Nichtparametrische Verfahren für die Analyse von komplexen Datensätzen

An often encountered problem in pre-clinical, early clinical or translational studies is the analysis of complex data structures. In such studies, sample sizes are typically quite small; outcomes might not be normally distributed; are highly skewed or are not even on a metric scale. In these situations, nonparametric inference methods should be preferred over parametric procedures. Furthermore, an issue that often arises in practical applications is the occurrence of missing data. We develop nonparametric methods for the analysis of repeated measures designs that are based on all-available information instead of using completely observed subjects only. Neither any specific data distribution nor equal covariance matrices across the (treatment) groups are required. The methods can be applied to metric, highly skewed, ordinal, ordered categorical and even binary data in a unified way. No adjustment for ties in the data is necessary as opposed to classical nonparametric methods. We further generalize the framework to allow for possibly dependent replicates or clustered data. One typical example where clustered data frequently arise are animal experiments, where several animals share the same cage. The assumption of independence between animals from the same cage is likely to be violated since it can be assumed that these animals are more similar than animals from other cages, for example in terms of their behaviour. In this dissertation, statistical hypotheses are formulated in terms of the nonparametric relative effect, which is easy to understand and to interpret. We present quadratic-type as well as multiple contrast test-type procedures including simultaneous confidence intervals for the analysis of such designs. Extensive simulation studies evaluate the precision of the proposed estimators as well as type-I error rates and the power in various settings. It turns out that the methods are applicable in many different situations. Real world data sets exemplify the application of the newly developed procedures.Ein häufig auftretendes Problem in präklinischen, frühen klinischen oder translationalen Studien ist die Analyse komplexer Datenstrukturen. In solchen Studien ist der Stichprobenumfang in der Regel recht klein; die Parameter sind möglicherweise nicht normalverteilt, schief verteilt oder liegen nicht auf einer metrischen Skala. In solchen Situationen sollten nichtparametrische Inferenzmethoden gegenüber parametrischen Modellen bevorzugt werden. Ein weiteres häufiges Problem sind fehlende Werte. Wir entwickeln nichtparametrische Methoden für die Analyse von Modellen mit wiederholten Messungen, die auf allen verfügbaren Informationen beruhen, anstatt nur die Information von vollständig beobachteten Subjekten zu verwenden. Es sind weder eine bestimmte Datenverteilung noch gleiche Kovarianzmatrizen der Messwiederholungen der (Behandlungs-)Gruppen erforderlich. Die Methoden können auf metrische, sehr schiefe, ordinale, geordnete kategoriale und sogar binäre Daten in einheitlicher Weise angewendet werden. Im Gegensatz zu den klassischen nichtparametrischen Methoden ist keine Anpassung für Bindungen in den Daten erforderlich. Wir verallgemeinern das Modell sowie die Prozeduren, um mögliche abhängige Wiederholungen oder geclusterte Daten zu berücksichtigen. Ein typisches Beispiel für geclusterte Daten sind Daten aus Tierexperimenten, in denen meist mehrere Tiere in einem Käfig gehalten werden. Hierbei sollte von der Annahme der Unabhängigkeit der Tiere in einem Käfig abgesehen werden, da davon ausgegangen werden kann, dass sich Tiere aus demselben Käfig ähnlicher sind als Tiere aus anderen Käfigen. In dieser Dissertation werden Hypothesen in nichtparametrischen relativen Effekten formuliert, welche leicht verständlich und einfach zu interpretieren sind. Für die Analyse solcher Modelle werden sowohl quadratische als auch multiple Kontrasttestverfahren einschließlich simultaner Konfidenzintervalle vorgestellt. Umfangreiche Simulationsstudien evaluieren die Präzision der vorgeschlagenen Schätzer sowie die Typ-I-Fehlerraten und die Power in verschiedenen Settings. Es zeigt sich, dass die Methoden in vielen verschiedenen Situationen anwendbar sind. Reale Datensätze veranschaulichen die Anwendung der neu entwickelten Verfahren

A Recurrent Neural Network Model for Predicting Activated Partial Thromboplastin Time After Treatment With Heparin: Retrospective Study

Background: Anticoagulation therapy with heparin is a frequent treatment in intensive care units and is monitored by activated partial thromboplastin clotting time (aPTT). It has been demonstrated that reaching an established anticoagulation target within 24 hours is associated with favorable outcomes. However, patients respond to heparin differently and reaching the anticoagulation target can be challenging. Machine learning algorithms may potentially support clinicians with improved dosing recommendations. Objective: This study evaluates a range of machine learning algorithms on their capability of predicting the patients' response to heparin treatment. In this analysis, we apply, for the first time, a model that considers time series. Methods: We extracted patient demographics, laboratory values, dialysis and extracorporeal membrane oxygenation treatments, and scores from the hospital information system. We predicted the numerical values of aPTT laboratory values 24 hours after continuous heparin infusion and evaluated 7 different machine learning models. The best-performing model was compared to recently published models on a classification task. We considered all data before and within the first 12 hours of continuous heparin infusion as features and predicted the aPTT value after 24 hours. Results: The distribution of aPTT in our cohort of 5926 hospital admissions was highly skewed. Most patients showed aPTT values below 75 s, while some outliers showed much higher aPTT values. A recurrent neural network that consumes a time series of features showed the highest performance on the test set. Conclusions: A recurrent neural network that uses time series of features instead of only static and aggregated features showed the highest performance in predicting aPTT after heparin treatment

Cerebrovascular Events in Suspected Sepsis: Retrospective Prevalence Study in Critically Ill Patients Undergoing Full-Body Computed Tomography

Purpose: This study aimed at retrospectively evaluating full-body computed tomography (CT) examinations for the prevalence of cerebrovascular events in patients with suspected sepsis treated in the intensive care unit (ICU). Methods: All full-body CT examinations, i.e., both cranial CT (cCT) and body CT including chest, abdomen and pelvis, for focus search in septic patients over a 12-months period were identified from three ICUs, using full-text search. From this retrospective cohort, we fully analyzed 278 cCT examinations for the occurrence of acute cerebral findings. All acute cerebrovascular events were independently reviewed by two blinded readers. Clinical and laboratory findings were extracted. The data were statistically analyzed using contingency tests. Results: In our population of patients with suspected sepsis, 10.8% (n = 30/278) were identified to have major cerebral events, including 7.2% (n = 20/278) major cerebrovascular events and 4.3% (n = 12/278) generalized parenchymal damage. 13.4% (n = 22/163) of patients with a severe coma as compared with non-severe coma, 4.4% (n = 3/68), showed a major cerebral event (p = 0.04). Patients referred from the cardiology/nephrology ICU ward showed major cerebral events in 16.3% (n = 22/135), as compared with 4.9% (n = 3/61) in patients from pulmonary ICU and 6.1% (n = 5/82) major cerebral events with surgical referral (p = 0.02). Conclusion: Our study provides further evidence that septic patients may suffer from cerebral events with relevance to their prognosis. Severe coma and the referring ward were associated with acute cerebral conditions. Full-body CT has the advantage of both detecting of septic foci and possibly identifying ischemic or hemorrhagic stroke in this vulnerable patient population

Imaging intensive care patients: multidisciplinary conferences as a quality improvement initiative to reduce medical error

Background: Strategies to identify imaging-related error and minimise its consequences are important in the management of critically ill patients. A new quality management (QM) initiative for radiological examinations has been implemented in an intensive care unit (ICU) setting. In regular multidisciplinary conferences (MDCs), radiologists and ICU physicians re-evaluate recent examinations. Structured bilateral feedback is provided to identify errors early. This study aims at investigating its impact on the occurrence of QM events (imaging-related errors). Standardised protocols of all MDCs from 1st of June 2018 through 31st of December 2019 were analysed with regard to categories of QM events (i.e. indication, procedure, report) and resulting consequences. Results: We analysed 241 MDCs with a total of 973 examinations. 14.0% (n = 136/973) of examinations were affected by QM events. The majority of events were report-related (76.3%, n = 106/139, e.g. misinterpreted finding), followed by procedure-related (18.0%, n = 25/139, e.g. technical issue) and indication-related events (5.8%, n = 8/139, e.g. faulty indication). The median time until identification of a QM event (time to MDC) was 2 days (interquartile range = 2). Comparing the first to the second half of the intervention period, the incidence of QM events decreased significantly from 22.9% (n = 109/476) to 6.0% (n = 30/497) (p < 0.0001). Significance of this effect was confirmed by linear regression (p < 0.0001). Conclusions: Establishing structured discussion and feedback between radiologists and intensive care physicians in the form of MDCs is associated with a statistically significant reduction in QM events. These results indicate that MDCs may be one suitable approach to timely identify imaging-related error

Tumor-Associated Microglia/Macrophages as a Predictor for Survival in Glioblastoma and Temozolomide-Induced Changes in CXCR2 Signaling with New Resistance Overcoming Strategy by Combination Therapy

Tumor recurrence is the main challenge in glioblastoma (GBM) treatment. Gold standard therapy temozolomide (TMZ) is known to induce upregulation of IL8/CXCL2/CXCR2 signaling that promotes tumor progression and angiogenesis. Our aim was to verify the alterations on this signaling pathway in human GBM recurrence and to investigate the impact of TMZ in particular. Furthermore, a combi-therapy of TMZ and CXCR2 antagonization was established to assess the efficacy and tolerability. First, we analyzed 76 matched primary and recurrent GBM samples with regard to various histological aspects with a focus on the role of TMZ treatment and the assessment of predictors of overall survival (OS). Second, the combi-therapy with TMZ and CXCR2-antagonization was evaluated in a syngeneic mouse tumor model with in-depth immunohistological investigations and subsequent gene expression analyses. We observed a significantly decreased infiltration of tumor-associated microglia/macrophages (TAM) in recurrent tumors, while a high TAM infiltration in primary tumors was associated with a reduced OS. Additionally, more patients expressed IL8 in recurrent tumors and TMZ therapy maintained CXCL2 expression. In mice, enhanced anti-tumoral effects were observed after combi-therapy. In conclusion, high TAM infiltration predicts a survival disadvantage, supporting findings of the tumor-promoting phenotype of TAMs. Furthermore, the combination therapy seemed to be promising to overcome CXCR2-mediated resistance

What statistics instructors need to know about concept acquisition to make statistics stick

The limits of my language are the limits of my mind. All I know is what I have words for (Wittgenstein). When learning something completely new, we connect the unknown term to an already existing part of our knowledge. We can only build new ideas and insights upon an existing conceptual foundation. In the field of statistics, we educators frequently find ourselves met with great confusion when teaching novices. These students, entirely unfamiliar with even basic statistics, must connect the introduced statistical terms within their personal existing networks of largely non-statistical knowledge. Lecturers, on the other hand, who are well versed in statistics, have deeply internalized the content to be taught and its relevant context. The juxtaposition of the two roles may produce amusement in a lecturer upon gaining insight into the word associations made by the statistical novices. For example, a ‘logistic regression’ does not involve the ‘shipping of goods in economically difficult times,’ though this might seem entirely reasonable and intuitive to the statistics learner. Other times, these different perspectives can lead to headaches and frustration for both learners and their lecturers. In this article, we illustrate how simple statistical terms are initially connected to a student’s pre-exiting knowledge and how these associations change after completing an introductory course in applied statistics. Furthermore, we emphasize the important difference between “term”, “approach”, and “context”. Understanding this fundamental distinction may help improve the communication between the lecturer and the learner. We offer a collection of practical tools for instructors to help promote students’ conceptual understanding in a supportive, mutually-beneficial learning environment

What statistics instructors need to know about concept acquisition to make statistics stickmake statistics stick

"The limits of my language are the limits of my mind. All I know is what I have words for" (Wittgenstein). When learning something completely new, we connect the unknown term to an already existing part of our knowledge. We can only build new ideas and insights upon an existing conceptual foundation. In the field of statistics, we educators frequently find ourselves met with great confusion when teaching novices. These students, entirely unfamiliar with even basic statistics, must connect the introduced statistical terms within their personal existing networks of largely non-statistical knowledge. Lecturers, on the other hand, who are well versed in statistics, have deeply internalized the content to be taught and its relevant context. The juxtaposition of the two roles may produce amusement in a lecturer upon gaining insight into the word associations made by the statistical novices. For example, a ‘logistic regression’ does not involve the ‘shipping of goods in economically difficult times,’ though this might seem entirely reasonable and intuitive to the statistics learner. Other times, these different perspectives can lead to headaches and frustration for both learners and their lecturers. In this article, we illustrate how simple statistical terms are initially connected to a student’s pre-exiting knowledge and how these associations change after completing an introductory course in applied statistics. Furthermore, we emphasize the important difference between “term”, “approach”, and “context”. Understanding this fundamental distinction may help improve the communication between the lecturer and the learner. We offer a collection of practical tools for instructors to help promote students’ conceptual understanding in a supportive, mutually-beneficial learning environment

Final-year medical students’ perspective: a survey on the use of computed tomography in sepsis

Abstract Objectives To determine the perspective of final-year medical students on the use of computed tomography (CT) in patients with sepsis. Methods A total of 207 questionnaires were distributed to final-year medical students at a large university medical center, and 113 returned questionnaires met the criteria for inclusion in the analysis. Questions referred to sepsis guidelines, CT indications, and the use of contrast agents. Control variables included a level of practical experience as a final-year student (trimester of student’s practical year) and previous radiological experience. Statistical hypothesis tests such as the Mann-Whitney U test and chi-square test were performed. Results The majority of participating students, 85% (n = 91/107), considered a Systemic Organ Failure Assessment (SOFA) score ≥ 2 as a diagnostic criterion for sepsis. The presence of ≥ 2 positive systemic inflammatory response syndrome (SIRS) criteria was considered relevant for diagnosing sepsis by 34% (n = 34/100). Ninety-nine percent (n = 64/65) of the participants who fully agreed with a SOFA score ≥ 2 being relevant for diagnosing sepsis would also use it as an indication for a CT scan. Seventy-six percent (n = 78/103) of the students rated a known severe allergic reaction to contrast agents as an absolute contraindication for its administration. Ninety-five percent (n = 78/82) considered radiation exposure as problematic in CT examinations, especially in repeat CTs. Conclusion Most final-year medical students were familiar with the sepsis criteria. Still, some referred to outdated diagnostic criteria. Participants saw the ability to plan further patient management based on CT as a major benefit. Most participants were aware of radiation as a risk of CT. Critical relevance statement More detailed knowledge of CT in septic patients should be implemented in the medical curriculum. Retraining of medical students could help increase student confidence potentially improving patient care. Key points 1. Whereas the majority of final-year medical students were familiar with sepsis criteria, some referred to outdated diagnostic criteria. 2. Participants saw the ability to plan further patient management based on CT as a major benefit. 3. Most participants were aware of radiation as a risk of CT. Graphical Abstrac

Management of the Contralateral Neck in Unilateral Node-Positive Oral Squamous Cell Carcinoma

Introduction: In lateralized oral squamous cell carcinoma (OSCC) with ipsilateral cervical lymph node metastasis (CLNM), the surgical management of the unsuspicious contralateral neck remains a matter of debate. The aim of this study was to analyze this cohort and to compare the outcomes of patients with and without contralateral elective neck dissection (END). Material and Methods: A retrospective analysis of patients with lateralized OSCC, ipsilateral CLNM (pN+) and contralateral cN0-stage was performed. Patients were divided into two groups according to the surgical management of the contralateral neck: I: END; and II: no END performed. Adjuvant radiotherapy was applied bilaterally in both groups according to individual risk. Results: A total of 65 patients (group I: 16 (24.6%); group II: 49 (75.4%)) with a median follow-up of 28 months were included. Initially, there was no case of contralateral CLNM after surgery. During follow-up, 6 (9.2%) patients presented with recurrent CLNM. In 5 of these cases (7.7%), the contralateral neck (group I: 3/16 (18.8%); group II: 2/49 (4.1%)) was affected. Increased ipsilateral lymph node ratio was associated with contralateral CLNM (p = 0.07). END of the contralateral side showed no significant benefit regarding OS (p = 0.59) and RFS (p = 0.19). Conclusions: Overall, the risk for occult contralateral CLNM in patients with lateralized OSCC ipsilateral CLNM is low. Our data suggest that END should not be performed routinely in this cohort. Risk-adapted radiotherapy of the contralateral neck alone seems to be sufficient from the oncological point of view

Management of the Contralateral Neck in Unilateral Node-Positive Oral Squamous Cell Carcinoma

Introduction: In lateralized oral squamous cell carcinoma (OSCC) with ipsilateral cervical lymph node metastasis (CLNM), the surgical management of the unsuspicious contralateral neck remains a matter of debate. The aim of this study was to analyze this cohort and to compare the outcomes of patients with and without contralateral elective neck dissection (END). Material and Methods: A retrospective analysis of patients with lateralized OSCC, ipsilateral CLNM (pN+) and contralateral cN0-stage was performed. Patients were divided into two groups according to the surgical management of the contralateral neck: I: END; and II: no END performed. Adjuvant radiotherapy was applied bilaterally in both groups according to individual risk. Results: A total of 65 patients (group I: 16 (24.6%); group II: 49 (75.4%)) with a median follow-up of 28 months were included. Initially, there was no case of contralateral CLNM after surgery. During follow-up, 6 (9.2%) patients presented with recurrent CLNM. In 5 of these cases (7.7%), the contralateral neck (group I: 3/16 (18.8%); group II: 2/49 (4.1%)) was affected. Increased ipsilateral lymph node ratio was associated with contralateral CLNM (p = 0.07). END of the contralateral side showed no significant benefit regarding OS (p = 0.59) and RFS (p = 0.19). Conclusions: Overall, the risk for occult contralateral CLNM in patients with lateralized OSCC ipsilateral CLNM is low. Our data suggest that END should not be performed routinely in this cohort. Risk-adapted radiotherapy of the contralateral neck alone seems to be sufficient from the oncological point of view