabetes, hyperlipidemia, COPD, obstructive sleep apnea, and gastroesophageal reflux disease (Table 1). Rates of individual complications in patients undergoing ERCP with and without high-risk comorbidities are shown in Fig. 1. Trends in the prevalence of high-risk comorbidities among patients undergoing ERCP in the National Inpatient Sample from 2016–2022 are shown in Fig. 2.
Fig. 2.
Trends in prevalence of high-risk comorbidities among patients undergoing ERCP in the National Inpatient Sample from 2016–2022. High-risk comorbidity defined as ≥ 1 of chronic kidney disease, chronic heart failure, or liver cirrhosis
Univariate Outcomes
High-risk patients experienced significantly worse outcomes across all major domains (Table 2). Inpatient mortality was markedly higher in high-risk compared with lower-risk patients (3.8% vs. 0.8%, P < 0.001), and morbidity occurred in 71.8% vs. 35.7% (P < 0.001). Specific complications were also more common in the high-risk cohort, including cardiovascular complications (28.5% vs. 8.5%), infectious complications (30.6% vs. 14.6%), respiratory complications (14.4% vs. 4.0%), hematologic complications (10.4% vs. 3.7%), and renal complications (40.7% vs. 10.0%), with all comparisons statistically significant (P < 0.001). Resource utilization was likewise greater among high-risk patients: mean length of stay was 8.5 ± 9.6 days vs. 5.3 ± 5.9 days (P < 0.001) and mean total hospital charges were $122,635 vs. $81,984 (P < 0.001), although total hospital costs did not differ significantly between groups.
Table 2.
In-hospital outcomes of patients undergoing ERCP in the National Inpatient Sample (2016–2022), weighted for sample design, stratified by high-risk comorbidity status*
| Outcome | No high-risk comorbidity n = 904,234 | High-risk comorbidity n = 267,739 | p-value |
|---|---|---|---|
| Mortality | 7,469 (0.8) | 10,169 (3.8) | < 0.001 |
| Any morbidity | 322,919 (35.7) | 192,359 (71.8) | < 0.001 |
| Neurological complication | 7,939 (0.9) | 7,339 (2.7) | < 0.001 |
| Cardiovascular complication | 76,694 (8.5) | 76,174 (28.5) | < 0.001 |
| Respiratory complication | 36,024 (4.0) | 38,544 (14.4) | < 0.001 |
| Gastrointestinal complication | 78,289 (8.7) | 19,139 (7.1) | < 0.001 |
| Infectious complication | 131,944 (14.6) | 82,019 (30.6) | < 0.001 |
| Wound complication | 32,369 (3.6) | 31,849 (11.9) | < 0.001 |
| Hematological complication | 33,309 (3.7) | 27,814 (10.4) | < 0.001 |
| Venous thromboembolism | 14,539 (1.6) | 8,044 (3.0) | < 0.001 |
| Renal complication | 90,684 (10.0) | 108,959 (40.7) | < 0.001 |
| Resource utilization | |||
| Length of stay, mean ± SD (days) | 5.3 [1.3, 9.2] | 8.5 [2.3, 14.7] | < 0.001 |
| Total cost, mean ± SD (USD) | 30,939 ± 52,624 | 31,426 ± 54,470 | 0.06 |
| Total charges, mean ± SD (USD) | 81,984 ± 96,368 | 122,635 ± 192,900 | < 0.001 |
*High-risk comorbidity defined as presence of chronic kidney disease, chronic heart failure, or liver cirrhosis
Values are n (%) unless otherwise indicated
Multivariable Analyses
In adjusted models (Tables 3 and 4), high-risk comorbidities remained the strongest predictor of poor outcomes. High-risk patients had nearly fourfold increased odds of inpatient mortality (OR 3.80, 95% CI 3.66–3.94) and more than threefold increased odds of morbidity (OR 3.22, 95% CI 3.18–3.26). When examined individually, LC conferred the greatest mortality risk (OR 4.53), while CHF was most strongly associated with morbidity (OR 2.84). Other significant predictors of mortality included advanced age, pancreatic cancer, acute necrotizing pancreatitis, bile duct perforation, choleperitonitis, and ductal cancer. Conversely, female sex, morbid obesity, and elective or diagnostic ERCP were associated with lower mortality risk.
Table 3.
Multivariable logistic regression for in-hospital mortality among patients undergoing ERCP (NIS 2016–2022, weighted design; AUC = 0.75)
| Variable | OR (95% CI) | p-value |
|---|---|---|
| Age (per 10-year increase) | 1.51 (1.47–1.54) | < 0.05 |
| Female sex | 0.87 (0.84–0.90) | < 0.05 |
| Type 2 diabetes | 0.87 (0.84–0.90) | < 0.05 |
| Morbid obesity | 0.91 (0.84–0.98) | < 0.05 |
| High-risk comorbidity group | 3.80 (3.66–3.94) | < 0.05 |
| Chronic kidney disease | 1.65 (1.59–1.72) | < 0.05 |
| Chronic heart failure | 2.38 (2.29–2.48) | < 0.05 |
| Liver cirrhosis | 4.53 (4.34–4.73) | < 0.05 |
| Elective admission | 0.86 (0.80–0.93) | < 0.05 |
| Pancreatic cancer | 1.82 (1.74–1.92) | < 0.05 |
| Choledocholithiasis | 1.27 (1.22–1.31) | < 0.05 |
| Chronic pancreatitis | 0.79 (0.72–0.86) | < 0.05 |
| Acute necrotizing pancreatitis | 3.90 (3.52–4.32) | < 0.05 |
| Bile duct perforation | 1.86 (1.34–2.57) | < 0.05 |
| Choleperitonitis | 3.20 (2.70–3.78) | < 0.05 |
| Duct cancer | 2.05 (1.63–2.57) | < 0.05 |
Table 4.
Multivariable logistic regression for in-hospital morbidity among patients undergoing ERCP (NIS 2016–2022, weighted design; AUC = 0.73)
| Variable | OR (95% CI) | p-value |
|---|---|---|
| Age (per 10-year increase) | 1.68 (1.67–1.68) | < 0.05 |
| Female sex | 0.88 (0.87–0.89) | < 0.05 |
| Type 2 diabetes | 1.20 (1.19–1.21) | < 0.05 |
| Chronic obstructive pulmonary disease | 1.06 (1.04–1.08) | < 0.05 |
| Morbid obesity | 1.14 (1.12–1.16) | < 0.05 |
| High-risk comorbidity group | 3.22 (3.18–3.26) | < 0.05 |
| Chronic kidney disease | 2.54 (2.50–2.58) | < 0.05 |
| Chronic heart failure | 2.84 (2.79–2.88) | < 0.05 |
| Liver cirrhosis | 2.26 (2.22–2.31) | < 0.05 |
| Elective admission | 0.93 (0.91–0.94) | < 0.05 |
| Diagnostic ERCP | 0.83 (0.81–0.85) | < 0.05 |
| Pancreatic cancer | 0.96 (0.94–0.97) | < 0.05 |
| Choledocholithiasis | 0.84 (0.83–0.85) | < 0.05 |
| Chronic pancreatitis | 0.81 (0.79–0.82) | < 0.05 |
| Acute necrotizing pancreatitis | 2.33 (2.24–2.43) | < 0.05 |
| Bile duct perforation | 4.26 (3.80–4.77) | < 0.05 |
| Choleperitonitis | 10.62 (9.70–11.64) | < 0.05 |
| Duct cancer | 1.02 (0.93–1.11) | 0.74 |
Predictors of morbidity were similar, with acute necrotizing pancreatitis, bile duct perforation, and choleperitonitis emerging as strong drivers of adverse outcomes.
Model Performance
The predictive models demonstrated good discrimination. The mortality model achieved an AUC of 0.76, while the morbidity model achieved an AUC of 0.73, with good calibration across risk strata. Internal validation with an 80/20 train-test split confirmed consistent performance.
Discussion
This large, nationally representative analysis demonstrates that high-risk comorbidities—specifically chronic kidney disease (CKD), congestive heart failure (CHF), and liver cirrhosis (LC)-are strongly associated with increased inpatient mortality and morbidity in patients undergoing ERCP. Nearly one-quarter of all ERCP admissions in the NIS carried at least one of these comorbidities, underscoring how commonly they intersect with biliary and pancreatic disease. Importantly, the adverse outcomes we observed reflect the overall vulnerability of these medically complex patients rather than a direct increase in classic ERCP-related complications such as pancreatitis, bleeding, or perforation.
The magnitude of association between high-risk comorbidities and adverse outcomes was striking. After adjustment, high-risk comorbidities conferred almost a fourfold higher risk of mortality and more than a threefold higher risk of morbidity compared with lower-risk patients. LC was the strongest predictor of mortality, consistent with prior literature showing heightened susceptibility to bleeding, sepsis, and hepatic decompensation after invasive procedures [10–13, 20]. CHF emerged as the most potent predictor of morbidity, which may be explained by fluid management challenges, hemodynamic instability, and frequent pulmonary comorbidities in this group [21]. These findings extend earlier single-comorbidity studies by integrating CKD, CHF, and LC into a unified high-risk definition that better mirrors real-world populations, where multiple chronic conditions commonly coexist.
The higher complication rates we observed should be interpreted with caution. The NIS does not isolate specific post-ERCP adverse events such as pancreatitis or perforation, and therefore the composite morbidity measure includes all inpatient complications recorded during the admission. As a result, the excess morbidity is likely driven by underlying illness and concurrent hospital events rather than ERCP itself. Indeed, in daily practice many high-risk patients undergo technically straightforward, uncomplicated ERCP without direct endoscopic complications. Our findings therefore do not suggest that ERCP is inherently unsafe in this population, but rather that these patients carry higher baseline risk and are more likely to experience adverse outcomes during the hospitalization in which ERCP is performed. This was reflected by the discrepancy between costs and charges, as insurers paid similar amounts between the control and high-risk population. While charges were on average higher in the high-risk comorbidity group cost was not statistically higher. This is likely because insurers pay a set negotiated rate for patients who undergo an ERCP to hospitals, and this analysis can further contextualize the difficulty that providers may have had with getting prior authorization to undergo the ERCP procedure.
The role of procedural indication and disease severity was also evident. Conditions such as acute necrotizing pancreatitis, bile duct perforation, and choleperitonitis were independently associated with markedly higher risks of both mortality and morbidity, reflecting the additive impact of acute systemic illness. Conversely, morbid obesity and female sex were associated with reduced mortality, findings consistent with the “obesity paradox” and sex-based outcome differences observed in other surgical and acute care settings [22, 23]. While the mechanisms remain uncertain, these associations highlight the complexity of risk prediction in diverse patient populations.
Our predictive models for mortality (AUC 0.76) and morbidity (AUC 0.73) demonstrated good discrimination and calibration. Incorporating comorbidity profiles into pre-procedural evaluation may improve risk stratification, guide triage to higher-resourced centers, and facilitate informed discussions with patients and families. High-risk patients may benefit from multidisciplinary care pathways, including pre-procedure optimization of fluid status, nutritional support, or closer monitoring in the peri-procedural period. These strategies are especially relevant as the population of medically complex patients requiring ERCP continues to grow.
This study has several strengths. It uses a large, nationally representative dataset with contemporary ICD-10 coding, enhancing generalizability and accuracy of comorbidity capture. The integrated high-risk definition reflects clinical reality more accurately than prior single-comorbidity analyses. Limitations include the retrospective design, reliance on administrative coding, and inability to assess long-term or post-discharge complications. We could not account for procedural details such as cannulation technique, sedation method, or operator experience, which may influence outcomes. Additionally, the high complication rate could be attributable to the presentation of high-risk comorbidities directly and their interaction which was not measured by this study. We also could not measure any possible confounding directly attributable to other facets to the population of patients with high-risk comorbidities. Finally, because the NIS does not reliably distinguish ERCP-specific complications from broader inpatient morbidity, causality cannot be inferred.
In conclusion, CKD, CHF, and LC are present in nearly one-quarter of ERCP inpatients and are independently associated with significantly worse inpatient outcomes although more targeted analyses are needed to determine the causal framework of patients with these comorbidities. While high-risk patients demonstrate higher mortality and morbidity, these outcomes largely reflect their underlying medical fragility rather than ERCP-specific complications. Our validated predictive models provide a framework for risk stratification and resource allocation. Prospective studies are warranted to refine these models and to develop targeted peri-procedural strategies for this vulnerable population.
Supplementary Information
Below is the link to the electronic supplementary material.
Author Contributions
A.D., S.K.A, N.A, E.W, M.F: Study concept, design, and drafting, critical review and approval of final manuscript. Z.I, K.A, Y.A: Data acquisition, analysis and interpretation, drafting the manuscript.
Funding
This research did not receive funding from any agency or institution.
Data Availability
No datasets were generated or analysed during the current study.
Declarations
Conflict of interest
S.K.A is a consultant for Merit Endoscopy, Boston Scientific, EndoscopySteris, Olympus, MicroTech, Endo-Therapeutics, Hemostasis, and Neurotronic and the recipient of research support from Cook Medical. M.F is a consultant for Boston Scientific, Cook Medical, XLumena Corp, and Neometrics.
Ethical approval
This study was exempt from IRB approval because it analyzed retrospective, de-identified inpatient admission data from the NIS.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
No datasets were generated or analysed during the current study.