Which scoring systems are useful for predicting the prognosis of lower gastrointestinal bleeding? Old and new

Abstract

Background

The incidence of lower gastrointestinal bleeding is on the rise, prompting the creation of various scoring systems to forecast patient’s outcomes. But there is no single unified scoring system and these scoring systems clinical data are small and not worldwide.

Aims

To evaluate how different scoring systems predict mortality and prolonged hospital stay (≥ 10 days).

Methods

A retrospective review was conducted on the medical records of 4417 patients who presented with hematochezia at the emergency department from January 2016 to December 2022. We evaluated the predictive accuracy of various scoring systems for 30-day mortality and prolonged hospital stay (≥ 10 days) by analyzing the areas under the receiver-operating characteristic curves, taking into account factors such as patient age, laboratory findings, and comorbidities (ABC); AIMS 65; Glasgow-Blatchford; Oakland; Rockall(pre-endoscopy); SHA₂PE; and CHAMPS scores.

Results

We analyzed data from 1000 patients (mean age 66 years, 56.1% men, mean hospital stay 9.4 days) with lower gastrointestinal bleeding confirmed by any other means including DRE, colonoscopy and CT. The 30-day mortality rate was 3.7%. The primary etiologies of lower gastrointestinal bleeding were identified as ischemic colitis and diverticular bleeding, accounting for 18.8% and 18.5% of cases, respectively. In terms of forecasting 30-day mortality, the AIMS 65, CHAMPS, and ABC scoring systems demonstrated superior performance (p < 0.001). For predicting prolonged hospital stay, the SHA2PE score exhibited the highest accuracy among all evaluated systems (p < 0.001).

Conclusions

The newly developed scoring systems demonstrated superior accuracy in forecasting outcomes for patients with lower gastrointestinal bleeding, and the results of this study demonstrate that these scoring systems can be applied in clinical practice.

Introduction

Acute lower gastrointestinal bleeding (LGIB) accounts for 20% of gastrointestinal bleeding cases, and more than 50% of patients with LGIB require hospitalization [1, 2]. Although the rate of upper gastrointestinal bleeding (UGIB) has decreased rapidly over the past 10 years [3], the incidence of LGIB has increased slightly, and a similar trend has been reported in Asia [4, 5].

The data regarding the treatment outcomes of LGIB in a randomized controlled design are scarce compared with those of acute UGIB, leading to lack of consensus on clinical practice regarding risk stratification in patients with LGIB, optimal time to endoscopy, appropriate hemoglobin levels, and choice of hemostatic intervention [6].

Several studies have evaluated the predictive performance of existing scoring systems for the prognosis of LGIB. These include ROCKALL (RS) (1996) [7]; Glasgow-Blatchford (GBS) (2000) [8]; albumin level < 3.0 mg/dL, international normalized ratio (INR) > 1.5, altered mental status, systolic blood pressure ≤ 90 mmHg, and age > 65 years (AIMS 65) (2011) [9]; Oakland (2017) [10]; Systolic pressure, Hemoglobin, Anticoagulant or Antiplatelet therapy, Pulse and Emergency room bleeding (SHA₂PE) (2018) [11]; age, blood test results, and comorbidities (ABC) (2021) [12]; and CHAMPS (2022) scores [13]. However, limited studies have directly compared the predictive performance of recently developed scoring systems with that of existing scoring systems. Therefore, in this study, we compared a previously widely used risk-scoring system for LGIB with a recently developed scoring system to assess mortality and predict prognosis.

Methods

Study participants

Between January 2016 and December 2022, patients of ≥ 19 years of age with hematochezia who visited the emergency department of Chungnam National University Hospital were retrospectively analyzed. Data on patient demographics (age, sex, and comorbidities), initial vital signs, and blood test results performed in the emergency department were collected. Patients with LGIB confirmed by any method, including digital rectal examination (DRE), computed tomography (CT), sigmoidoscopy, colonoscopy, or other diagnostic techniques, were included in this study. Patients discharged from the emergency department were excluded because hematochezia was not confirmed by any means. Patients were also excluded in case of no signs of LGIB or in case of UGIB, small bowel bleeding, or variceal bleeding.

For patients admitted with LGIB, computed tomography (CT), duodenoscopy, colonoscopy, and angiography were performed to confirm and classify the cause of LGIB. The ABC, AIMS 65, Oakland, SHA₂PE, GBS, RS (pre-endoscopy), and CHAMPS scores were calculated using the patient data. We used area under the receiver-operating characteristic curve (AUROC) to evaluate the performance of these scoring systems in predicting 30-day mortality and prolonged hospital stay in patients with LGIB.

The study protocol was approved by the Institutional Review Board of the Chungnam National University Hospital (IRB number: CNUH 2024-01-053). All procedures were performed in accordance with the ethical standards of the responsible committee and the Declaration of Helsinki and its later amendments. The requirement for informed patient consent was waived due to the retrospective nature of the analysis.

Outcomes and definitions

The primary outcome was to determine the scoring system that most accurately predicted 30-day all-cause mortality in patients hospitalized with LGIB. The secondary outcomes encompassed the evaluation of a scoring system’s ability to predict prolonged hospital stay, as well as the identification of risk factors linked to both 30-day mortality and long-term hospitalization. LGIB was characterized as hemorrhage occurring in the colon and rectal regions below the ileocecal valve, verified through colonoscopy and CT.

Prolonged hospital stay was categorized as any inpatient stay lasting 10 days or more, while the overall length of stay was measured from the moment of admission to the point of discharge.

Therapeutic interventions included endoscopic interventions, interventions through radiological procedures, and hemostasis through surgery.

Statistical analysis

Patient characteristics were analyzed using descriptive statistics, including median with range. The predictive performance was assessed by calculating the AUROC of each scoring system to identify the primary and secondary outcomes in patients with LGIB. To evaluate the comparative effectiveness of the different scoring systems, we employed DeLong’s test to analyze the AUROC.

To determine risk factors associated with 30-day mortality and prolonged hospital stay, we conducted logistic regression analyses. Initially, univariate logistic regression was employed to examine variables linked to all-cause mortality and prolonged hospital stays. The Hosmer-Lemeshow test was then applied to assess the validity of fit of these models. Subsequently, multivariate logistic regression was utilized to control for confounding effects among variables and to elucidate the relationships between individual factors and outcomes. A p-value of less than 0.05 was considered statistically significant. All data analyses were performed using IBM SPSS Statistics version 26.0 (IBM Corporation, Armonk, NY, USA).

Results

Patient characteristics

A total of 1,000 patients with hematochezia were enrolled in the study between January 2016 and December 2022. During the study period, 4,417 patients visited the emergency department for hematochezia, of whom 3,236 were discharged and 1,181 were hospitalized for LGIB. Among them, 181 were excluded based on the exclusion criteria (Fig. 1).

Fig. 1.

Study flow chart

The median patient age was 67 years, and 56.1% of the patients were men. The most common concomitant disease was cancer (18.8%), followed by renal failure (12.3%). Twenty% and 10.6% of the patients received antiplatelet and anticoagulant treatments, respectively, and 27% consumed non-steroidal anti-inflammatory drugs (NSAIDs). Unfortunately, 37 (3.7%) patients enrolled in the study died, of whom 24 (2.4%) had LGIB. Additionally, 13 patients (1.3%) died from causes other than LGIB. The median duration of stay for hospitalized patients was nine days. Fifty-four (5.4%) patients had an altered mental status upon admission to the emergency department (Table 1).

Table 1.

Baseline characteristics of the patients

Characteristic	No.
Total number	1000
Sex, n (%)
Male	561 (56.1)
Female	439 (43.9)
Age, median years (range)	67 (19–94)
Comorbidity, n (%)
Cancer	188 (18.8)
Chronic pulmonary obstructive disease	28 (2.8)
Heart failure	117 (11.7)
Liver cirrhosis	86 (8.6)
Renal failure	123 (12.3)
Medication, n (%)
Antiplatelet	200 (20)
Anticoagulant	106 (10.6)
Non-steroidal anti-inflammatory drugs	270 (27)
Mental status, n (%)
Alert	946 (94.6)
Altered	54 (5.4)
Mortality, n (%)
All-cause mortality in 30 days	37 (3.7)
Bleeding-related mortality	24 (2.4)
Hospitalization
Day, median (range)	9.42 (1–148)

Initial status

Initial vital tests performed in the emergency department showed a mean systolic blood pressure of 100 mmHg and heart rate of 101 beats/min. In the first blood test, the average hemoglobin level was 9.53 g/dL. Mean creatinine level, blood urea nitrogen (BUN) level, INR, and albumin level were 1.56 mg/dL, 29.5 mg/dL, 1.34, and 3.0 g/dL, respectively (Table 2).

Table 2.

Vital signs and laboratory test results at the emergency room

Parameters	Results
Vital signs (median)
Systolic blood pressure (mmHg)	100
Diastolic blood pressure (mmHg)	56
Heart rate (beats/min)	101
Laboratory test results
Hemoglobin, mean (g/dL)	9.53
Hematocrit, mean (%)	28.0
Platelet, median (µL)	169,000
Creatinine, median (mg/dL)	1.56
Blood urea nitrogen, median (mg/dL)	29.5
Albumin, median (g/dL)	3.0
International normalized ratio, median	1.34

Endoscopic results

Among the patients who underwent endoscopy, the most common cause of hematochezia was ischemic colitis (18.8%), followed by diverticular bleeding (18.5%), ulcer bleeding (10%), and cancer bleeding (7.5%) after polypectomy (7.4%) (Table 3).

Table 3.

Endoscopic results

Endoscopic findings	No. (%)
Ischemic colitis	188 (18.8)
Diverticulosis	185 (18.5)
Ulcer bleeding	100 (10)
Cancer bleeding	75 (7.5)
Post-polypectomy bleeding	74 (7.4)
Ulcerative colitis	35 (3.5)
Colitis	33 (3.3)
Polyp	28 (2.8)
Angiodysplasia	11 (1.1)
Pseudomembranous colitis	4 (0.4)
Crohn’s disease	3 (0.3)
Subepithelial tumor	3 (0.3)
Arteriovenous malformation	3 (0.3)

Of the 1,000 patients, 256 were unable to undergo colonoscopy because of old age or poor general condition, which made it impossible for them to undergo bowel preparation. Of the patients who underwent endoscopy, 188 underwent endoscopic bleeding control and 18 underwent transarterial embolization (Table 4).

Table 4.

The proportion of patients who underwent endoscopy and intervention

Intervention	No. (%)
Intervention
Endoscopic bleeding control	188 (18.8)
Transarterial embolization	18 (1.8)

Comparison of scores for predicting prognosis in patients with LGIB

The AIMS 65 (AUROC, 0.844), CHAMPS (AUROC, 0.842), and ABC (AUROC, 0.837) scores were superior to the GBS (AUROC, 0.780), SHA₂PE (AUROC, 0.761), RS (AUROC, 0.759), and Oakland (AUROC, 0.735) scores in predicting 30-day mortality (Fig. 2). For prolonged hospital stay prediction, the SHA₂PE (AUROC, 0.721) and AIMS 65 (AUROC, 0.713) scoring systems were superior to all other scoring systems (Fig. 3). Also calibration using the Hosmer-Lemeshow test resulted in a chi-square statistic of 4.192 (8 degrees of freedom, p-value 0.839) for 30 day mortality, a chi-square statistic of 7.176 (8 degrees of freedom, p-value 0.518). This indicates good agreement between the model’s predicted probabilities and observed outcomes (Figs. 4 and 5).

Fig. 2.

Prediction of 30-day mortality. ABC, age, blood test results, and comorbidities; GBS, Glasgow-Blatchford score; AIMS 65; SHA2PE; CHAMPS

Fig. 3.

Prolonged hospital-stay prediction. ABC, age, blood test results, and comorbidities; GBS, Glasgow-Blatchford score; AIMS 65,; SHA2PE; CHAMPS3

Fig. 4.

Hosmer-Lemeshow test for 30 day mortality. df: degree of freedom. sig: significance

Fig. 5.

Hosmer-Lemeshow test for Prolonged hospital-stay. df: degree of freedom. sig: significance

Correlated factors with all-cause mortality in 30 days

The data on the factors related to all-cause mortality at 30 days were collected from each scoring system. Each factor was selected based on the following: antiplatelet agents and anticoagulants from the SHA₂PE score, blood pressure and heart rate from the RS, comorbidities from the ABC score, and blood tests based on the AIMS 65. Univariate logistic regression analysis confirmed the following variables: albumin (≤ 3.0 g/dL), BUN (≥ 30 mg/dL), INR (> 1.50), systolic blood pressure (SBP;<100 mmHg), creatinine (> 1.5 mg/dL), heart rate (> 100 beats/min), platelet (≤ 1,000,000/µL), diastolic blood pressure (DBP; <60 mmHg), hematocrit (≤ 30.0%), hemoglobin (≤ 10.0 g/dL), cancer, and age (≥ 75 years). On multivariate analysis of factors related to 30-day mortality, cancer as an underlying disease, high BUN level (≥ 30 mg/dL), prolonged INR(> 1.50), and low albumin level (≤ 3.0 g/dL) were related (Table 5).

Table 5.

Logistic regression analyses results for risk factors of mortality from lower gastrointestinal bleeding

	Univariate analysis		Multivariate analysis
	OR (95% CI)	p-value	OR (95% CI)		p-value
Male sex	0.918 (0.475–1.774)	0.798
Age ≥ 75 years	2.362 (1.216–4.586)	0.009
Cancer	2.560 (1.292–5.070)	0.005	2.542 (1.057–6.118)	0.037
COPD	0.963 (0.127–7.285)	0.971
Renal failure	2.034 (0.908–4.557)	0.079
Heart failure	1.809 (0.776–4.218)	0.164
Liver cirrhosis	2.136 (0.865–5.273)	0.092
Antiplatelet	0.931 (0.403–2.151)	0.867
Anticoagulant	1.334 (0.508–3.500)	0.557
NSAIDs	1.001 (0.478–2.098)	0.997
SBP (< 100 mmHg)	7.723 (3.192–18.687)	< 0.001
DBP (< 60 mmHg)	3.671 (1.417–9.506)	0.004
Heart rate (> 100 beats/min)	4.968 (2.161–11.420)	< 0.001
Hemoglobin (≤ 10.0 g/dL)	2.757 (1.247–6.093)	0.009
Hematocrit (≤ 30.0%)	3.177 (1.382–7.306)	0.004
Platelet (≤ 1,000,000/µL)	4.184 (2.155–8.125)	< 0.001
Creatinine (> 1.5 mg/dL)	5.449 (2.796–10.620)	< 0.001
BUN (≥ 30 mg/dL)	13.399 (5.527–32.479)	< 0.001	5.413 (1.818–16.119)	0.002
INR (> 1.50)	8.507 (4.332–16.705)	< 0.001	5.321 (1.977–14.323)	< 0.001
Albumin (≤ 3.0 g/dL)	19.056 (4.558–79.675)	< 0.001	5.548 (1.088–28.282)	0.039

OR, odds ratio; CI, confidence interval; COPD, chronic obstructive pulmonary disease; NSAIDs, non-steroidal anti-inflammatory drugs; SBP, systolic blood pressure; DBP, diastolic blood pressure; BUN, blood urea nitrogen; INR, international normalized ratio

Correlated factors with prolonged hospital stay

Univariate logistic regression analysis was performed on variables associated with prolonged hospital stay, and the results confirmed the following variables: albumin (≤ 3.0 g/dL), SBP (< 100 mmHg), liver cirrhosis, platelet (≤ 1,000,000/µL), hemoglobin (≤ 10.0 g/dL), heart rate (> 100 beats/min), INR (> 1.50), hematocrit (≤ 30.0%), NSAIDs, DBP (< 60 mmHg), cancer, BUN (≥ 30 mg/dL), and creatinine (> 1.5 mg/dL). On multivariate analysis of factors related to prolonged hospital stay, underlying liver cirrhosis, history of NSAID intake, and low SBP (< 100 mmHg), hemoglobin (≤ 10.0 g/dL), platelet (≤ 1,000,000/µL), and albumin (≤ 3.0 g/dL) levels were related(Table 6).

Table 6.

Logistic regression analyses results for prolonged hospital stay from lower gastrointestinal bleeding

	Univariate analysis		Multivariate analysis
	OR (95% CI)	p-value	OR (95% CI)	p-value
Male sex	0.731 (0.547–0.978)	0.034
Age ≥ 75 years	1.384 (1.029–1.861)	0.031
Cancer	1.775 (1.264–2.492)	< 0.001
COPD	1.051 (0.441–2.504)	0.910
Renal failure	1.551 (1.029–2.340)	0.035
Heart failure	1.043 (0.667–1.631)	0.853
Liver cirrhosis	4.473 (2.843–7.037)	< 0.001	2.823 (1.579–5.045)	< 0.001
Antiplatelet	0.895 (0.619–1.294)	0.0554
Anticoagulant	1.278 (0.815–2.004)	0.285
NSAIDs	2.519 (1.851–3.426)	< 0.001	1.569 (1.087–2.263)	0.016
SBP (< 100 mmHg)	4.595 (3.361–6.282)	< 0.001	2.619 (1.742–3.938)	< 0.001
DBP (< 60 mmHg)	1.825 (1.321–2.523)	< 0.001
Heart rate (> 100 beats/min)	2.978 (2.193–4.044)	< 0.001
Hemoglobin (≤ 10.0 g/dL)	3.022 (2.174–4.201)	< 0.001	2.535 (1.104–5.822)	0.028
Hematocrit (≤ 30.0%)	2.754 (1.987–3.817)	< 0.001
Platelet (≤ 1,000,000/µL)	3.439 (2.486–4.757)	< 0.001	1.581 (1.046–2.390)	0.030
Creatinine (> 1.5 mg/dL)	1.589 (1.123–2.249)	0.009
BUN (≥ 30 mg/dL)	1.770 (1.306–2.399)	< 0.001
INR (> 1.50)	2.936 (2.018–4.273)	< 0.001
Albumin (≤ 3.0 g/dL)	6.888 (4.816–9.851)	< 0.001	4.095 (2.611–6.423)	< 0.001

OR, odds ratio; CI, confidence interval; COPD, chronic obstructive pulmonary disease; NSAIDs, non-steroidal anti-inflammatory drugs; SBP, systolic blood pressure; DBP, diastolic blood pressure; BUN, blood urea nitrogen; INR, international normalized ratio

Discussion

Several scoring systems have been developed over the past few decades [14]. The latest scoring system included in this study is CHAMPS, which was established in 2022 [13]. Each system has different scoring components and primary endpoints. Thus, no scoring system outperforms the others.

AIMS 65 score include the following factors: albumin level, INR, age, SBP, and mental status. The data on these factors can be collected instantly as patients arrive at emergency department even if their mentality is altered and they cannot speak. All these factors are routinely checked in patients with hematochezia. Other scoring systems include factors that can be revealed by patient medical history such as history of hospital admission (Oakland), medications (SHA₂PE and CHAMPS), and other illnesses such as cancer, heart failure, liver cirrhosis, and renal failure. These factors are difficult to determine because some patients do not know the medications that they are consuming or whether they have cancer, heart failure, liver cirrhosis, or renal failure. However, once the data on patient history factors are collected, they are extremely useful in predicting all-cause mortality and prolonged hospital stays.

The RS, GBS, and AIMS 65 scores were developed in 1996, 2000, and 2011, respectively, as scoring systems to predict the prognosis of UGIB. LGIB lacks a risk-stratifying scoring system compared with UGIB, and existing scoring systems have not been adequately validated externally or adopted in widespread clinical practice. However, a scoring system for risk assessment in patients with LGIB has recently been developed. The Oakland, SHA₂PE, ABC, and CHAMPS scores were developed in 2017, 2018, 2021, and 2022, respectively, in an international multicenter study.

In this study, the AIMS 65 (AUROC, 0.844), CHAMPS (AUROC, 0.842), and ABC scores (AUROC, 0.837) were similar to the other scores in predicting 30-day mortality (all P < 0.001). Recently, Laursen et al. [12]. compared the ABC, AIMS 65, GBS, and Oakland scores in predicting mortality in patients with LGIB. The ABC score (AUROC, 0.84) was more closely associated with mortality than the AIMS 65 (AUROC, 0.75), GBS (AUROC, 0.74), and Oakland (AUROC, 0.69) scores. Compared to a previous study [12], our findings showed that AIMS 65 depicted the most accurate results, followed by the CHAMPS score, which was developed most recently.

In addition, we excluded the Strate, BLEED, and NOBLADS scores, which are scoring systems for risk stratification of patients with lower GI bleeding. This was because previous large lower GI bleeding cohort studies found the AIMS65 score to be more closely associated with mortality than scoring systems such as Strate, BLEED, and NOBLADS [10].

Multivariate logistic regression analysis of variables related to all-cause mortality within 30 days showed that BUN, INR, albumin, and cancer were statistically significant variables. The AIMS 65 score includes most of the above variables, excluding age, BUN, and state of consciousness; therefore, the AIMS 65 score may have been the most accurate predictor of mortality in this study. The ABC score includes the American Society of Anesthesiologists score and comorbidities, and the CHAMPS score includes the Charlson comorbidity index. The application of the severity of comorbidities as a score for risk stratification could have contributed to predicting the mortality [15, 16]; however, calculation may be difficult because of many variables. While AIMS 65 offers simplicity and rapid applicability, CHAMPS and ABC scores provide a more comprehensive risk assessment. The choice between these scores in clinical practice may depend on the specific clinical setting, available resources, and the need for rapid versus comprehensive assessment. Future research could focus on developing a score that combines the simplicity of AIMS 65 with the comprehensiveness of CHAMPS and ABC, potentially leading to an even more accurate and clinically useful tool for LGIB risk stratification.

A risk-scoring system that allows accurate triage in the initial assessment can avoid unnecessary hospitalizations among patients with LGIB. Therefore, the SHA₂PE score was developed to reduce unnecessary hospitalizations by identifying low-risk patients visiting the emergency department. In this study, the SHA₂PE score was the only risk stratification score used to score antiplatelet and anticoagulant drugs. This study confirmed that the SHA₂PE score performed better than the other scores in predicting the outcome of a prolonged hospital stay. Recently, Cerruti et al. [17]. externally validated the SHA₂PE scoring system. In predicting the need for intervention, the SHA₂PE score had a sensitivity, specificity, and AUROC of 73%, 82%, and 0.77 (95% confidence interval: 0.70–0.84), respectively [17]. Antiplatelet and anticoagulant drugs were not predictors of long-term hospitalization. However, patients with comorbidities such as cardiovascular disease or stroke may have a longer hospital stay because they are under medical observations while taking antiplatelet and anticoagulant drugs after the bleeding has improved. The SHA₂PE score’s superior performance in predicting prolonged hospital stays is likely due to its comprehensive yet focused approach to risk assessment in LGIB patients. Its alignment with clinical utility makes it a valuable tool for improving patient care and healthcare resource management in this specific patient population.

Multivariate logistic regression analyses showed that prolonged hospital stay was a statistically significant variable for albumin, hemoglobin, liver cirrhosis, and SBP. Although the SHA₂PE score was more accurate than the AIMS 65 score in predicting prolonged hospital stay, the AIMS 65 score showed the second-highest accuracy. This is because the AIMS 65 score include albumin and SBP and the first and second highest variable odds ratios of 4.095 and 2.619, respectively.

This study has several limitations. First, it was a retrospective study conducted at a single institution. The results of this study may differ in other hospitals with different patient demographics. Therefore, generalization of the results of this study to other clinical situations may be limited. However, the large sample size and 7-year consecutive patient data of this study can avoid selection bias. Second, this study excluded patients with LGIB among hospitalized patients for other reasons. Only patients who visited the emergency department because of LGIB were included in this study. Therefore, this study may not be applicable for the prognostic prediction of LGIB in hospitalized patients for other reasons. Lack of cancer staging data for patients with malignancies can be another limitation. While we included cancer as a comorbidity, we were unable to obtain comprehensive staging information, particularly for patients diagnosed at other institutions. Cancer stage can significantly impact mortality rates, and the absence of this data may affect the interpretation of our results. Future studies should aim to incorporate cancer staging data to provide a more nuanced analysis of its impact on outcomes in patients with lower gastrointestinal bleeding.

This study updated the previous research with a larger population and included a newly developed CHAMPS scoring system. Since the publication of the CHAMPS score in 2022 [13, 18], few studies have compared or included the newly developed scoring system with previous scoring systems. This study confirmed the predictive ability of a recently developed scoring system for LGIB.

In conclusion, the recently developed ABC, CHAMPS, and AIMS 65 scores outperform previous scoring systems in predicting mortality among patients with LGIB. The SHA₂PE score was the most accurate predictor of long-term hospitalization. However, improving prognosis in the future is difficult unless new strategies are developed to reduce mortality in patients with LGIB. Therefore, a scoring system that accurately predicts risk is required to develop a strategy, and this study will help in LGIB treatment in the future. Moreover, a multicenter study is required to validate the results of the present study in different clinical settings.

Author contributions

All authors contributed to the study’s conception and design. Material preparation, data collection, and analyses were performed by Ku Bean Jeong, Hee Seok Moon, Kyung Ryun In, Sun Hyung Kang, Jae Kyu Sung, and Hyun Yong Jeong. The first draft of the manuscript was written by Ku Bean Jeong, and all authors commented on the previous versions of the manuscript. All authors have read and approved the final version of the manuscript.

Funding

none.

Data availability

The datasets generated and/or analysed during the current study are not publicly available due to privacy concerns and the presence of potentially identifying patient information. But are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

: The study protocol was approved by the Institutional Review Board of the Chungnam National University Hospital (IRB number: CNUH 2024-01-053). All procedures were performed in accordance with the ethical standards of the responsible committee and the Declaration of Helsinki and its later amendments. The requirement for informed patient consent was waived by Institutional Review Board of the Chungnam National University Hospital due to the retrospective nature of the analysis.

Consent to publish

Not applicable.

Competing interests

The authors declare no competing interests.