Efficacy of Pneumococcal Immunization in Patients with Renal Disease – What Is the Data?
Bibliographic record
Abstract
BACKGROUND/AIMS: There is an increased incidence of invasive pneumococcal disease in patients with renal allografts, chronic renal insufficiency (CRI), or nephrotic syndrome (NS). Routine pneumococcal immunization (PI) has been recommended for these patients, but the efficacy of PI in this population is not well established. METHODS: A review was done of studies that reported the immunologic response, efficacy, or safety of PI in patients with renal allografts, CRI, or NS. RESULTS: On review of 26 published studies of PI in this population, all studies demonstrated a serologic response by the majority of patients to at least some pneumococcal serotypes. Use of steroids did not alter this response. In the studies with a greater than 6-month follow-up, declining antibody titers were consistently reported, and this decline was usually more rapid than in healthy controls. However, because the studies of the efficacy of PI in this population involve small numbers of patients and are not controlled, the significance of this decline in titers is not known. The incidence of serious adverse reactions to PI is very low. CONCLUSION: Pending more data, patients with renal transplants, CRI, or NS should continue to be offered PI.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".