Disruption of silicone valve housing in a Codman Hakim Precision valve with integrated Siphonguard
Bibliographic record
Abstract
Authors of this report describe 2 patients who had undergone shunt insertion for hydrocephalus and who, at 6 weeks or 9 months after their last revision, presented with symptoms of shunt dysfunction and CSF collections at the valve site. At the ensuing shunt revision in both patients, the silicone housing was fractured and the Siphonguard was disconnected from the Codman Hakim Precision flat-bottom valve. The cause of these failures was not clear since manipulation, bending, and twisting of the valves were not thought to have occurred during implantation. A review of the FDA's Manufacturer and User Facility Device Experience (MAUDE) database revealed 58 cases of silicone housing failure in the Codman Hakim Precision valve with integrated Siphonguard since the year 2000. A single report was found in the databases administered by the Canadian Medical Devices Sentinel Network (CMDSNet). The Codman Hakim Precision valves with integrated Siphonguard are delicate devices that do not withstand the intraoperative handling tolerated by other valves. When these valves are implanted, gentle handling and wide exposures are needed to minimize the risk of valve damage. Valves should be handled according to the manufacturer's instructions. However, in light of this particular pattern of failure, it is recommended that the manufacturer redesign this valve to provide handling tolerance that is characteristic of other valves on the market. The featured cases illustrate the importance of the surgeon's role in postmarket surveillance of medical devices and reporting device failures to the responsible agencies and manufacturers.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".