Bibliographic record
Abstract
Anticoagulants are in widespread use for the management of a variety of conditions, ranging from thrombus prevention to the treatment of arterial and venous occlusion. As with any effective therapy, recognition of adverse effects is critically important for the safe use of these drugs. Pitfalls in the use of heparins include dosing in close proximity to invasive procedures; not closely monitoring patients in whom dose adjustments may be required, such as the very obese, the elderly, and patients with renal or hepatic failure; failing to make dose adjustments during pregnancy; and not recognizing when patients are developing heparin-induced thrombocytopenia or osteoporosis. Pitfalls in the use of unfractionated heparin include delays in achieving a therapeutic activated partial thromboplastin time (aPTT) and failure to consider the effects of protein binding in acutely ill patients. A pitfall in the use of low molecular weight heparin is giving prophylactic doses when therapeutic doses are indicated. Pitfalls in the use of warfarin are stopping heparin before the warfarin is fully effective; failing to maintain the International Normalized Ratio within the therapeutic range; failing to adjust the dose of warfarin because of changes in diet, renal or hepatic failure, and exposure to new drugs; failing to stop warfarin at an appropriate interval before an invasive procedure; and giving warfarin during pregnancy. Pitfalls in the use of thrombin inhibitors include using them with thrombolytic agents; giving them in proximity to invasive procedures; not adjusting the dose for renal or hepatic failure; and failing to consider the effect of these agents on the prothrombin time when initiating warfarin therapy.
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 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 | 0.025 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.009 | 0.024 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".