Clinical Features and Factors Affecting Postoperative Mortality for Obstructive Acute Mesenteric Ischemia in China: A Hospital- Based Survey

D-Dimer in Acute Mesenteric Venous Thrombosis: A Prospective Case-Control International Multicenter Study

BACKGROUND

Acute mesenteric venous thrombosis (MVT) is rarely suspected as primary diagnosis in emergency departments and still carries an in-hospital mortality rate of above 20%.

OBJECTIVES

The aim of this study was to find differences in clinical and laboratory markers between patients with acute MVT and a control group of suspected but confirmed as not having any type of acute mesenteric ischaemia (AMI).

DESIGN

Data was retrieved from the AMESI (Acute MESenteric Ischaemia) study. This international, multicenter prospective case-control study from 32 sites collected data on patients with suspected AMI during a 10-month period.

METHODS

Independent factors associated with acute MVT were evaluated in a multivariable logistic regression analysis and expressed as odds ratios (OR) with 95% confidence intervals (CI).

RESULTS

D-dimer was not significantly higher in MVT (n = 73) compared to non-AMI (n = 287) patients (median 7.0 mg/L vs 4.5 mg/L, P = .092). After entering BMI, atherosclerotic disease, history of venous thromboembolism, CRP, and D-dimer as covariates in a multi-variable logistic regression analysis, absence of atherosclerotic disease (OR 0.096, 95% CI 0.011-0.84; P = .034) and elevated D-dimer (OR 2.59/one SD increment, 95% CI 1.07-6.28; P = .034) were associated with MVT. The discriminative ability of D-dimer for MVT as assessed by area under the curve in the receiver operating characteristics analysis was 0.63 (95% CI 0.49-0.78).

CONCLUSION

Elevated D-dimer was associated with MVT, but the discriminative ability of D-dimer was poor. There is an urgent need to find a more accurate plasma biomarker for this condition.

TRIAL REGISTRATION

NCT05218863 (registered 19.01.2022).

A method for predicting mortality in acute mesenteric ischemia: Machine learning

BACKGROUND

This study aimed to develop and validate an artificial intelligence model using machine learning (ML) to predict hospital mortality in patients with acute mesenteric ischemia (AMI).

METHODS

A total of 122 patients diagnosed with AMI at Sakarya University Training and Research Hospital between January 2011 and June 2023 were included in the study. These patients were divided into a training cohort (n=97) and a validation cohort (n=25), and further categorized as survivors and non-survivors during hospitalization. Serum-based laboratory results served as features. Hyperfeatures were eliminated using Recursive Feature Elimination (RFE) in Python to optimize outcomes. ML algorithms and data analyses were performed using Python (version 3.7).

RESULTS

Of the patients, 56.5% were male (n=69) and 43.5% were female (n=53). The mean age was 71.9 years (range 39-94 years). The mortality rate during hospitalization was 50% (n=61). To achieve optimal results, the model incorporated features such as age, red cell distribution width (RDW), C-reactive protein (CRP), D-dimer, lactate, globulin, and creatinine. Success rates in test data were as follows: logistic regression (LG), 80%; random forest (RF), 60%; k-nearest neighbor (KN), 52%; multilayer perceptron (MLP), 72%; and support vector classifier (SVC), 84%. A voting classifier (VC), aggregating votes from all models, achieved an 84% success rate. Among the models, SVC (sensitivity 1.0, specificity 0.77, area under the curve (AUC) 0.90, Confidence Interval (95%): (0.83-0.84)) and VC (sensitivity 1.0, specificity 0.77, AUC 0.88, Confidence Interval (95%): (0.83-0.84)) were noted for their effectiveness.

CONCLUSION

Independent risk factors for mortality were identified in patients with AMI. An efficient and rapid method using various ML models to predict mortality has been developed.

The Diagnostic Value of Biomarkers in Acute Mesenteric Ischaemia Is Insufficiently Substantiated: A Systematic Review

OBJECTIVE

There is an urgent need for accurate biomarkers to support timely diagnosis of acute mesenteric ischaemia (AMI) and thereby improve clinical outcomes. With this systematic review, the aim was to substantiate the potential diagnostic value of biomarkers for arterial occlusive AMI.

DATA SOURCES

The Pubmed, Embase, and the Cochrane Library electronic databases were searched.

REVIEW METHODS

A systematic review of the literature has been conducted to define the potential diagnostic value of biomarkers for arterial occlusive AMI. All studies including ≥ 10 patients describing biomarkers for macrovascular occlusive AMI between 1950 and 17 February 2023 were identified within the Pubmed, Embase, and the Cochrane Library electronic databases. There were no restrictions to any particular study design, but letters and editorials were excluded. The QUADAS-2 tool was used for the critical appraisal of quality. The study protocol was registered on Prospero (CRD42021254970).

RESULTS

Fifty of 4334 studies were eligible for inclusion in this review. Ninety per cent of studies were of low quality. A total of 60 biomarkers were identified, with 24 in two or more studies and 15 in five or more studies. There was variation in reported units, normal range, and cut off values. Meta-analysis was not possible due to study heterogeneity. Biomarkers currently recommended by the European Journal of Vascular and Endovascular Surgery, European Society for Trauma and Emergency Surgery 2016, and World Society of Emergency Surgery 2017 guidelines also had heterogeneous low quality data for use in the diagnosis of AMI.

CONCLUSION

This systematic review demonstrates high heterogeneity and low quality of the available evidence on biomarkers for arterial occlusive AMI. No clinical conclusions can be drawn on a biomarker or combination of biomarkers for patients suspected of arterial occlusive AMI. Restraint is advised when rejecting or determining AMI solely based on biomarkers.

Factors that may affect the outcome of acute occlusive mesenteric ischemia. A single-center study

BACKGROUND

Acute mesenteric ischemia is a rare but lethal disease. Acute occlusive mesenteric ischemia consists of mesenteric artery embolism, mesenteric artery thrombosis, and mesenteric vein thrombosis. This study aimed to investigate the factors that may affect the outcome of acute occlusive mesenteric ischemia.

METHODS

Data from acute occlusive mesenteric ischemia patients admitted between May 2016 and May 2022 were reviewed retrospectively. Patients were divided into 2 groups according to whether complications(Clavien‒Dindo ≥ 2) occurred within 6 months of the first admission. Demographics, symptoms, signs, laboratory results, computed tomography angiography features, management and outcomes were analyzed.

RESULTS

59 patients were enrolled in this study. Complications(Clavien‒Dindo ≥ 2) occurred within 6 months of the first admission in 17 patients. Transmural intestinal necrosis, peritonitis, white blood cell count, percentage of neutrophils, percentage of lymphocytes, neutrophil-to-lymphocyte ratio, lactate dehydrogenase, creatine kinase isoenzyme, cardiac troponin I, laparoscopic exploration rate, open embolectomy rate, enterostomy rate, length of necrotic small bowel, length of healthy small bowel, surgical time and intraoperative blood loss differed significantly between groups. Creatine kinase isoenzyme (OR = 1.415, 95% CI: 1.060-1.888) and surgical time (OR = 1.014, 95% CI: 1.001-1.026) were independent risk factors associated with complications(Clavien‒Dindo ≥ 2).

CONCLUSIONS

Our analysis suggests that acute occlusive mesenteric ischemia patients with a creatine kinase isoenzyme level greater than 2.22 ng/mL or a surgical time longer than 156 min are more likely to experience complications'(Clavien‒Dindo ≥ 2) occurrence within 6 months of the first admission.

Acute mesenteric ischemia: which predictive factors of delayed diagnosis at emergency unit?

PURPOSE

Acute mesenteric ischemia (AMI) is frequently diagnosed late, leading to a poor prognosis. Our aims were to identify predictive factors of delayed diagnosis and to analyze the outcomes of patients with AMI admitted in emergency units.

METHODS

All the patients with AMI (2015-2020), in two Emergency units, were retrospectively included. Two groups were defined according to the time of diagnosis between the arrival at emergency unit and the CT scan: ≤ 6 h (early), > 6 h (delayed).

RESULTS

119 patients (mean age = 71 ± 7 years) were included. The patients with a delayed diagnosis (n = 33, 28%) were significantly associated with atypical presentation, including lower rates of abdominal pain (73 vs 89%, p = 0.003), abdominal tenderness (33 vs 43%, p = 0.03), and plasma lactate (4 ± 2 vs 6 ± 7 mmol/l, p = 0.03) when compared with early diagnosis. After multivariate analysis, the absence of abdominal pain was the only independent predictive factor of delayed diagnosis (Odd Ratio = 0.17; 95% CI = 0.03-0.88, p = 0.03). Patients with delayed diagnosis tended to be associated to lower rates of revascularization (9 vs 17%, p = 0.4), higher rates of major surgical morbidity (90 vs 57%, p = 0.1), longer length of stay (16 ± 23 vs 13 ± 15 days, p = 0.4) and, at the end of follow-up, higher rate of short small bowel syndrome (18 vs 7%, p = 0.095).

CONCLUSION

AMI is a challenge for emergency physicians. History of patient, physical exam, biological data are not sufficient to diagnose AMI. New biomarkers, and awareness of emergency physicians should improve and accelerate the diagnosis of AMI.

Basic demographic characteristics and prevalence of comorbidities in acute mesenteric ischemia: a systematic review and proportional meta-analysis

PURPOSE

The aim of this systematic review and meta-analysis was to examine and assess the basic demographic characteristics and prevalence of comorbidities in acute mesenteric ischemia (AMI) and its various subtypes.

PATIENTS AND METHODS

A literature search was conducted by using the databases PubMed, EMBASE, and Google Scholar (to June 1, 2022). Random-effects or fixed-effects models were selected to pool means and proportions and their corresponding 95% confidence intervals (CI), based on heterogeneity between studies. The results of meta-analyses for basic demographic characteristics and prevalence (proportions) of each specific comorbidities of acute mesenteric ischemia (AMI) and its various subtypes were described.

RESULTS

Ninety-nine studies were included in the meta-analysis, including 17,103 patients with AMI. Furthermore, 7941 patients with subclass diagnoses of AMI were identified, including 3,239 patients with arterial occlusive mesenteric ischemia (AOMI), 2,977 patients with nonocclusive mesenteric ischemia (NOMI), and 1,725 patients with mesenteric venous thrombosis (MVT). As a surgical emergency, AMI is associated with older patients and a high likelihood of multisystem comorbidities. Comorbidities of AMI involved multiple systemic diseases, including cardiovascular disease, endocrine and metabolic diseases, kidney diseases, digestive diseases, respiratory diseases, cerebrovascular diseases, vascular diseases, and cancer.

CONCLUSION

The basic demographic characteristics and the prevalence of comorbidities of different subtypes of AMI are different. The management of comorbidities should be an essential part of improving the prognosis of AMI patients and may contribute to precise prevention of AMI.

Are the conventional scoring systems efficient in predicting mortality of acute mesenteric ischemia?: Mortality estimation in patients with AMI

Acute mesenteric ischemia is a surgical emergency with high morbidity and mortality rates. Therefore, it is important to determine the prognosis for this disease. In the present study, we aimed to compare the prediction accuracy of 3 scoring systems: Acute physiology and chronic health evaluation II, sequential organ failure assessment score and simplified acute physiology score II (SAPS II). The retrospective cohort study was conducted in a university hospital. Eighty-two acute mesenteric ischemia patients were evaluated retrospectively. The mortality prediction abilities of the scoring systems were evaluated by comparing the prediction rates of > 10%, 30% and 50% and the actual mortality among survivors and non-survivors in pairs. Predicted mortality rates among survivors and non-survivors differed among the 3 classification systems. The mortality estimates of the SAPS II were closer to the actual mortality rates. Analysis of the estimated mortality rates as mortality risk limits showed that acute physiology and chronic health evaluation II was superior to sequential organ failure assessment score and SAPS II in estimating mortality rates, whereas SAPS II was more successful in detecting survivors. The estimated mortality rates of the 3 rating systems, the estimated mortality rates were higher in the non-survivor group than in the survivor group. The accuracy of the SAPS II in determining prognosis was relatively better.

Incidence and outcomes of acute mesenteric ischaemia: a systematic review and meta-analysis

OBJECTIVE

To estimate the incidence of acute mesenteric ischaemia (AMI), proportions of its different forms and short-term and long-term mortality.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

MEDLINE (Ovid), Web of Science, Scopus and Cochrane Library were searched until 26 July 2022.

ELIGIBILITY CRITERIA

Studies reporting data on the incidence and outcomes of AMI in adult populations.

DATA EXTRACTION AND SYNTHESIS

Data extraction and quality assessment with modified Newcastle-Ottawa scale were performed using predeveloped standard forms. The outcomes were the incidence of AMI and its different forms in the general population and in patients admitted to hospital, and the mortality of AMI in its different forms.

RESULTS

From 3064 records, 335 full texts were reviewed and 163 included in the quantitative analysis. The mean incidence of AMI was 6.2 (95% CI 1.9 to 12.9) per 100 000 person years. On average 5.0 (95% CI 3.3 to 7.1) of 10 000 hospital admissions were due to AMI. Occlusive arterial AMI was the most common form constituting 68.6% (95% CI 63.7 to 73.2) of all AMI cases, with similar proportions of embolism and thrombosis.Overall short-term mortality (in-hospital or within 30 days) of AMI was 59.6% (95% CI 55.5 to 63.6), being 68.7% (95% CI 60.8 to 74.9) in patients treated before the year 2000 and 55.0% (95% CI 45.5 to 64.1) in patients treated from 2000 onwards (p<0.05). The mid/long-term mortality of AMI was 68.2% (95% CI 60.7 to 74.9). Mortality due to mesenteric venous thrombosis was 24.6% (95% CI 17.0 to 32.9) and of non-occlusive mesenteric ischaemia 58.4% (95% CI 48.6 to 67.7). The short-term mortality of revascularised occlusive arterial AMI was 33.9% (95% CI 30.7 to 37.4).

CONCLUSIONS

In adult patients, AMI is a rarely diagnosed condition with high mortality, although with improvement of treatment results over the last decades. Two thirds of AMI cases are of occlusive arterial origin with potential for better survival if revascularised.

PROSPERO REGISTRATION NUMBER

CRD42021247148.

Prognostic Factors for Mortality in Acute Mesenteric Ischemia

Postoperative mortality in patients undergoing surgical and/or interventional treatment for acute mesenteric ischemia (AMI) has remained an unsolved problem in recent decades. Here, we investigated clinical predictors of postoperative mortality in a large European cohort of patients undergoing treatment for AMI. In total, 179 patients who underwent surgical and/or interventional treatment for AMI between 2009 and 2021 at our institution were included in this analysis. Associations between postoperative mortality and various clinical variables were assessed using univariate and multivariable binary logistic regression analysis. Most of the patients were diagnosed with arterial ischemia (AI; n = 104), while venous ischemia (VI; n = 21) and non-occlusive mesenteric ischemia (NOMI; n = 54) were present in a subset of patients. Overall inhouse mortality was 55.9% (100/179). Multivariable analyses identified leukocytes (HR = 1.08; p = 0.008), lactate (HR = 1.25; p = 0.01), bilirubin (HR = 2.05; p = 0.045), creatinine (HR = 1.48; p = 0.039), etiology (AI, VI or NOMI; p = 0.038) and portomesenteric vein gas (PMVG; HR = 23.02; p = 0.012) as independent predictors of postoperative mortality. In a subanalysis excluding patients with fatal prognosis at the first surgical exploration (n = 24), leukocytes (HR = 1.09; p = 0.004), lactate (HR = 1.27; p = 0.003), etiology (AI, VI or NOMI; p = 0.006), PMVG (HR = 17.02; p = 0.018) and intraoperative FFP transfusion (HR = 4.4; p = 0.025) were determined as independent predictors of postoperative mortality. Further, the risk of fatal outcome changed disproportionally with increased preoperative lactate values. The clinical outcome of patients with AMI was determined using a combination of pre- and intraoperative clinical and radiological characteristics. Serum lactate appears to be of major clinical importance as the risk of fatal outcome increases significantly with higher lactate values.

A Comprehensive Way to Access Hospital Death Prediction Model for Acute Mesenteric Ischemia: A Combination of Traditional Statistics and Machine Learning

PURPOSE

This study aimed to use traditional statistics and machine learning to develop and validate prediction models for predicting hospital death in patients with AMI and compare these models' performance.

PATIENTS AND METHODS

Data were retrieved from the Medical Information Mart for Intensive Care (MIMIC III) electronic clinical database. A total of 338 eligible AMI patients were divided into a training cohort (n = 238) and a validation cohort (n = 100), and all patients were divided into survival groups and nonsurvival groups according to patients' hospital outcomes. The performance of the traditional statistics prediction model and the optimal machine learning prediction model was evaluated and compared with respect to discrimination, calibration, and clinical utility in the validation cohort.

RESULTS

Univariate and multivariate logistic regression analyses identified the following independent risk factors associated with hospital death for AMI in the training cohort, including diastolic blood pressure, blood lactate, blood creatinine, age, blood pH, and red blood cell distribution width. Both the nomogram (AUC = 77.0%, 67.9-86.1%) and optimal machine learning model (AUC = 82.9%, 74.9-91.0%) achieved good discrimination and calibration in the validation cohort. Decision curves analysis showed that the optimal machine learning model has a greater net benefit than that of nomogram in this study.

CONCLUSION

The nomogram achieved a concise and relatively accurate prediction of hospital death in patients with AMI, the machine learning model also has good discrimination and seems to have better clinical utility. Traditional statistics may help infer the relationship between risk factors and hospital death, while machine learning may contribute to a more accurate prediction. Traditional statistics and machine learning are complementary in developing the prediction model for hospital death of AMI. Therefore, a combination of nomogram-machine learning (Nomo-ML) predictive model may improve care and help clinicians make AMI management-related decisions.