Complicated pneumococcal pneumonia in the era of higher-valent pneumococcal conjugate vaccines: a systematic literature review and meta-analysis, 2001–2022
Bibliographic record
Abstract
PURPOSE: To estimate pneumococcal conjugate vaccine (PCV) national program impact on pneumococcal complicated pneumonia (PnCP) based on changes in PnCP population-based incidence, PnCP proportion of all-cause complicated pneumonia (or invasive pneumococcal disease), and PnCP serotype distribution. METHODS: MEDLINE, EMBASE, and Global Index Medicus articles (2001-March 2022) reporting laboratory-confirmed PnCP studies were stratified by age group, outcome measure, PCV program period(s) (pre-PCV, transition, and post-PCV), serotype distribution (based on serotyping methodology used), and PCV serotype formulation. Random effect meta-analysis of the total number of serotyped isolates within each study was used to calculate pooled serotype-specific percentages. RESULTS: Of 1360 publications screened, the 134 studies included from 30 countries differed widely by methodological approaches. Pediatric PnCP incidence tended to decline from pre-PCV to post-PCV periods, as did PnCP as a proportion of all-cause complicated pneumonia from transition to post-PCV periods. Studies describing changes in serotype distribution by PCV program period applied detection methods that varied from pre-PCV period microbiological culture with Quellung serotyping to in the transition and post-PCV periods molecular methods like PCR. Meta-analysis revealed near elimination of pediatric PCV7-serotype PnCP between pre- and post-PCV, while the PCV13nonPCV7 percentage increased from 51.1% pre-PCV period to 76.5% in the transition period, remaining stable post-PCV period. Non-PCV13 serotypes increased slightly from low baseline numbers. Adult data were lacking or inconsistent. CONCLUSIONS: Although studies were heterogeneous, pediatric PnCP incidence and proportion tended to decline from pre-PCV to post-PCV periods, and PCV13nonPCV7 serotype distribution percentage remained unchanged from transition to post-PCV period. Standardization of PnCP surveillance methods, definitions, and reporting is needed to evaluate accurately PCV program impact.
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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 | 0.017 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.043 |
| Bibliometrics | 0.009 | 0.012 |
| 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) | 0.003 | 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".