Evidence map›Paper›PMID 30244362›Full record

ArticleInfectious diseases and therapy2018

Development of a Risk-Scoring Tool to Determine Appropriate Level of Care in Acute Bacterial Skin and Skin Structure Infections in an Acute Healthcare Setting.

Kimberly C Claeys, Evan J Zasowski, Abdalhamid M Lagnf, Noor Sabagha, Donald P Levine, Susan L Davis, Michael J Rybak

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Infectious diseases and therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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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

7 authors at 3 institutions in 1 country.

Kimberly C ClaeysUniversity of Maryland School of Pharmacy, Baltimore, MD, USA.
Evan J ZasowskiAnti-Infective Research Laboratory, Wayne State University Eugene Applebaum College of Pharmacy and Health Sciences, Detroit, MI, USA.
Abdalhamid M LagnfAnti-Infective Research Laboratory, Wayne State University Eugene Applebaum College of Pharmacy and Health Sciences, Detroit, MI, USA.
Noor SabaghaSchool of Medicine, Wayne State University, Detroit, MI, USA.
Donald P LevineDivision of Infectious Disease, Wayne State University School of Medicine, Detroit, MI, USA.
Susan L DavisWayne State University Eugene Applebaum College of Pharmacy and Health Sciences, Detroit, MI, USA.
Michael J RybakAnti-Infective Research Laboratory, Wayne State University Eugene Applebaum College of Pharmacy and Health Sciences, Detroit, MI, USA. aa1592@wayne.edu.
Wayne State University · USEugene Applebaum College of Pharmacy and Health Sciences · USUniversity of Maryland, Baltimore · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAcute bacterial skin and skin structure infections (ABSSSIs) represent a large burden to the US healthcare system. There is little evidence-based guidance regarding the appropriate level of care for ABSSSIs. This study aimed to develop a prediction model and risk-scoring tool to determine appropriate levels of care.

methodsThis was a single-center observational cohort study of adult patients treated for ABSSSIs from 2012 to 2015 at the Detroit Medical Center. The predictive model used to create a novel risk-scoring tool was derived using multinomial regression analysis. The overall accuracy of this tool was compared to the Clinical Resource Efficacy Support Team (CREST) Classification and Standardized Early Warning Score (SEWS) using area-under-the- receiver-operator-curve (AUROC) analysis and Z-statistic.

resultsFinal patient disposition was 230 (45.5%) home from the emergency department (ED), 65 (12.8%) observation unit (OU), and 211 (41.7%) initial inpatient. IV antibiotic therapy was used in 358 (70.8%) patients. CREST and SEWS were not accurate in the determination of ED versus OU disposition [AUROC CREST 0.0.682 (95% CI 0.640-0.724), AUROC SEWS 0.686 (95% CI 0.641-0.731)], but performed better in determining ED/OU versus inpatient [AUROC CREST = 0.678 (95% CI 0.630-0.725), AUROC SEWS 0.693 (95% CI 0.645-0.740)]. These scores were also not accurate in determining IV versus PO antibiotic therapy [AUROC CREST = 0.586 (95% CI 0.530-0.624), AUROC SEWS = 0.630 (95% CI 0.576-0.684)]. A risk-scoring tool ranging from 0 to 10 points was derived incorporating WBC, temperature, site of infection, and past medical history of diabetes, liver disease, PVD, AKI, and/or CKD. The AUROC of the new model was 0.675 (95% CI 0.611-0.739) ED versus OU, 0.789 (95% CI 0.748-0.829) ED/OU versus inpatient, and 0.742 (95% CI 0.694-0.789) IV versus oral antibiotics. The new score had a significantly higher AUROC compared to both the CREST and SEWS for determining ED/OU versus inpatient (p < 0.001).

conclusionPrediction models based on patient risk may be useful for determining appropriate level of care during for ABSSSIs. While the prediction model demonstrated moderate to high levels of correlation with patient level of care, further validation of a prospective cohort of patients is warranted.

Indexed as

Acute bacterial skin and skin structure infectionEmergency departmentObservation unitPatient dispositionPredictive analytics

Identifiers

PMID30244362
PMCPMC6249187
OpenAlexW2893139621

What OpenQuestion holds

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LicenceCC BY-NC
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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.