A Worldwide Perspective of Nursing Home-Acquired Pneumonia Compared With Community-Acquired Pneumonia
Bibliographic record
Abstract
BACKGROUND: Nursing home-acquired pneumonia (NHAP) is the leading cause of death among long-term care patients and the second most common cause of transfers to acute care facilities. The aim of this study was to characterize the incidence, microbiology, and outcomes for hospitalized patients with community-acquired pneumonia (CAP) and NHAP. METHODS: A secondary analysis of 5,160 patients from the Community-Acquired Pneumonia Organization database was performed. World regions were defined as the United States and Canada (I), Latin America (II), and Europe (III). RESULTS: From a total of 5,160 hospitalized patients with CAP, NHAP was identified in 287 (5.6%) patients. Mean age was 80 y. NHAP distribution by region was 6% in region I, 3% in region II, and 7% in region III. Subjects with NHAP had higher frequencies of neurological disease, diabetes mellitus, congestive heart failure, and renal failure than did subjects with CAP (P < .001). ICU admission was required in 32 (12%) subjects. Etiology was defined in 68 (23%) subjects with NHAP and 1,300 (27%) with CAP. The most common pathogens identified in NHAP included Streptococcus pneumoniae (31%), Staphylococcus species (31%), and Pseudomonas aeruginosa (7%). Presentation of NHAP more frequently included pleural effusions (34% vs 21%, P < .001) and multilobar involvement (31% vs 24%, P < .001). Thirty-day hospital mortality was statistically greater among subjects with NHAP than among those with CAP (42% vs 18%, P < .001). CONCLUSIONS: Worldwide, only a very small proportion of hospitalized patients with CAP present with NHAP; the poor outcomes for these patients may be due primarily to a higher number of comorbidities compared with patients without NHAP.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".