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Bedside teaching (BST) has a long tradition and a firm place in medical education. In light of the often-described decrease in bedside teaching, there are now efforts to use the remaining time as efficiently as possible. However, there is little research on tangible quality characteristics of good BST. [for full text, please go to the a.m. URL]

Purpose This study aimed to assess the distinctive features of patients with infected ascites and liver cirrhosis and develop a scoring system allowing to accurately identify patients who do not require abdominocentesis to rule out infected ascites. Methods A total of 700 episodes of patients with decompensated liver cirrhosis undergoing abdominocentesis between 2006 and 2020 were included. 532 spontaneous bacterial peritonitis episodes and 37 secondary peritonitis episodes were compared to a control group of 125 patients with 131 episodes of non-infected ascites. Overall, 34 clinical, drug, and laboratory features were evaluated using machine learning to identify key differentiation criteria and integrate them into a point-score model. Results The most important distinction criteria between infected and non-infected ascites were inflammatory markers C-reactive protein and leukocyte count, the occurrence of organ failure, fever, and comorbidities. In total, 11 discriminatory features were selected using a Lasso regression model to establish a point-score model. Considering a pre-test probability for infected ascites of 10%, 15%, and 25%, the negative and positive predictive values of the point-score model for infected ascites were 98.1%, 97.0%, 94.6% and 14.9%, 21.8%, and 34.5%, respectively. Besides the main model, a simplified model was generated, containing only features that are fast to collect, and revealed similar predictive values. Conclusions Our point-score model appears to be a promising non-invasive approach to rule out abdominocentesis in clinical routine with high negative predictive values in patients with hydropic decompensated liver cirrhosis. Diagnosis of infected ascites, on the other hand, requires abdominocentesis.

Objective: Evidence on the cost-effectiveness of screening for colorectal cancer (CRC) in the German general population remains scarce as key input parameters, the costs to treat CRC, are largely unknown. Here, we provide detailed estimates on CRC treatment costs over time. Methods: Using insurance claims data from the Vilua healthcare research database, we included subjects with newly diagnosed CRC and subjects who died of CRC between 2012 and 2016. We assessed annualized CRC-related inpatient, outpatient and medication costs for up to five years after first diagnosis and prior to death, stratified by sex and age. Findings: We identified 1748 and 1117 subjects with follow-up data for at least 1 year after diagnosis and prior to death, respectively. In those newly diagnosed, average costs were highest in the first year after diagnosis (men, EUR 16,375–16,450; women, EUR 10,071–13,250) and dropped steeply in the following years, with no consistent pattern of differences with respect to age. Costs prior to death were substantially higher as compared to the initial phase of care and consistently on a high level even several years before death, peaking in the final year of life, with strong differences by sex and age (men vs. women

Background There is no universally accepted treatment standard for idiopathic toe walking patients (ITW) in the current literature. None of the established methods provide homogenous satisfying results. In our department we treat ITW patients with lower leg orthoses with a circular foot unit for a total of 16 weeks. In this study we reviewed our database to evaluate the success of our treatment protocol for a 24 months follow up period. Results Twenty-two patients were included in this study. Age at the beginning of treatment was 7.0 years +/− 2.9 (range 2.5-13.1). Percentage of ITW at the beginning of treatment according to the perception of the parents was 89% +/− 22.2 (range 50-100). Immediately after the treatment with our device, percentage of ITW dropped to 11% +/− 13.2 (range 0-50). After 12 months, 73% of the patients (16/22) walked completely normal or showed ITW less than 10% of the day. After 24 months, 64% of the patients kept a normal gait (14/22). Conclusion This study provides evidence that the treatment of idiopathic toe walking with lower leg orthoses with a circular foot unit results in satisfying long-term results in two thirds of the patients.

Background: In chronically ill patients, medication adherence during implementation can be crucial for treatment success and can decrease health costs. In some populations, regression models do not show this relationship. We aim to estimate subgroup-specific and personalized effects to identify target groups for interventions.Methods: We defined three cohorts of patients with type 1 diabetes (n = 12,713), type 2 diabetes (n = 85,162) and hyperlipidemia (n = 117,485) from German claims data between 2012 and 2015. We estimated the association of adherence during implementation in the first year (proportion of days covered) and mean total costs in the three following years, controlled for sex, age, Charlson’s Comorbidity Index, initial total costs, severity of the disease and surrogates for health behavior. We fitted three different types of models on training data: 1) linear regression models for the overall conditional associations between adherence and costs, 2) model-based trees to identify subgroups of patients with heterogeneous adherence effects, and 3) model-based random forests to estimate personalized adherence effects. To assess the performance of the latter, we conditionally re-estimated the personalized effects using test data, the fixed structure of the forests, and fixed effect estimates of the remaining covariates.Results: 1) our simple linear regression model estimated a positive adherence effect, that is an increase in total costs of 10.73 Euro per PDC-point and year for diabetes type 1, 3.92 Euro for diabetes type 2 and 1.92 Euro for hyperlipidemia (all p ≤ 0.001). 2) The model-based tree detected subgroups with negative estimated adherence effects for diabetes type 2 (-1.69 Euro, 24.4% of cohort) and hyperlipidemia (-0.11 Euro, 36.1% and -5.50 Euro, 5.3%). 3) Our model-based random forest estimated personalized adherence effects with a significant proportion (4.2%–24.1%) of negative effects (up to -8.31 Euro). The precision of these estimates was high for diabetes type 2 and hyperlipidemia patients.Discussion: Our approach shows that tree-based models can identify patients with different adherence effects and the precision of personalized effects is measurable. Identified patients can form target groups for adherence-promotion interventions. The method can also be applied to other outcomes such as hospitalization risk to maximize positive health effects of an intervention.

ObjectivesTo estimate the treatment incidence of Post-Covid Syndrome in the context of office-based care in Bavaria, Germany, and to establish whether related diagnoses occur more frequently than in patients with no known history of COVID-19.DesignRetrospective analysis of routinely collected claims data.SettingOffice-based care in Bavaria, Germany.Participants391,990 patients with confirmed COVID-19 diagnosis, 62,659 patients with other respiratory infection, and a control group of 659,579 patients with no confirmed or suspected diagnosis COVID-19.Primary and Secondary Outcome MeasuresPrimary outcome is diagnosis of a Post-COVID Syndrome by an office-based physician. Secondary outcomes are: Chronic Fatigue Syndrome (CFS), psychological disorder, fatigue, mild cognitive impairment, disturbances of taste and smell, dyspnea, pulmonary embolism and myalgia.ResultsAmong all patients with confirmed COVID-19 infection, 14.2% (95% CI: 14.0-14.5) received a diagnosis of a Post-COVID Syndrome, and 6.7% (6.5-6.9) received the diagnosis in at least two quarterly periods during a two-year follow-up. Compared with patients with other respiratory infections and with controls, patients with COVID-19 more frequently received a variety of diagnoses including CFS (1.6% vs. 0.6% and 0.3%, respectively), fatigue (13.3% vs. 9.2% and 6.0%), dyspnea (9.9% vs. 5.1% and 3.2%) and disturbances of taste and smell (3.2% vs. 1.2% and 0.5%). The treatment incidence of Post-COVID Syndrome was highest among adults aged 40-59 (19.0%) and lowest among children aged below 12 years (2.6%).ConclusionsOur results demonstrate a moderately high incidence of Post-COVID Syndrome two years after infection with COVID-19. There is an urgent need to find efficient and effective solutions to help patients with mental disorders, dyspnea, fatigue and loss of smell. Guidelines and treatment algorithms, including referral criteria, occupational and physical therapy, require promptly and coherent implementation. Further research is required both to find new therapeutic options and to assess the implications of Post-COVID Syndrome for health services.Strengths and Limitations of the StudyThe data cover all statutory health insurance companies in Bavaria and have high generalisability to the general population.By considering the proportion of COVID-19 patients consulting a physician, our results are better able to differentiate between everyday complaints and medically significant illness than data from a self-reported questionnaire.Follow-up of up to two years enables first assessment of the proportion requiring continuous care for a Post-COVID Syndrome.The routinely collected data are not audited and contain little information regarding the severity of the symptoms.

Cardiac output (CO) is a key determinant of oxygen delivery, but choosing the optimal method to obtain CO in pediatric patients remains challenging. The pressure recording analytical method (PRAM), implemented in the MostCareUp system (Vygon), is an invasive uncalibrated pulse wave analysis (PWA) method to measure CO. The objective of this study is to compare CO measured by PRAM (PRAM-CO; test method) with CO simultaneously measured by transesophageal Doppler echocardiography (TEE-CO; reference method) in pediatric patients.In this prospective observational method comparison study, PRAM-CO and TEE-CO were assessed in pediatric elective cardiac surgery patients at 2 time points: after anesthesia induction and after surgery. The study was performed in a German university medical center from March 2019 to March 2020. We included pediatric patients scheduled for elective cardiac surgery with arterial catheter and TEE monitoring. PRAM-CO and TEE-CO were compared using Bland-Altman analysis accounting for repeated measurements per subject, and the percentage error (PE).We included 52 PRAM-CO and TEE-CO measurement pairs of 30 patients in the final analysis. Mean ± SD TEE-CO was 2.15 ± 1.31 L/min (range 0.55-6.07 L/min), and mean PRAM-CO was 2.21 ± 1.38 L/min (range 0.55-5.90 L/min). The mean of the differences between TEE-CO and PRAM-CO was -0.06 ±0.38 L/min with 95% limits of agreement (LOA) of 0.69 (95% confidence interval [CI], 0.53-0.82 L/min) to -0.80 L/min (95% CI, -1.00 to -0.57 L/min). The resulting PE was 34% (95% CI, 27%-41%).With a PE of45%, PRAM-CO shows clinically acceptable agreement with TEE-CO in hemodynamically stable pediatric patients before and after cardiac surgery.

Aims Dynamic retinal vessel analysis (DVA) provides a noninvasive way to asses microvascular function in patients and potentially to improve predictions of individual cardiovascular (CV) risk. The aim of our study was to use untargeted machine learning on DVA in order to improve CV mortality prediction and to identify corresponding response alterations. Methods and results We adopted a workflow consisting of noise reduction and extraction of independent components within DVA signals. Predictor performance was assessed in survival random forest models. Applying our technique to the prediction of all-cause mortality in a cohort of 214 hemodialysis patients resulted in the selection of a component which was highly correlated to maximal venous dilation following flicker stimulation (vMax), a previously identified predictor, confirming the validity of our approach. When fitting for CV mortality as the outcome of interest, a combination of three components derived from the arterial signal resulted in a marked improvement in predictive performance. Clustering analysis suggested that these independent components identified groups of patients with substantially higher CV mortality. Conclusions Our results provide a machine learning workflow to improve the predictive performance of DVA and identify groups of hemodialysis patients at high risk of CV mortality. Our approach may also prove to be promising for DVA signal analysis in other CV disease states. Translational perspective DVA is a noninvasive technique which can help to assess microvascular dysfunction, one of the driving factors of CV disease. This study demonstrates a machine learning method which improves DVA interpretation for the estimation of CV risk in hemodialysis patients. Similar techniques can help doctors to identify high risk patients for timely therapeutic interventions and to monitor the effects of these interventions.

Background: Subgroup analyses are frequently used to assess heterogeneity of treatment effects in randomised clinical trials. Inconsistent, improper and incomplete implementation, reporting and interpretation have been identified as ongoing challenges. Further, subgroup analyses were frequently criticised because of unreliable or potentially misleading results. More recently, recommendations and guidelines have been provided to improve the reporting of data in this regard. Methods: This systematic review was based on a literature search within the digital archives of three selected medical journals, The New England Journal of Medicine, The Lancet and Circulation. We reviewed articles of randomised clinical trials in the domain of cardiovascular disease which were published in 2015 and 2016. We screened and evaluated the selected articles for the mode of implementation and reporting of subgroup analyses. Results: We were able to identify a total of 130 eligible publications of randomised clinical trials. In 89/130 (68%) articles, results of at least one subgroup analysis were presented. This was dependent on the considered journal (p Conclusion: Compared to previous reviews in this context, we observed improvements in the reporting of subgroup analyses of cardiovascular randomised clinical trials. Nonetheless, critical shortcomings, such as inconsistent reporting of the implementation and insufficient pre-specification, persist.

Background After the ‘first wave’ in spring 2020, opinions regarding the threat and measures against COVID-19 seemed to vary among German general practitioners (GPs). Objectives To systematically investigate opinions and to identify subgroups of GPs sharing similar views. Methods A questionnaire was sent to all 210 practices accredited for undergraduate teaching of family medicine at the Medical Faculty of the Technical University of Munich. Questions addressed personal opinions regarding risks, dilemmas, restrictions and their relaxation associated with COVID-19, and personal fears, symptoms of depression and anxiety. Patterns of strong opinions (‘archetypes’) were identified using archetypal analysis, a statistical method seeking extremal points in the multidimensional data. Results One hundred and sixty-one GPs sent back a questionnaire (response rate 77%); 143 (68%) with complete data for all 38 relevant variables could be included in the analysis. We identified four archetypes with subgroups of GPs tending in the direction of these archetypes: a small group of ‘Sceptics’ (n = 12/8%) considering threats of COVID-19 as overrated and measures taken as exaggerated; ‘Hardliners’ (n = 34/24%) considering threats high and supporting strong measures; ‘Balancers’ (n = 77/54%) who also rated the threats high but were more critical about potentially impairing the quality of life of elderly people and children; and ‘Anxious’ GPs (n = 20/14%) tending to report more fear, depressive and anxiety symptoms. Conclusion Among the participants in this survey, opinions regarding the threat and the measures taken against COVID-19 during the ‘first wave’ in Germany in spring 2020 varied greatly.