scholarly journals Non-specific pain and 30-day readmission in acute coronary syndromes: findings from the TRACE-CORE prospective cohort

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jinying Chen ◽  
Catarina I. Kiefe ◽  
Marc Gagnier ◽  
Darleen Lessard ◽  
David McManus ◽  
...  
Keyword(s):  
Chest Pain ◽  
Language Processing ◽  
Prospective Cohort ◽  
Acute Coronary Syndromes ◽  
Healthcare Providers ◽  
Moderate Pain ◽  
Post Discharge ◽  
Patient Reported ◽  
Coronary Syndromes ◽  
The Impact

Abstract Background Patients with acute coronary syndromes often experience non-specific (generic) pain after hospital discharge. However, evidence about the association between post-discharge non-specific pain and rehospitalization remains limited. Methods We analyzed data from the Transitions, Risks, and Actions in Coronary Events Center for Outcomes Research and Education (TRACE-CORE) prospective cohort. TRACE-CORE followed patients with acute coronary syndromes for 24 months post-discharge from the index hospitalization, collected patient-reported generic pain (using SF-36) and chest pain (using the Seattle Angina Questionnaire) and rehospitalization events. We assessed the association between generic pain and 30-day rehospitalization using multivariable logistic regression (N = 787). We also examined the associations among patient-reported pain, pain documentation identified by natural language processing (NLP) from electronic health record (EHR) notes, and the outcome. Results Patients were 62 years old (SD = 11.4), with 5.1% Black or Hispanic individuals and 29.9% women. Within 30 days post-discharge, 87 (11.1%) patients were re-hospitalized. Patient-reported mild-to-moderate pain, without EHR documentation, was associated with 30-day rehospitalization (odds ratio [OR]: 2.03, 95% confidence interval [CI]: 1.14–3.62, reference: no pain) after adjusting for baseline characteristics; while patient-reported mild-to-moderate pain with EHR documentation (presumably addressed) was not (OR: 1.23, 95% CI: 0.52–2.90). Severe pain was also associated with 30-day rehospitalization (OR: 3.16, 95% CI: 1.32–7.54), even after further adjusting for chest pain (OR: 2.59, 95% CI: 1.06–6.35). Conclusions Patient-reported post-discharge generic pain was positively associated with 30-day rehospitalization. Future studies should further disentangle the impact of cardiac and non-cardiac pain on rehospitalization and develop strategies to support the timely management of post-discharge pain by healthcare providers.

scholarly journals COVID-19 and Acute Coronary Syndromes: Current Data and Future Implications

2021 ◽  
Vol 7 ◽  
Author(s):  
Matteo Cameli ◽  
Maria Concetta Pastore ◽  
Giulia Elena Mandoli ◽  
Flavio D'Ascenzi ◽  
Marta Focardi ◽  
...  
Keyword(s):  
Acute Coronary Syndromes ◽  
Healthcare Providers ◽  
Current Data ◽  
Hospital Environment ◽  
Healthcare Personnel ◽  
Clinical Approach ◽  
Mortality And Morbidity ◽  
The World ◽  
Coronary Syndromes ◽  
The Impact

Coronavirus disease-2019 (COVID-19) pandemic is a global healthcare burden, characterized by high mortality and morbidity rates all over the world. During the outbreak period, the topic of acute coronary syndromes (ACS) has raised several clinical issues, due to the risks of COVID-19 induced myocardial injury and to the uncertainties about the management of these cardiologic emergency conditions, which should be organized optimizing the diagnostic and therapeutic resources and ensuring the maximum protection to healthcare personnel and hospital environment. COVID-19 status should be assessed as soon as possible. Moreover, considerably lower rates of hospitalization for ACS have been reported all over the world, due to patients' hesitations to refer to hospital and to missed diagnosis. As a result, short- and long-term complications of myocardial infarction are expected in the near future; therefore, great efforts of healthcare providers will be required to limit the effects of this issue. In the present review we discuss the impact of COVID-19 pandemic on ACS diagnosis and management, with possible incoming consequences, providing an overview of the available evidence and suggesting future changes in social and clinical approach to ACS.

scholarly journals ‘Chest Pain Typicality’ in Suspected Acute Coronary Syndromes and the Impact of Clinical Experience

2015 ◽  
Vol 128 (10) ◽  
pp. 1109-1116.e2 ◽  
Author(s):  
Edward W. Carlton ◽  
Martin Than ◽  
Louise Cullen ◽  
Ahmed Khattab ◽  
Kim Greaves
Keyword(s):  
Chest Pain ◽  
Clinical Experience ◽  
Acute Coronary Syndromes ◽  
Coronary Syndromes ◽  
The Impact

Physical fitness cannot be used to predict the likelihood of acute coronary syndromes in ED patients with chest pain

2012 ◽  
Vol 30 (1) ◽  
pp. 57-60
Author(s):  
Taku Taira ◽  
Breena R. Taira ◽  
Jasmine Chohan ◽  
Daniel Dickinson ◽  
Regina M. Troxell ◽  
...  
Keyword(s):  
Chest Pain ◽  
Physical Fitness ◽  
Acute Coronary Syndromes ◽  
Coronary Syndromes

Chronic kidney disease as a risk factor for acute coronary syndromes in patients presenting to the emergency room with chest pain

2012 ◽  
Vol 159 (5) ◽  
pp. 391-396 ◽  
Author(s):  
Sherezade Khambatta ◽  
Michael E. Farkouh ◽  
R. Scott Wright ◽  
Guy S. Reeder ◽  
Peter A. McCullough ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Risk Factor ◽  
Chest Pain ◽  
Kidney Disease ◽  
Emergency Room ◽  
Acute Coronary Syndromes ◽  
Coronary Syndromes

scholarly journals Early prediction of diagnostic-related groups and estimation of hospital cost by processing clinical notes

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Jinghui Liu ◽  
Daniel Capurro ◽  
Anthony Nguyen ◽  
Karin Verspoor
Keyword(s):  
Language Processing ◽  
Hospital Cost ◽  
Diagnosis Related Groups ◽  
Characteristic Curve ◽  
Healthcare Providers ◽  
Post Discharge ◽  
Clinical Text ◽  
Case Mix Index ◽  
Operational Decision Making ◽  
Diagnostic Related Groups

AbstractAs healthcare providers receive fixed amounts of reimbursement for given services under DRG (Diagnosis-Related Groups) payment, DRG codes are valuable for cost monitoring and resource allocation. However, coding is typically performed retrospectively post-discharge. We seek to predict DRGs and DRG-based case mix index (CMI) at early inpatient admission using routine clinical text to estimate hospital cost in an acute setting. We examined a deep learning-based natural language processing (NLP) model to automatically predict per-episode DRGs and corresponding cost-reflecting weights on two cohorts (paid under Medicare Severity (MS) DRG or All Patient Refined (APR) DRG), without human coding efforts. It achieved macro-averaged area under the receiver operating characteristic curve (AUC) scores of 0·871 (SD 0·011) on MS-DRG and 0·884 (0·003) on APR-DRG in fivefold cross-validation experiments on the first day of ICU admission. When extended to simulated patient populations to estimate average cost-reflecting weights, the model increased its accuracy over time and obtained absolute CMI error of 2·40 (1·07%) and 12·79% (2·31%), respectively on the first day. As the model could adapt to variations in admission time, cohort size, and requires no extra manual coding efforts, it shows potential to help estimating costs for active patients to support better operational decision-making in hospitals.

scholarly journals PRe-hospital Evaluation of Sensitive TrOponin (PRESTO) Study: multicentre prospective diagnostic accuracy study protocol

BMJ Open ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. e032834 ◽  
Author(s):  
Abdulrhman Alghamdi ◽  
Eloïse Cook ◽  
Edward Carlton ◽  
Aloysius Siriwardena ◽  
Mark Hann ◽  
...  
Keyword(s):  
Chest Pain ◽  
Hospital Admission ◽  
Diagnostic Accuracy ◽  
Blood Sample ◽  
Acute Coronary Syndromes ◽  
Venous Blood ◽  
Prehospital Setting ◽  
Registration Number ◽  
Coronary Syndromes ◽  
Rule Out

IntroductionWithin the UK, chest pain is one of the most common reasons for emergency (999) ambulance calls and the most common reason for emergency hospital admission. Diagnosing acute coronary syndromes (ACS) in a patient with chest pain in the prehospital setting by a paramedic is challenging. The Troponin-only Manchester Acute Coronary Syndromes (T-MACS) decision rule is a validated tool used in the emergency department (ED) to stratify patients with suspected ACS following a single blood test.We are seeking to evaluate the diagnostic accuracy of the T-MACS decision aid algorithm to ‘rule out’ ACS when used in the prehospital environment with point-of-care troponin assays. If successful, this could allow paramedics to immediately rule out ACS for patients in the ‘very low risk’ group and avoid the need for transport to the ED, while also risk stratifying other patients using a single blood sample taken in the prehospital setting.Methods and analysisWe will recruit patients who call emergency (999) ambulance services where the responding paramedic suspects cardiac chest pain. The data required to apply T-MACS will be prospectively recorded by paramedics who are responding to each patient. Paramedics will be required to draw a venous blood sample at the time of arrival to the patient. Blood samples will later be tested in batches for cardiac troponin, using commercially available troponin assays. The primary outcome will be a diagnosis of acute myocardial infarction, established at the time of initial hospital admission. The secondary outcomes will include any major adverse cardiac events within 30 days of enrolment.Ethics and disseminationThe study obtained approval from the National Research Ethics Service (reference: 18/ES/0101) and the Health Research Authority. We will publish our findings in a high impact general medical journal.Trial registration numberRegistration number: ClinicalTrials.gov, study ID: NCT03561051

Improved Assessment of Chest pain Trial (IMPACT): assessing patients with possible acute coronary syndromes

2017 ◽  
Vol 207 (5) ◽  
pp. 195-200 ◽  
Author(s):  
Louise Cullen ◽  
Jaimi H Greenslade ◽  
Tracey Hawkins ◽  
Chris Hammett ◽  
Shanen O'Kane ◽  
...  
Keyword(s):  
Chest Pain ◽  
Acute Coronary Syndromes ◽  
Coronary Syndromes
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