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Background: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. Methods: A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. Results: 1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. Conclusions: Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451.
Einleitung: Angestoßen durch die Änderung der Approbationsordnung haben die berufspraktischen Kompetenzen in Deutschland eine höhere Priorität erhalten und werden in den medizinischen Fakultäten deswegen vermehrt vermittelt. Dadurch entstand die Notwendigkeit, den Prozess mehr und mehr zu standardisieren. Auf Initiative der deutschsprachigen Skills Labs wurde der GMA-Ausschuss für praktische Fertigkeiten gegründet, der einen kompetenzbasierten Lernzielkatalog entwickelte, dessen Entstehung und Struktur hier beschrieben wird. Ziel des Kataloges ist es, die praktischen Fertigkeiten im Medizinstudium zu definieren und damit den Fakultäten eine rationale Planungsgrundlage für die zur Vermittlung praktischer Fertigkeiten notwendigen Ressourcen zu geben.
Methodik: Aufbauend auf schon vorhandenen deutschsprachigen Lernzielkatalogen wurde mittels einem mehrfach iterativem Kondensationsprozesses, der der Erarbeitung von S1-Leitlinien entspricht, vorgegangen, um eine breite fachliche und politische Abstützung zu erhalten.
Ergebnisse: Es wurden 289 verschiedene praktische Lernziele identifiziert, die zwölf verschiedenen Organsystemen, drei Grenzbereichen zu anderen Kompetenzbereichen und einem Bereich mit organsystemübergreifenden Fertigkeiten zugeordnet. Sie wurden drei verschiedenen zeitlichen und drei verschiedenen Tiefendimensionen zugeordnet und mit dem Schweizer und dem Österreichischem Pendant abgeglichen.
Diskussion: Das vorliegende Konsensusstatement kann den deutschen Fakultäten eine Grundlage zur Planung der Vermittlung praktischer Fertigkeiten bieten und bildet einen wichtigen Schritt zu einem nationalen Standard medizinischer Lernziele.
Blick in die Zukunft: Das Konsensusstatement soll einen formativen Effekt auf die medizinischen Fakultäten haben, ihre praktischen Unterrichtsinhalte entsprechend zu vermitteln und die Ressourcen danach zu planen.
Introduction: Encouraged by the change in licensing regulations the practical professional skills in Germany received a higher priority and are taught in medical schools therefore increasingly. This created the need to standardize the process more and more. On the initiative of the German skills labs the German Medical Association Committee for practical skills was established and developed a competency-based catalogue of learning objectives, whose origin and structure is described here.
Goal of the catalogue is to define the practical skills in undergraduate medical education and to give the medical schools a rational planning basis for the necessary resources to teach them.
Methods: Building on already existing German catalogues of learning objectives a multi-iterative process of condensation was performed, which corresponds to the development of S1 guidelines, in order to get a broad professional and political support.
Results: 289 different practical learning goals were identified and assigned to twelve different organ systems with three overlapping areas to other fields of expertise and one area of across organ system skills. They were three depths and three different chronological dimensions assigned and the objectives were matched with the Swiss and the Austrian equivalent.
Discussion: This consensus statement may provide the German faculties with a basis for planning the teaching of practical skills and is an important step towards a national standard of medical learning objectives.
Looking ahead: The consensus statement may have a formative effect on the medical schools to teach practical skills and plan the resources accordingly.
Novel treatment options are needed for the successful therapy of patients with high-risk neuroblastoma. Here, we investigated the cyclin-dependent kinase (CDK) inhibitor SNS-032 in a panel of 109 neuroblastoma cell lines consisting of 19 parental cell lines and 90 sublines with acquired resistance to 14 different anticancer drugs. Seventy-three percent of the investigated neuroblastoma cell lines and all four investigated primary tumor samples displayed concentrations that reduce cell viability by 50% in the range of the therapeutic plasma levels reported for SNS-032 (<754 nM). Sixty-two percent of the cell lines and two of the primary samples displayed concentrations that reduce cell viability by 90% in this concentration range. SNS-032 also impaired the growth of the multidrug-resistant cisplatin-adapted UKF-NB-3 subline UKF-NB-3rCDDP1000 in mice. ABCB1 expression (but not ABCG2 expression) conferred resistance to SNS-032. The antineuroblastoma effects of SNS-032 did not depend on functional p53. The antineuroblastoma mechanism of SNS-032 included CDK7 and CDK9 inhibition-mediated suppression of RNA synthesis and subsequent depletion of antiapoptotic proteins with a fast turnover rate including X-linked inhibitor of apoptosis (XIAP), myeloid cell leukemia sequence 1 (Mcl-1), baculoviral IAP repeat containing 2 (BIRC2; cIAP-1), and survivin. In conclusion, CDK7 and CDK9 represent promising drug targets and SNS-032 represents a potential treatment option for neuroblastoma including therapy-refractory cases.