Contemporary NSTEMI management: the role of the hospitalist

Treatment and outcomes of patients with chronic lung disease and acute myocardial infarction: Insights from the nationwide AMIS plus registry

BACKGROUND

Limited data are available on patients with chronic lung disease (CLD) presenting with acute myocardial infarction (AMI). We aimed to analyse baseline characteristics, treatment and outcome of those patients enrolled in the Swiss nationwide prospective AMIS Plus registry.

METHODS

All AMI patients enrolled between January 2002 and December 2021 with data on CLD, as defined in the Charlson Comorbidity Index, were included. The primary endpoints were in-hospital mortality and major adverse cardiac and cerebrovascular events (MACCE), defined as all-cause death, reinfarction and cerebrovascular events. Baseline characteristics, in-hospital treatments and outcomes were analysed using descriptive statistics and logistic regression.

RESULTS

Among 53,680 AMI patients enrolled during this time, 5.8% had CLD. Compared with patients without CLD, CLD patients presented more frequently with non-ST-elevation myocardial infarction (MI) and type 2 MI (12.8% vs. 6.5%, p < 0.001). With respect to treatment, CLD patients were less likely to receive P2Y12 inhibitors (p < 0.001) and less likely to undergo percutaneous coronary interventions (68.7% vs. 82.5%; p < 0.001). In-hospital mortality declined in AMI patients with CLD over time (from 12% in 2002 to 7.3% in 2021). Multivariable regression analysis showed that CLD was an independent predictor for MACCE (adjusted OR was 1.28 [95% CI 1.07-1.52], p = 0.006).

CONCLUSION

Patients with CLD and AMI were less likely to receive evidence-based pharmacologic treatments, coronary revascularization and had a higher incidence of MACCE during their hospital stay compared to those without CLD. Over 20 years, in-hospital mortality was significantly reduced in AMI patients, especially in those with CLD.

The prognostic impact of insulin resistance surrogates in patients with acute myocardial infarction with and without type 2 diabetes

BACKGROUND

Cardiovascular disease is the major cause of morbidity and mortality, particularly in type 2 diabetes mellitus (T2DM). Novel markers of insulin resistance and progression of atherosclerosis include the triglycerides and glucose index (TyG index), the triglycerides and body mass index (Tyg-BMI) and the metabolic score for insulin resistance (METS-IR). Establishing independent risk factors for in-hospital death and major adverse cardiac and cerebrovascular events (MACCE) in patients with myocardial infarction (MI) remains critical. The aim of the study was to assess the risk of in-hospital death and MACCE within 12 months after ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) in patients with and without T2DM based on TyG index, Tyg-BMI and METS-IR.

METHODS

Retrospective analysis included 1706 patients with STEMI and NSTEMI hospitalized between 2013 and 2021. We analyzed prognostic value of TyG index, Tyg-BMI and METS-IR for in-hospital death and MACCE as its components (death from any cause, MI, stroke, revascularization) within 12 months after STEMI or NSTEMI in patients with and without T2DM.

RESULTS

Of 1706 patients, 58 in-hospital deaths were reported (29 patients [4.3%] in the group with T2DM and 29 patients [2.8%] in the group without T2DM; p = 0.1). MACCE occurred in 18.9% of the total study population (25.8% in the group with T2DM and 14.4% in the group without T2DM; p < 0.001). TyG index, Tyg-BMI and METS-IR were significantly higher in the group of patients with T2DM compared to those without T2DM (p < 0.001). Long-term MACCE were more prevalent in patients with T2DM (p < 0.001). The area under the ROC curve (AUC-ROC) for the prediction of in-hospital death and the TyG index was 0.69 (p < 0.001). The ROC curve for predicting in-hospital death based on METS-IR was 0.682 (p < 0.001). The AUC-ROC values for MACCE prediction based on the TyG index and METS-IR were 0.582 (p < 0.001) and 0.57 (p < 0.001), respectively.

CONCLUSIONS

TyG index was an independent risk factor for in-hospital death in patients with STEMI or NSTEMI. TyG index, TyG-BMI and METS-IR were not independent risk factors for MACCE at 12 month follow-up. TyG index and METS-IR have low predictive value in predicting MACCE within 12 months after STEMI and NSTEMI.

Managing Mesenteric-Side Small Bowel Perforation in the Setting of Non-ST Elevation Myocardial Infarction: A Dual Challenge

Small bowel perforations are critical surgical emergencies, and those occurring on the mesenteric side are particularly uncommon. These perforations can lead to significant morbidity due to potential vascular compromise and the rapid spread of intraluminal contents. When a patient concurrently presents with a non-ST elevation myocardial infarction (NSTEMI), the clinical management becomes even more intricate. Balancing the urgency of surgical intervention for bowel perforation with the potential cardiac risks associated with surgery, especially in the context of a concurrent NSTEMI, poses a significant clinical challenge. An 86-year-old male with an extensive cardiac history presented with a complaint of abdominal pain, primarily localized to the left lower quadrant. Diagnostic investigations, including a contrast-enhanced computerized tomography (CT) scan, identified extraluminal air and pronounced inflammation adjacent to a loop of small bowel, consistent with perforation. Simultaneously, elevated troponin levels and specific electrocardiogram (ECG) changes confirmed an NSTEMI diagnosis. Following a multidisciplinary discussion, the patient underwent exploratory laparotomy, resulting in small bowel resection. Postoperative cardiac monitoring managed a brief episode of supraventricular tachycardia effectively. This case highlights the intricacies involved in managing a patient with a rare mesenteric-side small bowel perforation while also dealing with an NSTEMI. While the causes of spontaneous small bowel perforations can vary, this case presented an added layer of complexity without a clear predisposing factor. The presence of NSTEMI introduced challenges in determining the timing and approach to surgical intervention. The necessity for collaboration between surgical and cardiology teams was evident, ensuring a comprehensive assessment of the patient's cardiac risk and optimizing cardiac medications. Managing a patient with concurrent small bowel perforation and NSTEMI demands meticulous clinical judgment and inter-specialty collaboration. This case offers valuable insights into the considerations and challenges faced in such unique clinical scenarios, emphasizing the importance of individualized patient care.

C-reactive protein and uric acid roles in distinguishing ST-segment elevation myocardial infarction from non-ST-elevation acute coronary syndrome

Acute coronary syndrome (ACS) is defined as a range of conditions which the blood flow to the heart was reduced or stopped. This disorder is correlated to a systemic inflammatory response and some biochemical factors. Therefore, the aim of this study was investigations of serum C-reactive protein (CRP) and uric acid levels in ST-segment elevation myocardial infarction (STEMI) and non-ST-elevation ACS (NSTE ACS), as common subtypes of ACS. Patients with ACS (n = 140) were assessed with coronary arteriography and divided into STEMI and NSTE ACS groups. The serum levels of hs-CRP and uric acid were investigated using a routine clinical chemistry analyzer. Patients with STEMI showed a significant increase in uric acid level compared to those with NSTE ACS (P < .0001). Other data indicated that hs-CRP level in patients with STEMI was significantly higher than individuals with NSTE ACS (P < .0001). Modeling analysis revealed that the increased levels of acid uric and hs-CRP in patients with STEMI were independent of the effects of age, gender, background diseases, and familial history (P < .001). The current study provides further evidence to indicate that hs-CRP and uric acid may be considered as biofactors for comparing STEMI from NSTE ACS and determining disease outcome.

The Predictive Value of Barthel Score, Sequential Organ Failure Assessment Score, and D-Dimer in the 28-Day Prognosis of Patients with Non-ST Elevation Myocardial Infarction: A Retrospective Study of 358 Patients

Purpose

To investigate the nursing prediction value of Barthel score, sequential organ failure assessment (SOFA) score and D-dimer on non-ST-elevation myocardial infarction (NSTEMI) inpatients.

Methods

The clinical data of 358 NSTEMI patients admitted to the emergency department were analyzed using logistic regression equation and a ROC curve was drawn. The area under ROC curve (AUC) of different indicators was compared. A COX regression model was created, and a survival curve was drawn.

Results

There were significant differences in age, D-dimer, WBC, NT-proBNP, EF (%), BI score, MEWS score, and SOFA score between the 28-day death group and the survival group (P < 0.05). The results showed that D-dimer (P = 0.002), SOFA score (P = 0.017), BI score (P < 0.001), and chest pain symptoms (P < 0.001) were independent predictors of 28-day death. When chest pain symptoms (AUC = 0.585), D-dimer (AUC = 0.945, Z = 8.00, P < 0.01), BI score (AUC = 0.145, Z = 5.36, P < 0.01), and SOFA score (AUC = 0.847, Z = 4.93, P < 0.01) were compared, the results showed that BI score (HR = 0.961, P < 0.01) and SOFA score (HR = 1.316, P < 0.001) had statistical significance on the 28-day survival time of the dead patients.

Conclusion

The Barthel score, SOFA score, and D-dimer are all essential in predicting the severity of NSTEMI patients, with a high nursing evaluation value. The Barthel and SOFA scores are associated with the risk of death within 28 days.

Intelligent Algorithm-Based Coronary Angiography Characteristics of Acute Non-ST-Segment Elevation Myocardial Infarction Patients with Different Genders

OBJECTIVE

This study was aimed at comparing the characteristics of coronary angiography based on intelligent algorithm in patients with acute non-ST-segment elevation myocardial infarction (NSTEMI) of different genders.

METHODS

Eighty patients were selected to segment the coronary angiogram using the convolutional neural network (CNN) algorithm, the input layer of the CNN was used to receive the image dataset, and three-dimensional data were input during semantic segmentation to achieve automatic segmentation of the target features. Segmentation results were quantitatively assessed by accuracy (Acc), sensitivity (Se), specificity (Sp), and Dice coefficient (Dice). The characteristics of coronary angiography were compared between the two groups.

RESULTS

The CNN algorithm had good segmentation effect, complete vessel extraction, and little noise, and Acc, Se, Sp, and Dice were 90.32%, 93.39%, 91.25%, and 89.75%, respectively. The proportion of diabetes mellitus was higher in female patients with NSTEMI (68.8%) than that in male patients (46.3%); the proportion of the left main coronary artery (LM) and left anterior descending artery (LAD) was lower in the female group (7.5%, 41.3%) than that in the male group (13.8%, 81.3%), and the difference between the two groups was statistically significant (P < 0.05).

CONCLUSION

The CNN algorithm achieves accurate extraction of vessels from coronary angiographic images, and women with diabetes and hyperlipidemia are more likely to have NSTEMI than men, especially the elderly.

Distribution Characteristics of ST-Segment Elevation Myocardial Infarction and Non-ST-Segment Elevation Myocardial Infarction Culprit Lesion in Acute Myocardial Infarction Patients Based on Coronary Angiography Diagnosis

This research was aimed at exploring the application value of coronary angiography (CAG) based on a convolutional neural network algorithm in analyzing the distribution characteristics of ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) culprit lesions in acute myocardial infarction (AMI) patients. Methods. Patients with AMI treated in hospital from June 2019 to December 2020 were selected as subjects. According to the results of an echocardiogram, the patients were divided into the STEMI group (44 cases) and the NSTEMI group (36 cases). All patients received CAG. All images were denoised and edge detected by a convolutional neural network algorithm. Then, the number of diseased vessels, the location of diseased vessels, and the degree of stenosis of diseased vessels in the two groups were compared and analyzed. Results. The number of patients with complete occlusion (3 cases vs. 12 cases) and collateral circulation (5 cases vs. 20 cases) in the NSTEMI group was significantly higher than that in the STEMI group, and the difference was statistically significant, P < 0.05. There was a statistically significant difference in the number of lesions between the distal LAD (1 case vs. 10 cases) and the distal LCX (4 cases vs. 11 cases), P < 0.05. There was a statistically significant difference in the number of patients with one lesion branch (1 vs. 18) and three lesion branches (25 vs. 12) between the two groups, P < 0.05. The image quality after the convolution neural network algorithm is significantly improved, and the lesion is more prominent. Conclusion. The convolutional neural network algorithm has good performance in DSA image processing of AMI patients. STEMI and NSTEMI as the starting point of AMI disease analysis to determine the treatment plan have high clinical application value. This work provided reference and basis for the application of the convolutional neural network algorithm and CAG in the analysis of the distribution characteristics of STEMI and NSTEMI culprit lesions in AMI patients.