[Familial thoracic aortic aneurysms and dissections can be divided into three different main categories]. / Familjära torakala aortaaneurysm och dissektioner - flera former finns.

Thoracic aortic aneurysms and dissections (TAAD) can be divided into three different main categories. 1. Inherited syndromes predisposing to TAAD such as Marfan syndrome, Ehlers-Danlos syndrome type IV and Loeys-Dietz syndrome (less than 5% of all TAAD). 2. Familial TAAD (FTAAD) with more than one affected family member (20 % of all TAAD). Inheritance shows an autosomal dominant pattern and there are no features of known syndromes. 3. Sporadic forms of TAAD with no family history or features of syndromic forms. FTAAD present earlier in life and dissections occur in smaller diameter than in sporadic cases. The underlying genetic cause can be found in about 20 % of the inherited cases. The pathogenesis seems to be an involvement of the transforming growth factor ß (TGFß) signaling pathway or a dysfunction of the smooth muscle cell contraction. The role of ß-blockers for aneurysm prevention is uncertain and there are on-going studies comparing angiotensin receptor blockers and ß-blockers.

[Facilitating scientific data collection systems]. / Tutkimustiedon keruuta helpottavat tietojärjestelmät.

Electronic information systems continuously accumulate huge amounts of quantitative information related to the functioning of primary health care and utilizable in the monitoring of the population's health status, correct allocation of resources and in many types of research. A centralized data bank can function as a general practice research network, the members collecting data both for their own studies and for studies carried out by others. In Finland a computer-assisted "virtual health check" involving the whole population was carried out in Sipoo in 2009.

[Experiences from a multidisciplinary cardiogenetic clinic]. / Ärftliga hjärt­kärlsjukdomar ­ ett multidisciplinärt arbetssätt krävs.

Comprehensive genetic and clinical care of families with monogenic cardiovascular diseases requires competences from different medical specialties. Genetic assessment, cascade screening, risk estimation, treatment and follow-up is difficult to cover. Fourteen years ago, a center for cardiovascular diseases was created in our hospital, to improve the care of families with monogenic cardiovascular diseases. At our center, clinical geneticists, cardiologists, angiologists, pediatric cardiologists and genetic counselors work together in a seamless organization, while still having different clinic affiliations. A key feature of this organization are the family outpatient clinics, where the proband and his/her relatives at genetic risk are invited to take part. When the family or relatives live in other parts of the country, they are invited to participate through video conference.  In this paper we report our experiences and working routines from more than 300 families and 2000 individuals.

Coding Systems for Clinical Decision Support: Theoretical and Real-World Comparative Analysis.

BACKGROUND: Effective clinical decision support systems require accurate translation of practice recommendations into machine-readable artifacts; developing code sets that represent clinical concepts are an important step in this process. Many clinical coding systems are currently used in electronic health records, and it is unclear whether all of these systems are capable of efficiently representing the clinical concepts required in executing clinical decision support systems. OBJECTIVE: The aim of this study was to evaluate which clinical coding systems are capable of efficiently representing clinical concepts that are necessary for translating artifacts into executable code for clinical decision support systems. METHODS: Two methods were used to evaluate a set of clinical coding systems. In a theoretical approach, we extracted all the clinical concepts from 3 preventive care recommendations and constructed a series of code sets containing codes from a single clinical coding system. In a practical approach using data from a real-world setting, we studied the content of 1890 code sets used in an internationally available clinical decision support system and compared the usage of various clinical coding systems. RESULTS: SNOMED CT and ICD-10 (International Classification of Diseases, Tenth Revision) proved to be the most accurate clinical coding systems for most concepts in our theoretical evaluation. In our practical evaluation, we found that International Classification of Diseases (Tenth Revision) was most often used to construct code sets. Some coding systems were very accurate in representing specific types of clinical concepts, for example, LOINC (Logical Observation Identifiers Names and Codes) for investigation results and ATC (Anatomical Therapeutic Chemical Classification) for drugs. CONCLUSIONS: No single coding system seems to fulfill all the needs for representing clinical concepts for clinical decision support systems. Comprehensiveness of the coding systems seems to be offset by complexity and forms a barrier to usability for code set construction. Clinical vocabularies mapped to multiple clinical coding systems could facilitate clinical code set construction.

Optimization of mass transfer for toxin removal and immunoprotection of hepatocytes in a bioartificial liver.

This study was designed to determine optimal operating conditions of a bioartificial liver (BAL) based on mass transfer of representative hepatotoxins and mediators of immune damage. A microprocessor-controlled BAL was used to study mass transfer between patient and cell compartments separated by a hollow fiber membrane. Membrane permeability (70, 150, or 400 kDa molecular weight cut-off-MWCO), membrane convection (high: 50 mL/min; medium: 25 mL/min; low: 10 mL/min; diffusion: 0 mL/min), and albumin concentration in the cell compartment (0.5 or 5 g%) were considered for a total of 24 test conditions. Initially, the patient compartment contained pig plasma supplemented with ammonia (0.017 kDa), unconjugated bilirubin (0.585 kDa), conjugated bilirubin (0.760 kDa), TNF-alpha (17 kDa), pig albumin (67 kDa), pig IgG (147 kDa), and pig IgM (900 kDa). Mass transfer of each substance was determined by its rate of appearance in the cell compartment. Membrane fouling was assessed by dextran polymer technique. Of the three tested variables (membrane pore size, convection, and albumin concentration), membrane permeability had the greatest impact on mass transfer (P < 0.001). Mass transfer of all toxins was greatest under high convection with a 400 kDa membrane. Transfer of IgG and IgM was insignificant under all conditions. Bilirubin transfer was increased under high albumin conditions (P = 0.055). Fouling of membranes ranged from 7% (400 kDa), 24% (150 kDa) to 62% (70 kDa) during a 2-h test interval. In conclusion, optimal toxin removal was achieved under high convection with a 400-kDa membrane, a condition which should provide adequate immunoprotection of hepatocytes in the BAL.

Effectiveness of a Hospital-Based Computerized Decision Support System on Clinician Recommendations and Patient Outcomes: A Randomized Clinical Trial.

Importance: Sophisticated evidence-based information resources can filter medical evidence from the literature, integrate it into electronic health records, and generate recommendations tailored to individual patients. Objective: To assess the effectiveness of a computerized clinical decision support system (CDSS) that preappraises evidence and provides health professionals with actionable, patient-specific recommendations at the point of care. Design, Setting, and Participants: Open-label, parallel-group, randomized clinical trial among internal medicine wards of a large Italian general hospital. All analyses in this randomized clinical trial followed the intent-to-treat principle. Between November 1, 2015, and December 31, 2016, patients were randomly assigned to the intervention group, in which CDSS-generated reminders were displayed to physicians, or to the control group, in which reminders were generated but not shown. Data were analyzed between February 1 and July 31, 2018. Interventions: Evidence-Based Medicine Electronic Decision Support (EBMEDS), a commercial CDSS covering a wide array of health conditions across specialties, was integrated into the hospital electronic health records to generate patient-specific recommendations. Main Outcomes and Measures: The primary outcome was the resolution rate, the rate at which medical problems identified and alerted by the CDSS were addressed by a change in practice. Secondary outcomes included the length of hospital stay and in-hospital all-cause mortality. Results: In this randomized clinical trial, 20 563 patients were admitted to the hospital. Of these, 6480 (31.5%) were admitted to the internal medicine wards (study population) and randomized (3242 to CDSS and 3238 to control). The mean (SD) age of patients was 70.5 (17.3) years, and 54.5% were men. In total, 28 394 reminders were generated throughout the course of the trial (median, 3 reminders per patient per hospital stay; interquartile range [IQR], 1-6). These messages led to a change in practice in approximately 4 of 100 patients. The resolution rate was 38.0% (95% CI, 37.2%-38.8%) in the intervention group and 33.7% (95% CI, 32.9%-34.4%) in the control group, corresponding to an odds ratio of 1.21 (95% CI, 1.11-1.32; P < .001). The length of hospital stay did not differ between the groups, with a median time of 8 days (IQR, 5-13 days) for the intervention group and a median time of 8 days (IQR, 5-14 days) for the control group (P = .36). In-hospital all-cause mortality also did not differ between groups (odds ratio, 0.95; 95% CI, 0.77-1.17; P = .59). Alert fatigue did not differ between early and late study periods. Conclusions and Relevance: An international commercial CDSS intervention marginally influenced routine practice in a general hospital, although the change did not statistically significantly affect patient outcomes. Trial Registration: ClinicalTrials.gov identifier: NCT02577198.

Decision Support for Diabetes in Scotland: Implementation and Evaluation of a Clinical Decision Support System.

BACKGROUND: Automated clinical decision support systems (CDSS) are associated with improvements in health care delivery to those with long-term conditions, including diabetes. A CDSS was introduced to two Scottish regions (combined diabetes population ~30 000) via a national diabetes electronic health record. This study aims to describe users' reactions to the CDSS and to quantify impact on clinical processes and outcomes over two improvement cycles: December 2013 to February 2014 and August 2014 to November 2014. METHODS: Feedback was sought via patient questionnaires, health care professional (HCP) focus groups, and questionnaires. Multivariable regression was used to analyze HCP SCI-Diabetes usage (with respect to CDSS message presence/absence) and case-control comparison of clinical processes/outcomes. Cases were patients whose HCP received a CDSS messages during the study period. Closely matched controls were selected from regions outside the study, following similar clinical practice (without CDSS). Clinical process measures were screening rates for diabetes-related complications. Clinical outcomes included HbA1c at 1 year. RESULTS: The CDSS had no adverse impact on consultations. HCPs were generally positive toward CDSS and used it within normal clinical workflow. CDSS messages were generated for 5692 cases, matched to 10 667 controls. Following clinic, the probability of patients being appropriately screened for complications more than doubled for most measures. Mean HbA1c improved in cases and controls but more so in cases (-2.3 mmol/mol [-0.2%] versus -1.1 [-0.1%], P = .003). DISCUSSION AND CONCLUSIONS: The CDSS was well received; associated with improved efficiencies in working practices; and large improvements in guideline adherence. These evidence-based, early interventions can significantly reduce costly and devastating complications.

Implementing an evidence-based computerized decision support system to improve patient care in a general hospital: the CODES study protocol for a randomized controlled trial.

BACKGROUND: Computerized decision support systems (CDSSs) are information technology-based software that provide health professionals with actionable, patient-specific recommendations or guidelines for disease diagnosis, treatment, and management at the point-of-care. These messages are intelligently filtered to enhance the health and clinical care of patients. CDSSs may be integrated with patient electronic health records (EHRs) and evidence-based knowledge. METHODS/DESIGN: We designed a pragmatic randomized controlled trial to evaluate the effectiveness of patient-specific, evidence-based reminders generated at the point-of-care by a multi-specialty decision support system on clinical practice and the quality of care. We will include all the patients admitted to the internal medicine department of one large general hospital. The primary outcome is the rate at which medical problems, which are detected by the decision support software and reported through the reminders, are resolved (i.e., resolution rates). Secondary outcomes are resolution rates for reminders specific to venous thromboembolism (VTE) prevention, in-hospital all causes and VTE-related mortality, and the length of hospital stay during the study period. DISCUSSION: The adoption of CDSSs is likely to increase across healthcare systems due to growing concerns about the quality of medical care and discrepancy between real and ideal practice, continuous demands for a meaningful use of health information technology, and the increasing use of and familiarity with advanced technology among new generations of physicians. The results of our study will contribute to the current understanding of the effectiveness of CDSSs in primary care and hospital settings, thereby informing future research and healthcare policy questions related to the feasibility and value of CDSS use in healthcare systems. This trial is seconded by a specialty trial randomizing patients in an oncology setting (ONCO-CODES). TRIAL REGISTRATION: ClinicalTrials.gov, https://clinicaltrials.gov/ct2/show/NCT02577198?term=NCT02577198&rank=1.

Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial.

BACKGROUND: Computerized decision support systems (CDSSs) are computer programs that provide doctors with person-specific, actionable recommendations, or management options that are intelligently filtered or presented at appropriate times to enhance health care. CDSSs might be integrated with patient electronic health records (EHRs) and evidence-based knowledge. METHODS/DESIGN: The Computerized DEcision Support in ONCOlogy (ONCO-CODES) trial is a pragmatic, parallel group, randomized controlled study with 1:1 allocation ratio. The trial is designed to evaluate the effectiveness on clinical practice and quality of care of a multi-specialty collection of patient-specific reminders generated by a CDSS in the IRCCS Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) hospital. We hypothesize that the intervention can increase clinician adherence to guidelines and, eventually, improve the quality of care offered to cancer patients. The primary outcome is the rate at which the issues reported by the reminders are resolved, aggregating specialty and primary care reminders. We will include all the patients admitted to hospital services. All analyses will follow the intention-to-treat principle. DISCUSSION: The results of our study will contribute to the current understanding of the effectiveness of CDSSs in cancer hospitals, thereby informing healthcare policy about the potential role of CDSS use. Furthermore, the study will inform whether CDSS may facilitate the integration of primary care in cancer settings, known to be usually limited. The increasing use of and familiarity with advanced technology among new generations of physicians may support integrated approaches to be tested in pragmatic studies determining the optimal interface between primary and oncology care. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02645357.

Tibial intramedullary nails -- should they be removed? A retrospective study of 71 patients.

BACKGROUND: Anterior knee pain and young age of the patient have been considered justification for removal of a tibial intramedullary nail. There have been few reports on the outcome after nail removal, however. PATIENTS AND METHODS: We studied 71 patients in whom 72 tibial nails had been removed. We used self-assess-ment questionnaires to evaluate the location, intensity, and frequency of pain before and after removal. The degree of satisfaction was scored on a visual analog scale. RESULTS: 39 of 71 patients had less pain after removal of the nail, but were not asymptomatic. 14 patients had unaltered pain, and 18 patients had increased pain. 4 of 6 patients who had been treated with fasciotomy were not satisfied with the outcome of nail removal. INTERPRETATION: The results of nail removal to alleviate pain are poor. Removal of a nail should not be undertaken unless there is a convincing indication.

Decreased production of reactive oxygen species by blood monocytes caused by clozapine correlates with EEG slowing in schizophrenic patients.

We have earlier reported an increased theta-power value in clozapine (CLO)-treated patients with schizophrenia, nonresponsive to conventional antipsychotics. We also found that the decrease in the production of reactive oxygen species (ROS), induced by CLO, by peripheral blood monocytes (MO) of these patients correlates with clinical improvement. MO share the capability of ROS production with their more mature descendants, microglia of the brain. We hypothesized that the CLO-related changes in peripheral blood MO might be related to a parallel process in microglia and thus be reflected in brain activity. In those 8 patients for whom both QEEG and MO data were available, we explored possible relationships between these parameters. A clear-cut correlation between ROS production (R(2) = 0.929, p < 0.05) for nonstimulated MO, and (R(2) = 0.907, p < 0.001) for stimulated MO and theta-power values in the central frontal electrode (F(z)) was found. It is intriguing to speculate that the EEG slowing is a result of the modulatory action of the activated microglial cells in the central nervous system via production of ROS or cytokines or both. However, this proposition has to be confirmed by future research.