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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
An Automated Electronic Screening Tool (DETECT) for the Detection of Potentially Irreversible Loss of Brain Function
Anne Trabitzsch1, Konrad Pleul, Kristian Barlinn
1Surgery Center, University Hospital, Technische Universität Dresden; German Organ Procurement Organization, DSO region east, Dresden; Department of Neurology, Carl Gustav Carus University Hospital, Technische Universität Dresden; Department of Anesthesiology and Intensive Care Medicine, Pulmonary Engineering Group, University Hospital Carl Gustav Carus, Technische Universität Dresden; Institute of Neurosurgery, University Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden; Department of Pediatric Surgery, University Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden; Department of Quality and Medical Risk Managementt, University Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden; Medical Board, Universitätsklinikum Carl Gustav Carus an der Technischen Universität Dresden; Division of Nephrology, Department of Internal Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden.
Background:
A major reason for the low number of organ donors in Germany is a deficit in the recognition of patients who may have impending irreversible loss of brain function (ILBF) in hospitals capable of organ retrieval.
Methods:
We used anonymized data from the German Organ Procurement Organization (Deutsche Stiftung Organtransplantation, DSO) to compare two 12-month periods (a reference period and an evaluation period) before and after the implementation of an electronic screening tool (DETECT) at the University Hospital Dresden (UKD) with four other university hospitals without tool implementation (comparative cohort). DETECT is intended to aid in the recognition of potentially impending ILBF. The study endpoints encompassed patients with potentially unrecognized ILBF, patients with recognized ILBF, organ donations performed, and reports to the DSO. Changes in absolute risk were compared with Breslow-Day tests.
Results:
309 patients who died with primary or secondary brain lesions were identified in the UKD in the reference and evaluation periods (164 and 145 patients, respectively), and 1060 (529, 531) in the comparative cohort. In the UKD, the number of unrecognized cases of possibly impending ILBF was 14/164 (8.54%) in the reference period and 1/145 (0.69%) in the evaluation period, yielding an absolute reduction of 7.85% (95% confidence interval [--3.36; --12.33]); by contrast, in the comparative cohort, there was a 0.55% absolute increase between the two periods ([--2.21; 3.30]; p = 0.002 for the comparison between the two cohorts). Only minor differences in absolute risk change were seen with regard to the probability of recognized ILBF (7.09% [0.29; 13.88] vs. 2.42% [1.18; 6.01]; p = 0.234), organ donation (4.70% [--0.89; 10.28] vs. 0.55% [--2.17; 3.26]; p = 0.214), or reporting to the DSO (4.17% [--1.77; 10.11] vs. 2.22% [--1.44; 5.89; p = 0.447); these changes may have arisen by chance.
Conclusion:
These findings suggest that the use of DETECT can help to reduce the deficit in the recognition of patients with impending or manifest ILBF.
