<i>Streptococcus pneumoniae</i> Serotype Distribution Among US Adults Hospitalized With Community-Acquired Pneumonia, 2019–2020
Bibliographic record
Abstract
Abstract Background Serotype-specific urinary antigen detection (UAD) assay results can be used to estimate the serotype contribution among adults with pneumococcal community-acquired pneumonia (CAP) and to guide recommendations regarding higher-valency pneumococcal conjugate vaccines (PCVs). Methods Adults aged ≥18 years hospitalized with radiographic evidence of CAP were prospectively enrolled in 4 US cities from November 2019 to December 2020, overlapping the coronavirus disease 2019 (COVID-19) pandemic. Data were collected by patient interview and medical chart review. Streptococcus pneumoniae was isolated from standard-of-care respiratory samples and blood; urine collected per-protocol was tested by S pneumoniae BinaxNOW and UAD assays. The proportions of adults with radiologically confirmed CAP (RAD+ CAP) testing positive for S pneumoniae and for serotypes contained in PCV13, PCV15, and PCV20 were calculated. Results Among 3098 adults enrolled, 2105 (67.9%) had RAD+ CAP. Of these, 44.3% were ≥65 years of age, and most had a chronic medical condition (46.0%) or were immunocompromised (38.5%). Streptococcus pneumoniae was detected by any method in 214 (10.2%) RAD+ CAP participants, including 63 (3.0%) with serotypes covered by PCV13, 81 (3.9%) by PCV15, and 119 (5.7%) by PCV20. Streptococcus pneumoniae and PCV serotype positivity were higher before the pandemic (November 2019–April 2020) compared to during the COVID-19 pandemic (May 2020–December 2020). Conclusions Our study demonstrated that despite the COVID-19 pandemic, PCV serotype pneumococcus continued to cause an important proportion of adult CAP in the US. These data are useful for informing PCV recommendations and for establishing an epidemiologic baseline to assess the impact of such recommendations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".