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The design and automated testing of an expert system for the differential diagnosis of acute stroke
R A Wain1, S Tuhrim, L D'Autrechy
1Montefiore Medical Center.
Insights
Computerized medical decision-making systems can help differentiate between ischemic stroke and intracerebral hemorrhage. The Mount Sinai system showed high accuracy and efficiency for guiding thrombolytic therapy.
Area of Science:
- Neurology
- Medical Informatics
- Biomedical Engineering
Background:
- Stroke is a leading cause of death and disability.
- Distinguishing ischemic stroke (IS) from intracerebral hemorrhage (ICH) is critical for treatment, particularly with thrombolytic agents.
- Computed tomographic scans are standard but not always available, necessitating clinical decision support.
Purpose of the Study:
- To develop and compare computerized medical decision-making (CMD) systems for differentiating IS from ICH.
- To evaluate the performance of CMD systems based on existing algorithms and a newly developed one using National Stroke Data Bank data.
- To optimize for positive predictive value (PPV) for ischemic stroke in the context of thrombolytic therapy.
Main Methods:
- Constructed CMD systems based on Guy's Hospital and Strong Memorial Hospital algorithms.
- Developed a novel CMD system using Mount Sinai Hospital Stroke Data Bank data.
- Evaluated system performance using 337 patient cases, focusing on PPV and sensitivity for IS.
Main Results:
- The Guy's Hospital and Mount Sinai CMD systems achieved high PPVs (95% and 94%) and sensitivities (77% and 78%).
- The Strong Memorial CMD system had a PPV of 93% and sensitivity of 56%.
- The Mount Sinai CMD system was more efficacious, requiring less clinical information for comparable results.
Conclusions:
- Computerized decision-making systems can effectively aid in distinguishing stroke types for treatment selection.
- The Mount Sinai CMD system demonstrates high accuracy and efficiency, offering a valuable tool for clinicians.
- These systems can improve patient outcomes by facilitating timely and appropriate use of thrombolytic agents.
Abstract:
Stroke is the third leading cause of death in the United States and a major source of morbidity. [1] Recent studies have shown a potential use for thrombolytic agents in the treatment of ischemic stroke (IS) but these agents are contraindicated in intracerebral hemorrhage (ICH). A computed tomographic scan is used to distinguish between these two stroke types prior to the use of thrombolytic agents, but may not be readily obtainable. Decision making aids such as algorithms developed at Guy's Hospital and Strong Memorial Hospital have been designed in an attempt to make this distinction on clinical grounds. We have constructed computerized medical decision-making (CMD) systems based upon these algorithms and compared their performance to a system we developed with the use of National Stroke Data Bank data. Relevant medical data for each of 337 patient cases in the Mount Sinai Hospital Stroke Data Bank were presented to each of the CMD systems. In consideration of the clinical task of using thrombolytic agents, we attempted to maximize the positive predictive value (PPV) for ischemic stroke. The CMD systems based upon the Guy's Hospital and Mount Sinai algorithms produced PPV's of 95% and 94% with sensitivities of 77% and 78% respectively compared to a PPV of 93% and sensitivity of 56% with the Strong Memorial CMD system. The Mount Sinai CMD system was judged more efficacious than the Guy's Hospital system in that it required less clinical information that could be more easily obtained to arrive at similar results.