Lista Choosing Wisely della Società Italiana di Patologia Clinica e Medicina di Laboratorio (2022): una proposta di aggiornamento
Bibliographic record
Abstract
The Evidence Based Laboratory Medicine Group of study of the Italian Society of Clinical Pathology and Laboratory Medicine (EBLM GdS) adopted the approach of the American Society of Clinical Pathology and, rather than replacing the 2017 recommendations, is proposing to add five recommendations to the current SIPMeL Choosing wisely (CW) list involving the Society members. The EBLM GdS reviewed the 35 ASCP-CW, CW-Canada and CW-Australia recommendations and identified the five that possess the greatest relevance for Italian laboratories. This observatory identified five recommendations: 1) do not request amylase in addition to lipase when acute pancreatitis is suspected; 2) do not request erythrocyte sedimentation rate (ESR) measurement to screen asymptomatic patients or as a general test to detect inflammatory states in patients with undiagnosed conditions; 3) do not request serum ammonium for diagnosis or management of hepatic encephalopathy (EE); 4) do not request serum protein electrophoresis in asymptomatic patients in the absence of hypercalcemia, renal failure, anemia, or bone lytic lesions not otherwise explainable; and 5) do not request uric acid as part of routine assessment of cardiovascular risk, obesity, or diabetes. This preliminary draft presents a more extensive description and references than the previous SIPMeL-CW list in order to provide members with more elements to evaluate them and, if approved, it will be abridged. The sharing of the recommendations by SIPMeL members will be done through: 1) publication of the article in the official journal of SIPMeL; 2) sending the article to all members; and 3) presentation at the National Congress 2022. The five recommendations, if approved, will be forwarded to the National Council and to Choosing Wisely Italy for evaluation.
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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 | 0.030 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.024 | 0.029 |
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".