Literature DB >> 20586653

Predicting bacteremia among patients hospitalized for skin and skin-structure infections: derivation and validation of a risk score.

Benjamin A Lipsky1, Marin H Kollef, Loren G Miller, Xiaowu Sun, Richard S Johannes, Ying P Tabak.   

Abstract

OBJECTIVE: Bacteremia is relatively common in patients with skin and skin-structure infection (SSSI) severe enough to require hospitalization. We used selected demographic and clinical characteristics easily assessable at initial evaluation to develop a model for the early identification of patients with SSSI who are at higher risk for bacteremia. PARTICIPANTS: A large database of adults hospitalized with SSSI at 97 hospitals in the United States during the period from 2003 through 2007 and from whom blood samples were obtained for culture at admission.
METHODS: We compared selected candidate predictor variables for patients shown to have bacteremia and patients with no demonstrated bacteremia. Using stepwise logistic regression to identify independent risk factors for bacteremia, we derived a model by using 75% of a randomly split cohort, converted the model coefficients into a risk score system, and then we validated it by using the remaining 25% of the cohort.
RESULTS: Bacteremia was documented in 1,021 (11.7%) of the 8,747 eligible patients. Independent predictors of bacteremia (P<.001) were infected device or prosthesis, respiratory rate less than 10 or more than 29 breaths per minute, pulse rate less than 49 or more than 125 beats per minute, temperature less than 35.6 degrees C or at least 38.0 degrees C, white blood cell band percentage of 7% or more, white blood cell count greater than 11x10(9)/L, healthcare-associated infection, male sex, and older age. The bacteremia rates ranged from 3.7% (lowest decile) to 30.6% (highest decile) (P<.001). The model C statistic was 0.71; the Hosmer-Lemeshow test P value was .36, indicating excellent model calibration.
CONCLUSIONS: Using data available at hospital admission, we developed a risk score that differentiated SSSI patients at low risk for bacteremia from patients at high risk. This score may help clinicians identify patients who require more intensive monitoring or antimicrobial regimens appropriate for treating bacteremia.

Entities:  

Mesh:

Year:  2010        PMID: 20586653     DOI: 10.1086/654007

Source DB:  PubMed          Journal:  Infect Control Hosp Epidemiol        ISSN: 0899-823X            Impact factor:   3.254


  10 in total

Review 1.  Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.

Authors:  Benjamin A Goldstein; Ann Marie Navar; Michael J Pencina; John P A Ioannidis
Journal:  J Am Med Inform Assoc       Date:  2016-05-17       Impact factor: 4.497

2.  Clindamycin versus trimethoprim-sulfamethoxazole for uncomplicated skin infections.

Authors:  Loren G Miller; Robert S Daum; C Buddy Creech; David Young; Michele D Downing; Samantha J Eells; Stephanie Pettibone; Rebecca J Hoagland; Henry F Chambers
Journal:  N Engl J Med       Date:  2015-03-19       Impact factor: 91.245

3.  Staphylococcal Protein A Contributes to Persistent Colonization of Mice with Staphylococcus aureus.

Authors:  Yan Sun; Carla Emolo; Silva Holtfreter; Siouxsie Wiles; Barry Kreiswirth; Dominique Missiakas; Olaf Schneewind
Journal:  J Bacteriol       Date:  2018-04-09       Impact factor: 3.490

4.  A Placebo-Controlled Trial of Antibiotics for Smaller Skin Abscesses.

Authors:  Robert S Daum; Loren G Miller; Lilly Immergluck; Stephanie Fritz; C Buddy Creech; David Young; Neha Kumar; Michele Downing; Stephanie Pettibone; Rebecca Hoagland; Samantha J Eells; Mary G Boyle; Trisha Chan Parker; Henry F Chambers
Journal:  N Engl J Med       Date:  2017-06-29       Impact factor: 91.245

Review 5.  Diagnosis and management of skin and soft tissue infections in the intensive care unit: a review.

Authors:  Jason P Burnham; John P Kirby; Marin H Kollef
Journal:  Intensive Care Med       Date:  2016-10-03       Impact factor: 17.440

6.  Incidence of skin and soft tissue infections in ambulatory and inpatient settings, 2005-2010.

Authors:  Loren G Miller; Debra F Eisenberg; Honghu Liu; Chun-Lan Chang; Yan Wang; Rakesh Luthra; Anna Wallace; Christy Fang; Joseph Singer; Jose A Suaya
Journal:  BMC Infect Dis       Date:  2015-08-21       Impact factor: 3.090

Review 7.  Treatment of Gram-positive infections in critically ill patients.

Authors:  Cristina Vazquez-Guillamet; Marin H Kollef
Journal:  BMC Infect Dis       Date:  2014-11-28       Impact factor: 3.090

8.  Machine learning for fast identification of bacteraemia in SIRS patients treated on standard care wards: a cohort study.

Authors:  Franz Ratzinger; Helmuth Haslacher; Thomas Perkmann; Matilde Pinzan; Philip Anner; Athanasios Makristathis; Heinz Burgmann; Georg Heinze; Georg Dorffner
Journal:  Sci Rep       Date:  2018-08-15       Impact factor: 4.379

9.  Factors associated with sepsis development in 606 Spanish adult patients with cellulitis.

Authors:  J Collazos; B de la Fuente; J de la Fuente; A García; H Gómez; C Menéndez; H Enríquez; P Sánchez; M Alonso; I López-Cruz; M Martín-Regidor; A Martínez-Alonso; J Guerra; A Artero; M Blanes; V Asensi
Journal:  BMC Infect Dis       Date:  2020-03-12       Impact factor: 3.090

Review 10.  A systematic review showing the lack of diagnostic criteria and tools developed for lower-limb cellulitis.

Authors:  M Patel; S I Lee; R K Akyea; D Grindlay; N Francis; N J Levell; P Smart; J Kai; K S Thomas
Journal:  Br J Dermatol       Date:  2019-06-28       Impact factor: 9.302

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.