Christopher Martin Sauer

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• M.D., M.P.H., Ph.D.
• Clinician Scientist at University Hospital Essen

Objective: As data science and artificial intelligence continue to rapidly gain traction, the publication of freely available ICU datasets has become invaluable to propel data-driven clinical research. In this guide for clinicians and researchers, we aim to: 1) systematically search and identify all publicly available adult clinical ICU datasets,...

Analysis of electronic health records (EHRs) is an increasingly common approach for studying real-world patient data. Use of routinely collected data offers several advantages compared with other study designs, including reduced administrative costs, the ability to update analysis as practice patterns evolve, and larger sample sizes. Methodological...

e13590 Background: Advances in diagnosis and treatment have led to large reductions in mortality rates for patients with cancer, resulting in a steady increase in patients admitted to intensive care units (ICUs). However, there is conflicting evidence supporting the benefit of common life-sustaining therapies for critically ill patients, within thi...

Introduction Most people who die from prostate cancer are older than 75 years. However, prostate cancer diagnosed at younger ages is often more aggressive. While epidemiologic studies have examined the association between age and survival in patients with prostate cancer overall, the clinical drivers of this relationship in patients with advanced d...

Introduction The standard of care for metastatic hormone-sensitive prostate cancer (mHSPC) has evolved with the expanded approval of androgen receptor pathway inhibitors (ARPIs) alongside androgen deprivation therapy (ADT). ADT alone has been shown to affect cognitive function. However, the cognitive impact of distinct treatment combinations remain...

Background The deployment of Artificial Intelligence (AI) in healthcare has the potential to transform patient care through improved diagnostics, personalized treatment plans, and more efficient resource management. However, the effectiveness and fairness of AI are critically dependent on the data it learns from. Biased datasets can lead to AI outp...

Background Artificial intelligence (AI) and machine learning (ML) algorithms have shown great promise in clinical medicine. Despite the increasing number of published algorithms, most remain unvalidated in real-world clinical settings. This study aims to simulate the practical implementation challenges of a recently developed ML algorithm, AI-PAL,...

Background Inter-organizational partnerships and collaborations, used here interchangeably, have growing prominence across the health sector. Successful partnerships have received extensive study. However, especially for partnerships including nonprofit partners, limited attention has been given to negative factors that contribute to struggling par...

Background Artificial intelligence (AI) and machine learning (ML) algorithms have shown great promise in clinical medicine, offering potential improvements in diagnostic accuracy and patient outcomes. Despite the increasing number of published algorithms, most remain unvalidated in real-world clinical settings. This study aims to simulate the pract...

Reports of Large Language Models (LLMs) passing board examinations have spurred medical enthusiasm for their clinical integration. Through a narrative review, we reflect upon the skill shifts necessary for clinicians to succeed in an LLM-enabled world, achieving benefits while minimizing risks. We suggest how medical education must evolve to prepar...

Background FHIR (Fast Healthcare Interoperability Resources) has been proposed to enable health data interoperability. So far, its applicability has been demonstrated for selected research projects with limited data. Objective This study aimed to design and implement a conceptual medical intelligence framework to leverage real-world care data for...

e13552 Background: Sepsis is the leading cause of hospital readmission and death in the developed world. Cancer patients are at high risk due to their underlying disease and therapies. Meanwhile, antimicrobial resistance increases steadily, warranting a more careful administration of antibiotics. Predicting fever persistence 48 hours after initiati...

Background Hospitals use triage systems to prioritize the needs of patients within available resources. Misclassification of a patient can lead to either adverse outcomes in a patient who did not receive appropriate care in the case of undertriage or a waste of hospital resources in the case of overtriage. Recent advances in machine learning algori...

BACKGROUND Hospitals use triage systems to prioritize the needs of patients within available resources. Misclassification of a patient can lead to either adverse outcomes in a patient who did not receive appropriate care in the case of undertriage or a waste of hospital resources in the case of overtriage. Recent advances in machine learning algori...

BACKGROUND FHIR (Fast Healthcare Interoperability Resources) has been proposed to enable health data interoperability. So far, its applicability has been demonstrated for selected research projects with limited data. OBJECTIVE This study aimed to design and implement a conceptual medical intelligence framework to leverage real-world care data for...

Background: Variability in the provision of intensive care unit (ICU)-interventions may lead to disparities between socially defined racial-ethnic groups. Research Question: We used causal inference to examine the use of invasive mechanical ventilation (IMV), renal replacement therapy (RRT), and vasopressor agents (VP) to identify disparities in ou...

Background Atrial Fibrillation (AF) is the most common arrhythmia in the intensive care unit (ICU) and is associated with increased morbidity and mortality. Identification of patients at risk for AF is not routinely performed as AF prediction models are almost solely developed for the general population or for particular ICU populations. However,...

Introduction: Acute kidney injury (AKI) is a common issue in the intensive care unit affecting approx. 57% of all patients [1]. Furthermore, it is a common reason for initiating continuous renal replacement therapy (CRRT). Early identification of patients requiring CRRT could help physicians to focus on preventing progression to CRRT, improve plann...

This thesis discussed how advanced analytics and real-world evidence can be utilized to improve patient outcomes. In chapter 2 we summarize frequently observed pitfalls clinicians and data scientists should seek to avoid. Furthermore, we describe potential solutions how these issues can be avoided and overcome. In chapter 3 we compared the four pub...

Background: Whether or not a survival difference exists between radical and partial nephrectomy for stage T1 renal cell carcinoma (RCC) is controversial. We therefore aimed to evaluate cancer-specific, other cause, and overall survival among patients undergoing radical or partial nephrectomy for stage pT1 RCC. Materials and methods: We identified 3...

While serum lactate level is a predictor of poor clinical outcomes among critically ill patients with sepsis, many have normal serum lactate. A better understanding of this discordance may help differentiate sepsis phenotypes and offer clues to sepsis pathophysiology. Three intensive care unit datasets were utilized. Adult sepsis patients in the hi...

Patients admitted to the intensive care unit frequently have anemia and impaired renal function, but often lack historical blood results to contextualize the acuteness of these findings. Using data available within two hours of ICU admission, we developed machine learning models that accurately (AUC 0.86–0.89) classify an individual patient’s basel...

Background Tuberculosis is a major cause of morbidity and mortality in the developing world. Drug resistance, which is predicted to rise in many countries worldwide, threatens tuberculosis treatment and control. Objective To identify features associated with treatment failure and to predict which patients are at highest risk of treatment failure....

Comparison of patient characteristics in the training and testing subset. IQR: interquartile range. (DOCX)

Predicted (A) and smoothed (B) AUC for the different models in the imputed dataset. (TIF)

Comparison of prediction performance of the different models in the imputed dataset. Predictive performance is higher than in the complete cases analysis (Table 3). AUC: Area under the receiver-operator curve, PPV: Positive predictive value, NPV: Negative predictive value, LASSO: Least absolute shrinkage and selection operator, SVM: Support vector...

Merkel cell carcinoma (MCC) is a highly aggressive non-melanoma skin cancer of the elderly which is associated with the Merkel cell polyomavirus (MCPyV). MCC reveals a trilinear differentiation characterized by neuroendocrine, epithelial and pre/pro B-cell lymphocytic gene expression disguising the cellular origin of MCC. Here we investigated the e...

Blast of MKL-2 REST sequence. NCBI blast has revealed the identity of the truncated REST sequence which was detected in SCLC (A). The exons of the non-truncated and truncated splice variant are shown (B).

Summary of the IHC analysis for REST, ASCL1 and NeuroD1 in MCC cell lines and the B-ALL cell line REH, pos.= positive, neg.= negative, - = no expression, + = weak expression, ++ = moderate expression, +++ = strong expression

Expression of chromogranin A and synaptophysin in WaGa cells as assessed by immunofluorescence. WaGa nuclei are shown with DAPI (blue). The specific cytoplasmic expression of chromogranin A and synaptophysin is reflected by red fluorescence. The merged picture reveals in all cells a strong expression of chromogranin A or synaptophysin. The micropho...

Used primer for all PCR applications

MCPyV expression level in all used cell lines. The expression of MCPyV sT and LT were analyzed by means of a qRT-PCR. The cq values were normalized to MKL-1 and the sd of n=2 is shown. The MCPyV-positive MCC cell lines reveal a different expression pattern of MCPyV T antigens whereas the distribution of LT and sT is comparable (A). In addition, the...

Purpose Cancer patients are at increased risk of treatment- or disease-related admission to the intensive care unit [1]. Over the past decades, both critical care and cancer care have improved substantially. Due to increased cancer-specific survival [2], we hypothesized that the number of cancer patients admitted to the intensive care unit (ICU) an...

Over the past decades, both critical care and cancer care have improved substantially. Due to increased cancer-specific survival, we hypothesized that both the number of cancer patients admitted to the ICU and overall survival have increased since the millennium change. MIMIC-III, a freely accessible critical care database of Beth Israel Deaconess...

Over the past decades, both critical care and cancer care have improved substantially. Due to increased cancer-specific survival, we hypothesized that both the number of cancer patients admitted to the ICU and overall survival have increased since the millennium change. MIMIC-III, a freely accessible critical care database of Beth Israel Deaconess...

Introduction Merkel cell carcinoma (MCC) is a highly aggressive skin cancer of the elderly and immunosuppressed patients. More than 80% of MCCs are associated with the recently identified Merkel cell polyomavirus (MCPyV). MCCs reveal a trilinear differentiation characterized by neuroendocrine (chromogranin A and synapthophysin), epithelial (e.g. CK...

Merkel cell carcinoma (MCC) is a highly malignant skin cancer characterized by early metastases and poor survival. Although MCC is a rare malignancy, its incidence is rapidly increasing in the U.S. and Europe. The discovery of the Merkel cell polyomavirus (MCPyV) has enormously impacted our understanding of its etiopathogenesis and biology. MCCs ar...

Merkel cell carcinoma (MCC) is a relatively rare but highly malignant non-melanoma skin cancer of the elderly and immunosuppressed patients. The discovery of the Merkel cell polyomavirus (MCPyV) in 2008 significantly impacted the understanding of the etiopathogenesis of MCC. MCPyV is clonally integrated into the MCC genome and approximately 80% of...

Large B-cell lymphomas (LBCL) exhibit multiple genetic alterations, often in specific combinations. However, little is known about the biologic consequences of these concurrent genetic features. We recently characterized the comprehensive molecular signatures of two LBCL subtypes that exclusively involve extranodal disease sites, primary central ne...