A novel interpretable deep learning model for diagnosis in emergency department dyspnoea patients based on complete data from an entire health care system.

Background: Dyspnoea is one of the emergency department's (ED) most common and deadly chief complaints, but frequently misdiagnosed and mistreated. We aimed to design a diagnostic decision support which classifies dyspnoeic ED visits into acute heart failure (AHF), exacerbation of chronic obstructive pulmonary disease (eCOPD), pneumonia and "other diagnoses" by using deep learning and complete, unselected data from an entire regional health care system.

Methods: In this cross-sectional study, we included all dyspnoeic ED visits of patients ≥ 18 years of age at the two EDs in the region of Halland, Sweden, 07/01/2017-12/31/2019.

The Price of Explainability in Machine Learning Models for 100-Day Readmission Prediction in Heart Failure: Retrospective, Comparative, Machine Learning Study.

Background: Sensitive and interpretable machine learning (ML) models can provide valuable assistance to clinicians in managing patients with heart failure (HF) at discharge by identifying individual factors associated with a high risk of readmission. In this cohort study, we delve into the factors driving the potential utility of classification models as decision support tools for predicting readmissions in patients with HF.

Objective: The primary objective of this study is to assess the trade-off between using deep learning (DL) and traditional ML models to identify the risk of 100-day readmissions in patients with HF.

Characteristics, management and outcomes in patients with CKD in a healthcare region in Sweden: a population-based, observational study.

Objectives: To describe chronic kidney disease (CKD) regarding treatment rates, comorbidities, usage of CKD International Classification of Diseases (ICD) diagnosis, mortality, hospitalisation, evaluate healthcare utilisation and screening for CKD in relation to new nationwide CKD guidelines.

Design: Population-based observational study.

Setting: Healthcare registry data of patients in Southwest Sweden.

Synthetic electronic health records generated with variational graph autoencoders.

Data-driven medical care delivery must always respect patient privacy-a requirement that is not easily met. This issue has impeded improvements to healthcare software and has delayed the long-predicted prevalence of artificial intelligence in healthcare. Until now, it has been very difficult to share data between healthcare organizations, resulting in poor statistical models due to unrepresentative patient cohorts.

Health-related quality of life and long-term symptoms among patients with non-severe covid-19 - a prospective cohort study.

Background: The vast majority of covid-19 patients experience non-severe disease. Nonetheless, long-term symptoms may be common and the impact on quality of life is uncertain. This study aims to examine these aspects in a prospective, longitudinal cohort.

Clinical presentation in EMS patients with acute chest pain in relation to sex, age and medical history: prospective cohort study.

Objective: To assess symptom presentation related to age, sex and previous medical history in patients with chest pain.

Design: Prospective observational cohort study.

Setting: Two-centre study in a Swedish county emergency medical service (EMS) organisation.

The potential of new prediction models for emergency medical dispatch prioritisation of patients with chest pain: a cohort study.

Objectives: To develop emergency medical dispatch (EMD) centre prediction models with high sensitivity and satisfying specificity to identify high-priority patients and patients suitable for non-emergency care respectively, when assessing patients with chest pain.

Methods: Observational cohort study of 2917 unselected patients with chest pain who contacted an EMD centre in Sweden due to chest pain during 2018. Multivariate logistic regression was applied to develop models predicting low-risk or high-risk condition, that is, occurrence of time-sensitive diagnosis on hospital discharge.

Guideline adherence among prehospital emergency nurses when caring for patients with chest pain: a prospective cohort study.

Background: The emergency medical services (EMS) use guidelines to describe optimal patient care for a wide range of clinical conditions and symptoms. The intent is to guide personnel to provide patient care in line with best practice. The aim of this study is to describe adherence to such guidelines among prehospital emergency nurses (PENs) when caring for patients with chest pain.

Improving Machine Learning 30-Day Mortality Prediction by Discounting Surprising Deaths.

Background: Machine learning (ML) is an emerging tool for predicting need of end-of-life discussion and palliative care, by using mortality as a proxy. But deaths, unforeseen by emergency physicians at time of the emergency department (ED) visit, might have a weaker association with the ED visit.

Objectives: To develop an ML algorithm that predicts unsurprising deaths within 30 days after ED discharge.

Development of a prehospital prediction model for risk stratification of patients with chest pain.

Introduction: Chest pain is one of the most common reasons for contacting the emergency medical services (EMS). About 15% of these chest pain patients have a high-risk condition, while many of them have a low-risk condition with no need for acute hospital care. It is challenging to at an early stage distinguish whether patients have a low- or high-risk condition.

Dynamics of IgG-avidity and antibody levels after Covid-19.

Background: A potentially important aspect of the humoral immune response to Covid-19 is avidity, the overall binding strength between antibody and antigen. As low avidity is associated with a risk of re- infection in several viral infections, avidity might be of value to predict risk for reinfection with covid-19.

Objectives: The purpose of this study was to describe the maturation of IgG avidity and the antibody-levels over time in patients with PCR-confirmed non-severe covid-19.

Prehospital stratification in acute chest pain patient into high risk and low risk by emergency medical service: a prospective cohort study.

Objectives: To describe contemporary characteristics and diagnoses in prehospital patients with chest pain and to identify factors suitable for the early recognition of high-risk and low-risk conditions.

Design: Prospective observational cohort study.

Setting: Two centre study in a Swedish county emergency medical services (EMS) organisation.

Likelihood of admission to hospital from the emergency department is not universally associated with hospital bed occupancy at the time of admission.

Background: The decision to admit into the hospital from the emergency department (ED) is considered to be important and challenging. The aim was to assess whether previously published results suggesting an association between hospital bed occupancy and likelihood of hospital admission from the ED can be reproduced in a different study population.

Methods: A retrospective cohort study of attendances at two Swedish EDs in 2015 was performed.

Spatial peak and mean QRS-T angles: A comparison of similar but different emerging risk factors for cardiac death.

Background: The spatial peak and mean QRS-T angles are scientifically but not clinically established risk factors for cardiovascular events including cardiac death. The study aims were to compare these angles, assess their association with hypertension (HT) and diabetes mellitus (DM), and explore the relation between the mean QRS-T angle and the ventricular gradient (VG; reflecting electrical heterogeneity), which both are derived from the QRSarea and Tarea vectors.

Methods: Altogether 1094 participants (aged 50-65 years, 550 women) from the pilot of the population-based Swedish CArdioPulmonary bioImage Study with Frank vectorcardiographic recordings were included and divided into 5 subgroups: apparently healthy n = 320; HT n = 311; DM n = 33; DM + HT n = 53; miscellaneous conditions n = 377.

Receiving care according to national heart failure guidelines is associated with lower total costs: an observational study in Region Halland, Sweden.

Aims: Patients with heart failure (HF) have high costs, morbidity, and mortality, but it is not known if appropriate pharmacotherapy (AP), defined as compliance with international evidence-based guidelines, is associated with improved costs and outcomes. The purpose of this study was to evaluate HF patients' health care utilization, cost and outcomes in Region Halland (RH), Sweden, and if AP was associated with lower costs.

Methods And Results: A total of 5987 residents of RH in 2016 carried HF diagnoses.

Pitfalls of medication adherence approximation through EHR and pharmacy records: Definitions, data and computation.

Background And Purpose: Patients' adherence to medication is a complex, multidimensional phenomenon. Dispensation data and electronic health records are used to approximate medication-taking through refill adherence. In-depth discussions on the adverse effects of data quality and computational differences are rare.

Training machine learning models to predict 30-day mortality in patients discharged from the emergency department: a retrospective, population-based registry study.

Objectives: The aim of this work was to train machine learning models to identify patients at end of life with clinically meaningful diagnostic accuracy, using 30-day mortality in patients discharged from the emergency department (ED) as a proxy.

Design: Retrospective, population-based registry study.

Setting: Swedish health services.

Readmission prediction using deep learning on electronic health records.

Unscheduled 30-day readmissions are a hallmark of Congestive Heart Failure (CHF) patients that pose significant health risks and escalate care cost. In order to reduce readmissions and curb the cost of care, it is important to initiate targeted intervention programs for patients at risk of readmission. This requires identifying high-risk patients at the time of discharge from hospital.

Symptom description in patients with chest pain-A qualitative analysis of emergency medical calls involving high-risk conditions.

Aims And Objectives: To explore the symptoms descriptions and situational information provided by patients during ongoing chest pain events caused by a high-risk condition.

Background: Chest pain is a common symptom in patients contacting emergency dispatch centres. Only 15% of these patients are later classified as suffering from a high-risk condition.

Long-Term Effects of Oxygen Therapy on Death or Hospitalization for Heart Failure in Patients With Suspected Acute Myocardial Infarction.

Background: In the DETO2X-AMI trial (Determination of the Role of Oxygen in Suspected Acute Myocardial Infarction), we compared supplemental oxygen with ambient air in normoxemic patients presenting with suspected myocardial infarction and found no significant survival benefit at 1 year. However, important secondary end points were not yet available. We now report the prespecified secondary end points cardiovascular death and the composite of all-cause death and hospitalization for heart failure.

Prehospital factors associated with an acute life-threatening condition in non-traumatic chest pain patients - A systematic review.

Background: Chest pain is a common symptom among patients contacting the emergency medical services (EMS). Risk stratification of these patients is warranted before arrival in hospital, regarding likelihood of an acute life-threatening condition (LTC).

Aim: To identify factors associated with an increased risk of acute LTC among patients who call the EMS due to non-traumatic chest pain.

Value of the QRS-T area angle in improving the prediction of sudden cardiac death after acute coronary syndromes.

Background: Prediction of sudden cardiac death (SCD) after acute coronary syndromes (ACS) remains a challenge. Although electrophysiology measures obtained by 3-D vectorcardiography (VCG) shortly after ACS may be useful predictors of SCD, they have not been adopted into clinical practice. The main objective of our study was to assess whether the VCG-derived QRS-T area angle (between area vectors) and the QRS-T angle (between maximum vectors) have additional value beyond standard risk factors in predicting SCD after ACS.

Transient repolarization alterations dominate the initial phase of an acute anterior infarction--a vectorcardiography study.

Objective: To study effects of ischemia-reperfusion on ventricular electrophysiology in humans by three-dimensional electrocardiography.

Methods: Fifty-seven patients with first-time acute anterior ST elevation myocardial infarction were monitored from admission and >24h after symptom onset with continuous vectorcardiography (VCG; modified Frank orthogonal leads). Global ventricular depolarization and repolarization (VR) measures were compared at maximum vs.

The impact of hypertension and diabetes on outcome in patients undergoing percutaneous coronary intervention.

Objective: Information relating the outcome of percutaneous coronary intervention to diabetes mellitus or hypertension is limited. The study objective was to describe the outcome in patients undergoing percutaneous coronary intervention in relation to diabetes and hypertension.

Methods: Data were extracted from 5 national registers: the Swedish Coronary Angiography and Angioplasty Register (all percutaneous coronary interventions), the Prescribed Drug Registry (all prescribed pharmaceuticals purchased in Swedish pharmacies), the Swedish Hospital Discharge Register (data on myocardial infarction, revascularization, stroke, and congestive heart failure from in-hospital and specialist health care), and the National Population Register and Cause of Death Register (data on death).