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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. Synthetic data, i.e., artificial but realistic electronic health records, could overcome the drought that is troubling the healthcare sector. Deep neural network architectures, in particular, have shown an incredible ability to learn from complex data sets and generate large amounts of unseen data points with the same statistical properties as the training data. Here, we present a generative neural network model that can create synthetic health records with realistic timelines. These clinical trajectories are generated on a per-patient basis and are represented as linear-sequence graphs of clinical events over time. We use a variational graph autoencoder (VGAE) to generate synthetic samples from real-world electronic health records. Our approach generates health records not seen in the training data. We show that these artificial patient trajectories are realistic and preserve patient privacy and can therefore support the safe sharing of data across organizations. [ABSTRACT FROM AUTHOR]

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. Non-hospitalised patients with PCR-confirmed covid-19 were prospectively invited to self-report assessments of background data, symptoms and recovery, illness perception (BIPQ) and health-related quality of life (HR-Qol) measured by EQ5D-VAS. 154 patients were included (mean age 46 years, 69% female). The majority of participants (65%) had symptoms for 1–4 weeks and 12% more than 6 months. The most common symptoms were initially malaise, fatigue, headache, fever and cough and the most common long-term symptoms were impaired physical condition, fatigue, anosmia and headache. The BIPQ index had a negative correlation with the EQ5D-VAS score after the infection, but not with long-term symptoms. Mean differences in the EQ5D-VAS score were significantly lower after the infection and patients with long-term symptoms had a more pronounced negative effect in EQ5D-VAS scores. We found that most patients with non-severe covid-19 reported symptoms for 1–4 weeks and approximately 10% developed long-term symptoms. Non-severe covid-19 seems to have a negative influence on HR-Qol, especially in patients with long-term symptoms and with a greater burden from the disease. None of the initial symptoms could predict the presence of long-term symptoms. [ABSTRACT FROM AUTHOR]

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. Results: Prediction models were developed for the identification of patients suitable for high- and low-priority dispatch, using 11 and 10 variables respectively. The area under the receiver-operating characteristic curve (AUROC) for the high-risk prediction model was 0.79 and for the low-risk model it was 0.74. When applying the high-risk prediction model, 56% of the EMS missions were given highest priority, compared with 65% with the current standard. When applying the low-risk model, 7% were given the lowest priority compared to 1% for the current standard. The new prediction models outperformed today's dispatch priority accuracy in terms of sensitivity as well as positive and negative predictive value in both high- and low-risk prediction. The low-risk model predicted almost six times as many patients as having low-risk conditions compared with today's standard. This was done without increasing the number of high-risk patients wrongly assessed as low-risk. Conclusions: By introducing prediction models, based on logistic regression analyses, using variables obtained by standard EMD-questions on age, sex, medical history and symptomology, EMD prioritisation can be improved compared with using current criteria index-based ones. This will allow a more efficient emergency medical services resource allocation. [ABSTRACT FROM AUTHOR]

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. Objective: To describe guideline adherence among PENs when caring for patients with chest pain. To investigate whether guideline adherence is associated with patient age, sex or final diagnosis of acute myocardial infarction on hospital discharge. Methods: Guideline adherence in terms of patient examination and pharmaceutical treatment was analysed in a cohort of 2092 EMS missions carried out in 2018 in Region Halland, Sweden. Multivariate regression was used to describe how guideline adherence is associated with patient age, sex and diagnosis on hospital discharge. Results: Guideline adherence was high regarding examination of vital signs (93%) and electrocardiogram (ECG) registration (96%) but lower in terms of pharmaceutical treatment (ranging from 28 to 90%). Adherence was increased in cases in which the patient ended up with acute myocardial infarction (AMI) as diagnosis on discharge. Patients with AMI were given acetylsalicylic acid by PENs in 50% of cases. Women were less likely than men to receive treatment with acetylsalicylic acid and oxycodone. Conclusions: Guideline adherence among PENs when caring for patients with chest pain is satisfactory in terms vital signs and ECG registration. Regarding pharmaceutical treatment guideline adherence is defective. Improved adherence is mainly associated with male sex in patients and a diagnosis of AMI on hospital discharge. Defective adherence excludes measures known to improve patients' prognoses such as treatment with acetylsalicylic acid. [ABSTRACT FROM AUTHOR]

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. Prehospital personnel are largely dependent on symptom characteristics when trying to identify these patients. Design: Qualitative descriptive. Methods: Manifest content analysis of 56 emergency medical calls involving patients with chest pain was carried out. A stratified purposive sampling was used to obtain calls concerning patients with high‐risk conditions. These calls were then listened to and transcribed. Thereafter, meaning units were identified and coded and finally categorised. Consolidated criteria for reporting qualitative studies guidelines have been applied. Results: A wide range of situational information and symptoms descriptions was found. Pain and affected breathing were dominating aspects, but other situational information and several other symptoms were also reported. The situational information and these symptoms were classified into seven categories: Pain narrative, Affected breathing, Bodily reactions, Time, Bodily whereabouts, Fear and concern and Situation management. The seven categories consisted of 17 subcategories. Conclusions: Patients with chest pain caused by a high‐risk condition present a wide range of symptoms which are described in a variety of ways. They describe different kinds of chest pain accompanied by pain from other parts of the body. Breathing difficulties and bodily reactions such as muscle weakness are also reported. The variety of symptoms and the absence of a typical symptomatology make risk stratification on the basis of symptoms alone difficult. Relevance to clinical practice: This study highlights the importance of an open mind when assessing patients with chest pain and the requirement of a decision support tool in order to improve risk stratification in these patients. [ABSTRACT FROM AUTHOR]

The article presents the findings of a study, which examined the long-term relationship between casual blood pressure measurement and future hypertension. The initial study group consisted of 20-year-old men with mild blood pressure elevation and a normotensive male control group. After 30 years, it was found that 38% in the group with blood pressure elevation at baseline had developed hypertension, as compared to 10% in the control group. There was a significant positive relationship between baseline systolic blood pressure and diastolic blood pressure and systolic blood pressure 30 years later.