German Clinical Trials Register (Deutsches Register Klinischer Studien, DRKS) No. DRKS00000145.

Critical Care 2017, 21(Suppl 1):P349 Introduction Imbalance in cellular energetics has been suggested to be an important mechanism for organ failure in sepsis and septic shock. We hypothesized that such energy imbalance would either be caused by metabolic changes leading to decreased energy production or by increased energy consumption. Thus, we set out to investigate if mitochondrial dysfunction or decreased energy consumption alters cellular metabolism in muscle tissue in experimental sepsis. Methods We submitted anesthetized piglets to sepsis (n = 12) or placebo (n = 4) and monitored them for 3 hours. Plasma lactate and markers of organ failure were measured hourly, as was muscle metabolism by microdialysis. Energy consumption was intervened locally by infusing ouabain through one microdialysis catheter to block major energy expenditure of the cells, by inhibiting the major energy consuming enzyme, N+/K + -ATPase. Similarly, energy production was blocked infusing sodium cyanide (NaCN), in a different region, to block the cytochrome oxidase in muscle tissue mitochondria. Results All animals submitted to sepsis fulfilled sepsis criteria as defined in Sepsis-3, whereas no animals in the placebo group did. Muscle glucose decreased during sepsis independently of N+/K + -ATPase or cytochrome oxidase blockade. Muscle lactate did not increase during sepsis in naïve metabolism. However, during cytochrome oxidase blockade, there was an increase in muscle lactate that was further accentuated during sepsis. Muscle pyruvate did not decrease during sepsis in naïve metabolism. During cytochrome oxidase blockade, there was a decrease in muscle pyruvate, independently of sepsis. Lactate to pyruvate ratio increased during sepsis and was further accentuated during cytochrome oxidase blockade. Muscle glycerol increased during sepsis and decreased slightly without sepsis regardless of N+/K + -ATPase or cytochrome oxidase blocking. There were no significant changes in muscle glutamate or urea during sepsis in absence/presence of N+/K + -ATPase or cytochrome oxidase blockade. ConclusionsThese results indicate increased metabolism of energy substrates in muscle tissue in experimental sepsis. Our results do not indicate presence of energy depletion or mitochondrial dysfunction in muscle and should similar physiologic situation be present in other tissues, other mechanisms of organ failure must be considered. , and long-term follow up has shown increased fracture risk [2]. It is unclear if these changes are a consequence of acute critical illness, or reduced activity afterwards. Bone health assessment during critical illness is challenging, and direct bone strength measurement is not possible. We used a rodent sepsis model to test the hypothesis that critical illness causes early reduction in bone strength and changes in bone architecture. Methods 20 Sprague-Dawley rats (350 ± 15.8g) were anesthetised and randomised to receive cecal ligation and puncture (CLP) (50% cecum length, 18G needle single pass through anterior and posterior wa...

BackgroundAlthough polypharmacy can cause adverse health outcomes, patients often know little about their medication. A regularly conducted medication review (MR) can help provide an overview of a patient’s medication, and benefit patients by enhancing their knowledge of their drugs. As little is known about patient attitudes towards MRs in primary care, the objective of this study was to gain insight into patient-perceived barriers and facilitators to the implementation of an MR.MethodsWe conducted a qualitative study with a convenience sample of 31 patients (age ≥ 60 years, ≥3 chronic diseases, taking ≥5 drugs/d); in Hesse, Germany, in February 2016. We conducted two focus groups and, in order to ensure the participation of elderly patients with reduced mobility, 16 telephone interviews. Both relied on a semi-structured interview guide dealing with the following subjects: patients’ experience of polypharmacy, general design of MRs, potential barriers and facilitators to implementation etc. Interviews were audio-recorded, transcribed verbatim, and analysed by two researchers using thematic analysis.ResultsPatients’ average age was 74 years (range 62–88 years). We identified barriers and facilitators for four main topics regarding the implementation of MRs in primary care: patient participation, GP-led MRs, pharmacist-led MRs, and the involvement of healthcare assistants in MRs. Barriers to patient participation concerned patient autonomy, while facilitators involved patient awareness of medication-related problems. Barriers to GP-led MRs concerned GP’s lack of resources while facilitators related to the trusting relationship between patient and GP. Pharmacist-led MRs might be hindered by a lack of patients’ confidence in pharmacists’ expertise, but facilitated by pharmacies’ digital records of the patients’ medications. Regarding the involvement of healthcare assistants in MRs, a potential barrier was patients’ uncertainty regarding the extent of their training. Patients could, however, imagine GPs delegating some aspects of MRs to them.ConclusionsOur study suggests that patients regard MRs as beneficial and expect indications for their medicines to be checked, and possible interactions to be identified. To foster the implementation of MRs in primary care, it is important to consider barriers and facilitators to the four identified topics.Electronic supplementary materialThe online version of this article (10.1186/s12875-017-0707-0) contains supplementary material, which is available to authorized users.

Background: Experienced and anticipated regret influence physicians' decision-making. In medicine, diagnostic decisions and diagnostic errors can have a severe impact on both patients and physicians. Little empirical research exists on regret experienced by physicians when they make diagnostic decisions in primary care that later prove inappropriate or incorrect. The aim of this study was to explore the experience of regret following diagnostic decisions in primary care. Methods: In this qualitative study, we used an online questionnaire on a sample of German primary care physicians. We asked participants to report on cases in which the final diagnosis differed from their original opinion, and in which treatment was at the very least delayed, possibly resulting in harm to the patient. We asked about original and final diagnoses, illness trajectories, and the reactions of other physicians, patients and relatives. We used thematic analysis to assess the data, supported by MAXQDA 11 and Microsoft Excel 2016. Results: 29 GPs described one case each (14 female/15 male patients, aged 1.5-80 years, response rate < 1%). In 26 of 29 cases, the final diagnosis was more serious than the original diagnosis. In two cases, the diagnoses were equally serious, and in one case less serious. Clinical trajectories and the reactions of patients and relatives differed widely. Although only one third of cases involved preventable harm to patients, the vast majority (27 of 29) of physicians expressed deep feelings of regret. Conclusion: Even if harm to patients is unavoidable, regret following diagnostic decisions can be devastating for clinicians, making them 'second victims'. Procedures and tools are needed to analyse cases involving undesirable diagnostic events, so that 'true' diagnostic errors, in which harm could have been prevented, can be distinguished from others. Further studies should also explore how physicians can be supported in dealing with such events in order to prevent them from practicing defensive medicine.

BackgroundCritical incident reporting systems (CIRS) can be an important tool for the identification of organisational safety needs and thus to improve patient safety. In German primary care, CIRS use is obligatory but remains rare. Studies on CIRS implementation in primary care are lacking, but those from secondary care recommend involving management personnel.ObjectiveThis project aimed to increase CIRS use in 69 practices belonging to a local practice network.MethodsThe intervention consisted of the provision of a web-based CIRS, accompanying measures to train practice teams in error management and CIRS, and the involvement of the network’s management. Three measurements were used: (1) number of incident reports and user access rates to the web-based CIRS were recorded, (2) staff were given a questionnaire addressing incident reporting, error management and safety climate and (3) qualitative reflection conferences were held with network management.ResultsOver 20 months, 17 critical incidents were reported to the web-based CIRS. The number of staff intending to report the next incident online decreased from 42% to 20% of participants. In contrast, the number of practices using an offline CIRS (eg, incident book) increased from 23% to 49% of practices. Practices also began proactively approaching network management for help with incidents. After project completion, participants scored higher in the patient safety climate factor ‘perception of causes of errors’. For many practices, the project provided the first contact with structured error management.ConclusionSpecific measures to improve the use of CIRS in primary care should focus on network management and practice owners. Practices need basic training on safety culture and error management. Continuing, practices should implement an offline CIRS, before they can profit from the exchange of reports via web-based CIRS. It is crucial that practices receive feedback on incidents, and trained network management personnel can provide such support.

IntroductionClinically complex patients often require multiple medications. Polypharmacy is associated with inappropriate prescriptions, which may lead to negative outcomes. Few effective tools are available to help physicians optimise patient medication. This study assesses whether an electronic medication management support system (eMMa) reduces hospitalisation and mortality and improves prescription quality/safety in patients with polypharmacy.Methods and analysisPlanned design: pragmatic, parallel cluster-randomised controlled trial; general practices as randomisation unit; patients as analysis unit. As practice recruitment was poor, we included additional data to our primary endpoint analysis for practices and quarters from October 2017 to March 2021. Since randomisation was performed in waves, final study design corresponds to a stepped-wedge design with open cohort and step-length of one quarter. Scope: general practices, Westphalia-Lippe (Germany), caring for BARMER health fund-covered patients. Population: patients (≥18 years) with polypharmacy (≥5 prescriptions). Sample size: initially, 32 patients from each of 539 practices were required for each study arm (17 200 patients/arm), but only 688 practices were randomised after 2 years of recruitment. Design change ensures that 80% power is nonetheless achieved. Intervention: complex intervention eMMa. Follow-up: at least five quarters/cluster (practice). recruitment: practices recruited/randomised at different times; after follow-up, control group practices may access eMMa. Outcomes: primary endpoint is all-cause mortality and hospitalisation; secondary endpoints are number of potentially inappropriate medications, cause-specific hospitalisation preceded by high-risk prescribing and medication underuse. Statistical analysis: primary and secondary outcomes are measured quarterly at patient level. A generalised linear mixed-effect model and repeated patient measurements are used to consider patient clusters within practices. Time and intervention group are considered fixed factors; variation between practices and patients is fitted as random effects. Intention-to-treat principle is used to analyse primary and key secondary endpoints.Ethics and disseminationTrial approved by Ethics Commission of North-Rhine Medical Association. Results will be disseminated through workshops, peer-reviewed publications, local and international conferences.Trial registrationNCT03430336. ClinicalTrials.gov (https://clinicaltrials.gov/ct2/show/NCT03430336).

BackgroundPolypharmacy interventions are resource-intensive and should be targeted to those at risk of negative health outcomes. Our aim was to develop and internally validate prognostic models to predict health-related quality of life (HRQoL) and the combined outcome of falls, hospitalisation, institutionalisation and nursing care needs, in older patients with multimorbidity and polypharmacy in general practices.MethodsDesign: two independent data sets, one comprising health insurance claims data (n=592 456), the other data from the PRIoritising MUltimedication in Multimorbidity (PRIMUM) cluster randomised controlled trial (n=502). Population: ≥60 years, ≥5 drugs, ≥3 chronic diseases, excluding dementia. Outcomes: combined outcome of falls, hospitalisation, institutionalisation and nursing care needs (after 6, 9 and 24 months) (claims data); and HRQoL (after 6 and 9 months) (trial data). Predictor variables in both data sets: age, sex, morbidity-related variables (disease count), medication-related variables (European Union-Potentially Inappropriate Medication list (EU-PIM list)) and health service utilisation. Predictor variables exclusively in trial data: additional socio-demographics, morbidity-related variables (Cumulative Illness Rating Scale, depression), Medication Appropriateness Index (MAI), lifestyle, functional status and HRQoL (EuroQol EQ-5D-3L). Analysis: mixed regression models, combined with stepwise variable selection, 10-fold cross validation and sensitivity analyses.ResultsMost important predictors of EQ-5D-3L at 6 months in best model (Nagelkerke’s R² 0.507) were depressive symptoms (−2.73 (95% CI: −3.56 to −1.91)), MAI (−0.39 (95% CI: −0.7 to −0.08)), baseline EQ-5D-3L (0.55 (95% CI: 0.47 to 0.64)). Models based on claims data and those predicting long-term outcomes based on both data sets produced low R² values. In claims data-based model with highest explanatory power (R²=0.16), previous falls/fall-related injuries, previous hospitalisations, age, number of involved physicians and disease count were most important predictor variables.ConclusionsBest trial data-based model predicted HRQoL after 6 months well and included parameters of well-being not found in claims. Performance of claims data-based models and models predicting long-term outcomes was relatively weak. For generalisability, future studies should refit models by considering parameters representing well-being and functional status.

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