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Record W3212965014 · doi:10.1182/blood-2021-151431

Pragmatic Evaluation of an Algorithm Using D-Dimer Adjusted to Clinical Probability in the Diagnosis of Pulmonary Embolism

2021· article· en· W3212965014 on OpenAlexaffabout
Kathleen Tina Winger, Alejandro Lazo‐Langner, Taylor Bechamp, Angela Yee‐Moon Wang, Matthew D. Leeder, Lauren F Chan, Christine D. MacDonald

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicinePulmonary embolismD-dimerEmergency departmentAlgorithmCohortPediatricsRetrospective cohort studyClinical PracticeDemographicsInternal medicinePhysical therapyMathematics

Abstract

fetched live from OpenAlex

Abstract BACKGROUND: Diagnosis of pulmonary embolism (PE) using clinical decision rules in combination with D-dimer (DD) values is a standard practice. The Wells score is the most commonly used rule, either in its original (3-category) or modified (2-category) versions, and in conjunction with a (DD) <500 ng/mL allows to exclude a PE in approximately 30% of patients. The recent PEGeD study (Kearon et al. 2019) concluded that a PE can be safely excluded by using a DD threshold adjusted to the clinical pre-test probability (C-PTP). In that study PE was excluded in patients with low C-PTP and a DD <1000 ng/mL or a moderate C-PTP and a DD <500 ng/mL In the present study we aimed to evaluate the performance of the PEGeD algorithm in daily practice. METHODS: We conducted a retrospective cohort study involving all adult patients who presented at London Health Sciences Centre or St. Joseph's Health Care Emergency Departments in London, Ontario, Canada between November 1, 2018 and December 31, 2020 with signs or symptoms suggestive of a pulmonary embolism and for whom a DD was ordered electronically. They were excluded if they did not have complete follow-up information for at least 90 days from the initial visit, they were pregnant, they were on long term anticoagulation for other indications, or had chest imaging prior to DD order. Using the electronic hospital chart, we extracted demographics, imaging results, and the Wells score with all its individual components. In our center, information about the Wells score and its components is routinely and prospectively collected when ordering DD. Since the PEGeD algorithm is not routinely used in our hospital, data of the C-PTP was utilized to determine which DD cut-off should be applied to the patient. Decision to perform imaging studies was taken by the ED physician at the time of assessment. The outcome of interest was the proportion of a PE or DVT at 90 days after the visit to the ED in patients with a low or intermediate C-PTP and who did not receive an initial diagnosis of PE and 99% confidence intervals (CI) were estimated using the Wilson's score method. RESULTS: A total of 2769 patient charts were reviewed and 1070 were included (Table 1, Figure 1). Of the 1070 patients, 71 (7%) of patients had a pulmonary embolism on initial presentation to the emergency department. At 90 days of follow up none (99% CI 0, 0.84) of the 787 patients who had a low C-PTP or a moderate C-PTP score and a DD <1000 ng/mL or <500 ng/mL, respectively, were positive for a PE . This included 194 patients who had a low C-PTP and a DD level of 500-999 ng/mL and 26 patients who had an intermediate C-PTP and a DD level of <500 ng/mL. Notably, 8 (1.02%, 99% CI 0.42-2.43) PEs would have been missed using the PEGeD protocol when using DD cut-off levels of <1000 ng/mL in the low C-PTP group, or <500 ng/mL in the intermediate C-PTP. CONCLUSIONS: In this cohort we found that if the PEGeD algorithm had been used, it would have resulted in a low risk of VTE during follow up in patients without an initial diagnosis of PE and who had either a low C-PTP and a DD <1000 ng/mL or a moderate C-PTP and a DD <500 ng/mL. We also found it would have been associated with 194 (48%) less diagnostic imaging studies in the low C-PTP range and 2 (6%) less studies in the intermediate C-PTP range. Despite this, 1% of patients with PE (99% upper confidence limit 2.43%) would have been missed. This study is limited by its retrospective nature with an inherent risk of misclassification. Further studies are needed before recommending the use of this algorithm in clinical practice. Work Cited Kearon, C., de Wit, K., Parpia, S., Schulman, S., Afilalo, M., Hirsch, A., Spencer, F. A., Sharma, S., D'Aragon, F., Deshaies, J.-F., Le Gal, G., Lazo-Langner, A., Wu, C., Rudd-Scott, L., Bates, S. M., & Julian, J. A. (2019). Diagnosis of Pulmonary Embolism with d -Dimer Adjusted to Clinical Probability. New England Journal of Medicine, 381(22), 2125-2134. https://doi.org/10.1056/NEJMoa1909159 Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.037
metaresearch head score (Gemma)0.121
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.121
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.112
GPT teacher head0.390
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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