Portuguese
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Journal of Infection 2011-Aug

A simple model to predict bacteremia in women with acute pyelonephritis.

Apenas usuários registrados podem traduzir artigos
Entrar Inscrever-se
O link é salvo na área de transferência
Kyung Su Kim
Kyuseok Kim
You Hwan Jo
Tae Yun Kim
Jin Hee Lee
Se Jong Lee
Joong Eui Rhee
Gil Joon Suh

Palavras-chave

Resumo

OBJECTIVE

To construct a simple model to predict bacteremia in women with uncomplicated acute pyelonephritis (APN) for the judicious use of blood cultures.

METHODS

A prospective database including 735 women with uncomplicated APN at an academic urban emergency department was analyzed retrospectively. Independent risk factors were determined using multivariate logistic regression in two-thirds of patients. Cutoff values representing 10% and 30% of risk were selected for the stratification. This model was internally and externally validated using a remaining one-thirds of patients and 169 independent patients, respectively.

RESULTS

Independent risk factors were as follows: age ≥65 years (odds ratio [OR]=5.18, 4 points), vomiting (OR=2.40, 2 points), heart rate >110 beats/min (OR=2.35, 2 points), segmented neutrophils >90% (OR=3.17, 3 points), and urine WBC ≥50/HPF (OR=4.27, 4 points). Patients were stratified as low (points <4), intermediate (points, 4-6), or high risk (7≤ points). The areas under receiver operating characteristics curves were 0.707 and 0.792 in internal and external validation cohorts, respectively. The model stratified internal and external validation cohort into low (8.5% and 5.7%), intermediate (16.5% and 14.8%), and high risk of bacteremia (42.0% and 56.4%).

CONCLUSIONS

This model provides a useful tool to predict the risk of bacteremia, which can be helpful to decide whether to perform blood cultures and whether to admit the patient for the intravenous antibiotics in women with uncomplicated APN.

Junte-se à nossa
página do facebook

O mais completo banco de dados de ervas medicinais apoiado pela ciência

  • Funciona em 55 idiomas
  • Curas herbais apoiadas pela ciência
  • Reconhecimento de ervas por imagem
  • Mapa GPS interativo - marcar ervas no local (em breve)
  • Leia publicações científicas relacionadas à sua pesquisa
  • Pesquise ervas medicinais por seus efeitos
  • Organize seus interesses e mantenha-se atualizado com as notícias de pesquisa, testes clínicos e patentes

Digite um sintoma ou doença e leia sobre ervas que podem ajudar, digite uma erva e veja as doenças e sintomas contra os quais ela é usada.
* Todas as informações são baseadas em pesquisas científicas publicadas

Google Play badgeApp Store badge