ABSTRACT
Background: Access to blood products is crucial for patient safety during the perioperative course. However, reduced donations and seasonally occurring blood shortages pose a significant challenge to the healthcare system, with surgeries being postponed. The German Blood Transfusion act requires that RBC packages become assigned to an individual patient, resulting in a significant reduction in the available blood products, further aggravating shortages. We aimed to develop a scoring system predicting transfusion probability in patients undergoing spine surgery to reduce assignment and, thus, increase the availability of blood products. Methods: The medical records of 252 patients who underwent spine surgery were evaluated and 18 potential predictors for RBC transfusion were tested to construct a logistic-regression-based predictive scoring system for blood transfusion in patients undergoing spine surgery. Results: The variables found to be the most important included the type of surgery, vertebral body replacement, number of stages, and pre-operative Hb concentration, indicating that surgical specification and the extent of the surgical procedure were more influential than the pre-existing patient condition and medication. Conclusions: Our model showed a good discrimination ability with an average AUC [min, max] of 0.87 [0.6, 0.97] and internal validation with a similar AUC of 0.84 [0.66, 0.97]. In summary, we developed a scoring system to forecast patients' perioperative transfusion needs when undergoing spine surgery using pre-operative predictors, potentially reducing the need for RBC allocation and, thus, resulting in an increased availability of this valuable resource.
ABSTRACT
Background: Acute coronary syndrome (ACS) is a major cause of morbidity and mortality in the western world. Classic angina pectoris (AP) is a common reason to request prehospital emergency medical services (EMS). Nevertheless, data on diagnostic accuracy and common misdiagnoses are scarce. Therefore, the aim of this study is to evaluate the amount and variety of misdiagnoses and assess discriminating features. Methods: For this retrospective cohort study, all patients requiring EMS for suspected ACS in the city of Bonn (Germany) during 2018 were investigated. Prehospital and hospital medical records were reviewed regarding medical history, presenting signs and symptoms, as well as final diagnosis. Results: Out of 740 analyzed patients with prehospital suspected ACS, 283 (38.2%) were ultimately diagnosed with ACS (ACS group). Common diagnoses in the cohort with non-confirmed ACS (nACS group) consisted of unspecific pain syndromes, arrhythmias, hypertensive crises, and heart failure. ST segment elevation (adjusted odds-ratios [adj. OR] 2.70), male sex (adj. OR 1.71), T wave changes (adj. OR 1.27), angina pectoris (adj. OR 1.15) as well as syncope (adj. OR 0.63) were identified among others as informative predictors in a multivariable analysis using the lasso technique for data-driven variable selection. Conclusions: Misdiagnosed ACS is as common as 61.8% in this cohort and analyses point to a complex of conditions and symptoms (i.e., male sex, electrocardiographic (ECG) changes, AP) for correct ACS diagnosis while neurological symptoms were observed significantly more often in the nACS group (e.g., Glasgow Coma Scale (GCS) < 15, p = 0.03). To ensure adequate and timely therapy for a potentially critical disease as ACS a profound prehospital examination and patient history is indispensable.