SPECT V/Q for the diagnosis of pulmonary embolism: protocol for a systematic review and meta-analysis of diagnostic accuracy and clinical outcome
Bibliographic record
Abstract
INTRODUCTION: Single photon emission computed tomography ventilation/perfusion (SPECT V/Q) imaging has many proponents within the nuclear medicine community and has already largely replaced planar V/Q scintigraphy in daily practice for the diagnosis of pulmonary embolism (PE). However, the test is still described in clinical guidelines as an experimental test because of insufficient evidence. METHODS AND ANALYSIS: We will conduct a systematic review and a meta-analysis of diagnostic accuracy and management outcome studies involving patients evaluated with V/Q SPECT for suspected acute PE. We will search from inception to 19 December 2017 MEDLINE, Embase and the Cochrane Central Register of Controlled Trials for diagnostic accuracy studies, randomised controlled trials and observational cohort studies. Two reviewers will conduct all screening and data collection independently. The methodological quality and risk of bias of eligible studies will be carefully and rigorously assessed using the Quality Assessment of Diagnostic Accuracy Studies-2, the Cochrane Collaboration's tool and the Risk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) tools. The primary outcomes will be sensitivity, specificity and likelihood ratios of V/Q SPECT for the diagnosis of acute PE. The secondary outcomes will be the rate of venous thromboembolism during a 3-month follow-up period in patients left untreated after a negative diagnostic work-up based on SPECT V/Q. ETHICS AND DISSEMINATION: This study of secondary data does not require ethics approval. It will be presented internationally and published in the peer-reviewed literature. PROSPERO REGISTRATION NUMBER: CRD42018084095.
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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 | 0.069 | 0.113 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.025 | 0.030 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.051 | 0.005 |
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".