Approach to nail trauma for primary care physicians
Bibliographic record
Abstract
OBJECTIVE: To provide an overview and approach to common nail bed injuries seen by primary care practitioners. SOURCES OF INFORMATION: An Ovid MEDLINE literature search was performed using search terms and studies were graded based on level of evidence. MAIN MESSAGE: Nail trauma is common in primary care practice and requires proper and prompt treatment to avoid lasting effects on finger function and cosmesis. When presented with a fingernail injury, primary care physicians should perform a thorough physical examination to determine extent of injury; take a history to rule out notable risk factors; perform a comprehensive neurovascular examination to assess pulp capillary refill, to do a 2-point discrimination, and to compare with an uninjured digit; and evaluate range of motion. Clinical evaluation may require local anesthesia and a tourniquet. Nail bed trauma can present in different ways and includes subungual hematomas, distal phalanx fractures, Seymour fractures, and-in more severe cases-fragmentation or avulsion of the nail bed. Treatment for subungual hematomas where the nail plate is intact does not require nail plate removal and nail bed exploration; however, exploration and repair are indicated for a nail plate injury, a proximal fracture involving the germinal matrix, and a distal phalanx fracture requiring stabilization. CONCLUSION: Fingertips are essential to normal hand function. Nail trauma is common and can be managed by primary care physicians. Shared decision making concerning management is based on the mechanism and extent of the injury and aims to prevent secondary deformities.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 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".