Objectives: To investigate the prevalence and distribution of comorbidity and its association with perioperative complications in patients undergoing radical prostatectomy (RPE). Methods: In 431 unselected RPE patients, the American Society of Anesthesiologists Physical Status classification (ASA-PS), the New York Heart Association classification of cardiac insufficiency (NYHA), the classification of angina pectoris of the Canadian Cardiovascular Society (CCS), height, weight, the body mass index (BMI), and the number of concomitant diseases (NCD) were assessed and related to perioperative cardiovascular complications. Results: In RPE patients less than 70 years old, comorbidity rose nearly continuously with increasing age. However, after reaching an age of 70 years, the proportion of NYHA-0 patients increased (60–64 years, 86%; 65–69 years, 85%; ≥70 years, 87%). Furthermore, the severe comorbidities decreased in patients selected for RPE aged 70 or more years. There was a nonsignificant trend towards higher comorbidity in patients with perioperative cardiovascular complications. Conclusions: These data suggest that documentation of the distribution of ASA-PS, CCS, NYHA and of concomitant diseases might be helpful to characterize the general health status and the degree of selection of prostate cancer treatment populations especially in series with a high portion of patients aged 70 or more years. Concerning perioperative complications, the individual predictive value of comorbidity seems to be poor in the radical prostatectomy setting. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

Objectives: To investigate the prevalence and distribution of comorbidity and its association with perioperative complications in patients undergoing radical prostatectomy (RPE). Methods: In 431 unselected RPE patients, the American Society of Anesthesiologists Physical Status classification (ASA-PS), the New York Heart Association classification of cardiac insufficiency (NYHA), the classification of angina pectoris of the Canadian Cardiovascular Society (CCS), height, weight, the body mass index (BMI), and the number of concomitant diseases (NCD) were assessed and related to perioperative cardiovascular complications. Results: In RPE patients less than 70 years old, comorbidity rose nearly continuously with increasing age. However, after reaching an age of 70 years, the proportion of NYHA-0 patients increased (60–64 years, 86%; 65–69 years, 85%; ≥70 years, 87%). Furthermore, the severe comorbidities decreased in patients selected for RPE aged 70 or more years. There was a nonsignificant trend towards higher comorbidity in patients with perioperative cardiovascular complications. Conclusions: These data suggest that documentation of the distribution of ASA-PS, CCS, NYHA and of concomitant diseases might be helpful to characterize the general health status and the degree of selection of prostate cancer treatment populations especially in series with a high portion of patients aged 70 or more years. Concerning perioperative complications, the individual predictive value of comorbidity seems to be poor in the radical prostatectomy setting. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

Selecting patients for clinical trials is very labor-intensive. Our goal is to develop an automated system that can support doctors in this task. This paper describes a major step towards such a system: the automatic translation of clinical trial eligibility criteria from natural language into formal, logic-based queries. First, we develop a semantic annotation process that can capture many types of clinical trial criteria. Then, we map the annotated criteria to the formal query language. We have built a prototype system based on state-of-the-art NLP tools such as Word2Vec, Stanford NLP tools, and the MetaMap Tagger, and have evaluated the quality of the produced queries on a number of criteria from clinicaltrials.gov. Finally, we discuss some criteria that were hard to translate, and give suggestions for how to formulate eligibility criteria to make them easier to translate automatically.