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Cuatro métodos de predicción de riesgo de infección bacteriana grave en recién nacidos febriles

Keywords: newborn, fever, severe bacterial infection, risk assessment, prediction studies.

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Abstract:

introduction. the aim of present research was to contrast the effectiveness of four assessment methods of severe bacterial infection risk (sbi) in febrile newborns (nb) , one of above mentioned methods was developed by paper's authors and the other are used in the international practice. methods. a retrospective and descriptive study was conducted and applied in 1358 febrile nb with no focalization signs and classified according to the sbi. the method proposed by authors was applied including a history of be healthy, lack of medical criterion of a infectious-toxic state, lack of evidences of focal infection in physical examination, fever lower than 39°c and no persistent or recurrent, blood leucocytes count >5,0 x 109/l and < 20,0 x 109/l, globular sedimentation speed <20 mm/h and urine leucocyte count <10 000/ml. this method and the other were applied in a initial assessment and at the end of the evolution 48 h. the predictive values were estimated for the different methods and also the effectiveness was assessed according to the gain function. results. the sbi was of 20,4%. the more frequent cause was the urinary tract infection. from the 652 nb initially assessed by our method there was a change of evolution category in 177 (13,0%) with the other methods also there were less marked changes. the failures of predictive values using our method were 40 (8,5%), a ratio significantly lower (p<0.001) than with the other methods. the gain function had higher arithmetic values with the other methods. conclusions. there is a greater margin of safe with our method in relation to the other study assessment methods. this advantage is attributed to the inclusion of clinical and laboratory assessing parameters (the magnitude and persistence of fever and the toxic-infectious feature) that may to change the febrile nb category in the scale, although we must to point out that all methods had prediction errors due to its own probability nature.

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