Validation of a Simplified Diagnostic Algorithm for Deep Vein Thrombosis
Bibliographic record
Abstract
Background: Evidence-based deep vein thrombosis (DVT) diagnostic algorithms used in the emergency department have been extensively validated, yet they are rarely followed by emergency physicians. The most well-known, the Wells score, is complex containing up to 13 clinical items, making it difficult to consistently apply in the emergency department. All diagnostic algorithms for DVT combine estimations of clinical pretest probability with D-dimer blood testing, and/or ultrasonography. In an effort to simplify DVT diagnostic algorithms, we developed a simplified rule for DVT testing, named the 2DAY algorithm. Objectives: The aims of this study were to evaluate the safety and efficiency of the 2DAY algorithm for DVT diagnosis in the emergency department. Methods: We used patient data from the Canadian multicentre diagnostic management study: the 4D study (NCT02038530), to validate the 2DAY algorithm. Patients were followed to determine if they were diagnosed with venous thromboembolism (proximal DVT or pulmonary embolism) within 90-days following their DVT assessment. The 2DAY algorithm consists of physician's estimate of whether DVT is the patient's most likely diagnosis and the blood D-dimer result to determine if an ultrasound is required. If DVT is the most likely diagnosis, then DVT is excluded with standard threshold of <500 ng/mL. If DVT is not the most likely diagnosis, then DVT is excluded using the age-adjusted D-dimer threshold. If DVT is not excluded based on the D-dimer result, the patient must undergo proximal ultrasound imaging. Repeat ultrasonography is indicated when the patient has a D-dimer is ≥ 1,500 ng/mL and a negative initial proximal ultrasound. The primary analysis was the proportion of patients diagnosed with venous thromboembolism within 90-days who had DVT ruled out by the 2DAY algorithm with the corresponding 95% confidence interval (CI) estimated using the Wilson Score method. Similar analysis was used to estimate the efficiency of the 2DAY algorithm defined as the proportion of patients who did not require an ultrasound. Results: In total, 1497 patients were eligible. Using the 2DAY algorithm, 163 (10.9 %) out of the 1497 patients were diagnosed with DVT. The mean age was 60.3, 41.8% were male, and 5.0% had active cancer. DVT was the most likely diagnosis for 68.1% of patients. From the 1334 patients who had DVT ruled out by the 2DAY algorithm, 10 (0.75%; 95% CI, 0.41-1.37) patients had VTE diagnosed during the 90-day follow-up period. The 2DAY algorithm had an efficiency of 38.6% (578/1497; 95% CI, 36.2-41.1). Conclusions: The 2DAY algorithm, was found to be safe and efficient in ruling out DVT. Before the 2DAY algorithm can be implemented in daily clinical practice, a prospective validation study is required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".