Safety and Feasibility of Same Day Discharge Strategy for Primary Percutaneous Coronary Intervention

Shah, Jehangir Ali; Saghir, Tahir; Bourazza, Ahmed; Haq, Syed Alishan ul; Kumar, Rajesh; Mengal, Muhammad Naeem; Zehra, Mehwish; Raza, Syeda Sakeena; Karim, Musa; Qamar, Nadeem

doi:10.5334/gh.1035

Cited by 8 publications

(19 citation statements)

References 28 publications

(51 reference statements)

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“…This prospective observational cohort study is a sub-group analysis of a previously reported study by Shah JA et al [ 10 ]. This study was conducted at a tertiary care cardiac hospital of Karachi, Pakistan between August 2019 and July 2020.…”

Section: Methodsmentioning

confidence: 99%

“…This study was approved by the ethical review board of the institution and consent for participation, and follow-up was taken from all the patients. A detailed descriptions of patient recruitment, management, and evaluation criteria are presented elsewhere [ 10 ]. Patients with myocardial infarction complicated by cardiogenic shock, atrioventricular (AV) block, or history of prior cardiac surgery or intervention or patients lost to follow-up at 30-day (3.4% (17)) [ 10 ] were excluded from the study.…”

Section: Methodsmentioning

confidence: 99%

“…Along with demographic and clinical characteristics, described elsewhere [ 10 ], the Zwolle risk score (ZRS) was calculated as per the scoring criteria defined by De Luca G et al [ 15 ] based on age, Killip class at presentation, total ischemic time (defined as symptom onset to device activation time), anterior wall myocardial infarction (AWMI), pre-procedure TIMI (Thrombolysis in Myocardial Infarction) flow grade, and number of diseased vessels. Patients were categorized into high- and low-risk group based on additive score; low-risk (≤3) and high-risk (≥4).…”

Section: Methodsmentioning

confidence: 99%

“…This necessitates coronary care unit monitoring of these patients for at least 24–48 h. With the increasing number of patients with CAD requiring extended post-procedure hospital care, identification of low-risk patients has become crucial in whom early discharge could be safe. Reduced post-procedure hospital stay can be beneficial for patients as well as it can have substantial financial implications for healthcare systems of low and middle-income countries with funding and resource constraints [ 10 ]. Safety and feasibility of early discharge (within 48–72 h of procedure) has been established by various studies [ 11 – 14 ].…”

Section: Introductionmentioning

confidence: 99%

“…Safety and feasibility of early discharge (within 48–72 h of procedure) has been established by various studies [ 11 – 14 ]. Also same-day discharge strategy showed promising results with lower rate of major adverse cardiac events after 30-days of the procedure [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

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Zwolle Risk Score for Safety Assessment of Same-Day Discharge after Primary Percutaneous Coronary Intervention

Shah¹,

Solangi²,

Batra³

et al. 2021

Journal of the Saudi Heart Association

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Objectives The Zwolle risk score (ZRS) has been considered to be a useful tool for the systematic evaluation of patients for early discharge after primary percutaneous coronary intervention (PCI). Therefore, aim of this study was to evaluate the clinical utility of ZRS for the same-day discharge strategy after primary PCI at a tertiary care cardiac center of Karachi, Pakistan. Methods This study was conducted at a tertiary care cardiac center between August 2019 and July 2020. Patients discharged within 24 h (same-day) of the primary PCI procedure were included. Patients were stratified as high- and low-risk based on ZRS score; low-risk (≤3) and high-risk (≥4). All patients were followed during 30-days post-procedure period for major adverse cardiac events (MACE). Results Out of 487 patients, 83.2% (405) were male and mean age was 54.6 ± 10.87 years. Mean ZRS was 2.34 ± 1.64 with 16.0% (78) patients in high-risk (≥4) group. 30-days MACE rate was observed to be 5.3% (26) with significantly higher rate among high-risk patients as compared to low-risk patients 12.8% (10) vs. 3.9% (16); p = 0.004 respectively with OR of 3.61 [1.57–8.29]. The area under the curve (AUC) of ZRS for prediction of 30-day MACE was 0.67 [95% CI: 0.58–0.77], ZRS ≥4 had sensitivity of 38.5% and specificity of 85.2% with AUC of 0.62 [95% CI: 0.50–0.74] for prediction of 30-day MACE. Conclusion ZRS showed moderate discriminating potential in identifying patients with high-risk of MACE at 30-day after same-day discharge after primary PCI.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Zwolle Risk Score for Safety Assessment of Same-Day Discharge after Primary Percutaneous Coronary Intervention

Shah¹,

Solangi²,

Batra³

et al. 2021

Journal of the Saudi Heart Association

Self Cite

View full text Add to dashboard Cite

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Impact of the COVID-19 Outbreak on the Treatment of Myocardial Infarction Patients

Grundeken¹,

Claessen²

2023

Curr Treat Options Cardio Med

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Purpose of review The COVID-19 pandemic has led to an overburdened healthcare system. While an increased rate of ACS is expected due to the pro-thrombotic state of COVID patients, observed ACS incidence and admission rates were paradoxically decreased during the (first wave of the) pandemic. In this narrative review, we will discuss potential reasons for this decrease in ACS incidence. Furthermore, we will discuss ACS management during the COVID-19 pandemic, and we will discuss outcomes in ACS. Recent findings A reluctance to seek medical contact (in order not to further overburden the health system or due to fear of being infected with COVID-19 while in hospital) and unavailability of medical services seem to be important factors. This may have led to an increased symptom onset to first medical contact time and an increased rate of out-of-hospital cardiac arrests. A trend towards less invasive management was observed (less invasive coronary angiography in NSTEMI patients and more “fibrinolysis-first” in STEMI patients), although a large variation was observed with some centers having a relative increase in early invasive management. Patients with ACS and concomitant COVID-19 infection have worse outcomes compared to ACS patients without COVID-19 infection. All of the above led to worse clinical outcomes in patients presenting with ACS during the COVID-19 pandemic. Interestingly, staffing and hospital bed shortages led to experimentation with very early discharge (24 h after primary PCI) in low-risk STEMI patients which had a very good prognosis and resulted in significant shorter hospital duration. Summary During the COVID-19 pandemic, ACS incidence and admission rates were decreased, symptom onset to first medical contact time prolonged, and out-of-hospital rates increased. A trend towards less invasive management was observed. Patients presenting with ACS during the COVID-19 pandemic had a worse outcome. On the other hand, experimental very early discharge in low-risk patients may relieve the healthcare system. Such initiatives, and strategies to lower the reluctance of patients with ACS symptoms to seek medical help, are vital to improve prognosis in ACS patients in future pandemics.

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Development and validation of a machine learning-based readmission risk prediction model for non-ST elevation myocardial infarction patients after percutaneous coronary intervention

Liu,

Du,

et al. 2024

Sci Rep

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To investigate the factors that influence readmissions in patients with acute non-ST elevation myocardial infarction (NSTEMI) after percutaneous coronary intervention (PCI) by using multiple machine learning (ML) methods to establish a predictive model. In this study, 1576 NSTEMI patients who were hospitalized at the Affiliated Hospital of North Sichuan Medical College were selected as the research subjects. They were divided into two groups: the readmitted group and the non-readmitted group. The division was based on whether the patients experienced complications or another incident of myocardial infarction within one year after undergoing PCI. Common variables selected by univariate and multivariate logistic regression, LASSO regression, and random forest were used as independent influencing factors for NSTEMI patients’ readmissions after PCI. Six different ML models were constructed using these common variables. The area under the ROC curve, accuracy, sensitivity, and specificity were used to evaluate the performance of the six ML models. Finally, the optimal model was selected, and a nomogram was created to visually represent its clinical effectiveness. Three different methods were used to select seven representative common variables. These variables were then utilized to construct six different ML models, which were subsequently compared. The findings indicated that the LR model exhibited the most optimal performance in terms of AUC, accuracy, sensitivity, and specificity. The outcome, admission mode (walking and non-walking), communication ability, CRP, TC, HDL, and LDL were identified as independent predicators of readmissions in NSTEMI patients after PCI. The prediction model constructed by the LR algorithm was the best. The established column graph model established proved to be effective in identifying high-risk groups with high accuracy and differentiation. It holds a specific predictive value for the occurrence of readmissions after direct PCI in NSTEMI patients.

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Safety and Feasibility of Same Day Discharge Strategy for Primary Percutaneous Coronary Intervention

Cited by 8 publications

References 28 publications

Zwolle Risk Score for Safety Assessment of Same-Day Discharge after Primary Percutaneous Coronary Intervention

Zwolle Risk Score for Safety Assessment of Same-Day Discharge after Primary Percutaneous Coronary Intervention

Impact of the COVID-19 Outbreak on the Treatment of Myocardial Infarction Patients

Development and validation of a machine learning-based readmission risk prediction model for non-ST elevation myocardial infarction patients after percutaneous coronary intervention

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