Pneumococcal vaccine administration associated with splenectomy: The need for improved education, documentation, and the use of a practical checklist
Bibliographic record
Abstract
An audit was performed of the documentation of pneumococcal vaccination in splenectomy patients in three major hospitals involving a geographical population base of 350,000 patients in British Columbia, Canada. Overall, 111 of the 164 hospitalized splenectomy patients (68%) had received pneumococcal vaccination. Of elective splenectomy cases, only 11 of 55 (20%) had been vaccinated prior to surgery, as is currently recommended. One hundred fifty-five patients (95%) had splenectomy status mentioned in the discharge summary. However, only 35 (21%) had mention of vaccination status, 10 (6%) mention of the need for future revaccination, and only 8 (5%) notation of the possibility of future infectious risks. The rate of pneumococcal vaccination was as satisfactory as any reported in the literature to date. However, there is need for improved education in relation to the timing of vaccination and discharge summary documentation. A checklist for potential splenectomy patients may aid in improving this situation as may geographically based splenectomy registries.
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 | 0.020 | 0.131 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".