Evidence map›Paper›PMID 27756213›Full record

ArticleBMC infectious diseases2016

Development of a prediction model for bacteremia in hospitalized adults with cellulitis to aid in the efficient use of blood cultures: a retrospective cohort study.

Chun-Yuan Lee, Calvin M Kunin, Chung Chang, Susan Shin-Jung Lee, Yao-Shen Chen, Hung-Chin Tsai

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.5field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 22 citations in OpenAlex.

  1. Clinical predictors, microbiological profile, and outcomes of bacteremia in patients with cellulitis: a 6-year retrospective cohort study.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
    Observational
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Observational
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 5 institutions in 2 countries.

Chun-Yuan LeeDivision of Infectious Diseases, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.
Calvin M KuninDepartment of Internal Medicine (CMK), Ohio State University, Columbus, OH, USA.
Chung ChangDepartment of Applied Mathematics, National Sun Yat-sen University, Kaohsiung, Taiwan.
Susan Shin-Jung LeeDivision of Infectious Diseases, Department of Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan.
Yao-Shen ChenDivision of Infectious Diseases, Department of Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan.
Hung-Chin TsaiDivision of Infectious Diseases, Department of Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan. hctsai1011@yahoo.com.tw.
Kaohsiung Veterans General Hospital · TWKaohsiung Medical University Chung-Ho Memorial Hospital · TWNational Sun Yat-sen University · TWNational Yang Ming Chiao Tung University · TWUniversity of Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCellulitis is a common infectious disease. Although blood culture is frequently used in the diagnosis and subsequent treatment of cellulitis, it is a contentious diagnostic test. To help clinicians determine which patients should undergo blood culture for the management of cellulitis, a diagnostic scoring system referred to as the Bacteremia Score of Cellulitis was developed.

methodsUnivariable and multivariable logistic regression analyses were performed as part of a retrospective cohort study of all adults diagnosed with cellulitis in a tertiary teaching hospital in Taiwan in 2013. Patients who underwent blood culture were used to develop a diagnostic prediction model where the main outcome measures were true bacteremia in cellulitis cases. Area under the receiver operating characteristics curve (AUC) was used to demonstrate the predictive power of the model, and bootstrapping was then used to validate the performance.

resultsThree hundred fifty one cases with cellulitis who underwent blood culture were enrolled. The overall prevalence of true bacteremia was 33/351 cases (9.4 %). Multivariable logistic regression analysis showed optimal diagnostic discrimination for the combination of age ≥65 years (odds ratio [OR] = 3.9; 95 % confidence interval (CI), 1.5-10.1), involvement of non-lower extremities (OR = 4.0; 95 % CI, 1.5-10.6), liver cirrhosis (OR = 6.8; 95 % CI, 1.8-25.3), and systemic inflammatory response syndrome (SIRS) (OR = 15.2; 95 % CI, 4.8-48.0). These four independent factors were included in the initial formula, and the AUC for this combination of factors was 0.867 (95 % CI, 0.806-0.928). The rounded formula was 1 × (age ≥65 years) + 1.5 × (involvement of non-lower extremities) + 2 × (liver cirrhosis) + 2.5 × (SIRS). The overall prevalence of true bacteremia (9.4 %) in this study could be lowered to 1.0 % (low risk group, score ≤1.5) or raised to 14.7 % (medium risk group, score 2-3.5) and 41.2 % (high risk group, score ≥4.0), depending on different clinical scores.

conclusionsDetermining the risk of bacteremia in patients with cellulitis will allow a more efficient use of blood cultures in the diagnosis and treatment of this condition. External validation of this preliminary scoring system in future trials is needed to optimize the test.

Indexed as

AdultAgedAged, 80 and overBacteremiaBlood CultureCellulitisCohort StudiesFemaleHospitalizationHumansLogistic ModelsMaleMiddle AgedModels, BiologicalOdds RatioRetrospective StudiesBacteremiaCellulitisPrediction model

Identifiers

PMID27756213
PMCPMC5070006
OpenAlexW2538014667

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.