Mortality reduction with 23-valent pneumococcal polysaccharide vaccine: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Pneumococcal disease, caused by Streptococcus pneumoniae, imposes a significant global health burden, particularly affecting vulnerable groups such as the elderly and immunocompromised. The 23-valent pneumococcal polysaccharide vaccine (PPV23) is designed to protect against 23 serotypes of Streptococcus pneumoniae. However, there is ongoing debate about its effectiveness in reducing all-cause mortality. This systematic review and meta-analysis aimed to evaluate the efficacy of PPV23 in reducing all-cause and pneumonia-related mortality among adults. METHODS: A systematic search was conducted across PubMed, Embase, and Web of Science, focusing on studies that evaluated the mortality outcomes of adults vaccinated with PPV23 compared to non-vaccinated adults. Both randomized controlled trials (RCTs) and observational studies were included, while case reports, case series, and non-human studies were excluded. Data extraction and quality assessment were facilitated by Nested Knowledge software, using the Newcastle-Ottawa Scale for observational studies and the Cochrane Risk of Bias tool for RCTs. RESULTS: The search yielded 826 records, with 19 studies meeting the inclusion criteria. The pooled analysis of four RCTs showed no significant reduction in all-cause mortality (RR = 1.030; 95% CI: 0.945, 1.122). However, analysis of pneumonia-related mortality across various studies indicated a significant reduction (HR = 0.504; 95% CI: 0.316, 0.693). Moderate to high heterogeneity was noted in mortality studies, and a potential publication bias was identified. CONCLUSION: The findings suggest that while PPV23 may not significantly reduce all-cause mortality, it is effective in reducing pneumonia-related mortality among adults, particularly in those at higher risk. These results support the continued use of PPV23 in targeted adult populations, emphasizing the need for more primary studies to explore its effectiveness across diverse groups.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.047 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".