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Pyogenic vertebral osteomyelitis: identification of microorganism and laboratory markers used to predict clinical outcome.

The aim of this study is to determine the predictive values of laboratory indicators of pyogenic vertebral osteomyelitis (PVO) and a potential cure if the microorganism cannot be identified. Forty-five consecutive patients with PVO were enrolled. Antibiotic therapy with or without surgery was performed according to microorganism. In the negative-culture (NC) group, cefazolin was administered in cases of hematogenous PVO, and vancomycin was administered in cases of postoperative or procedure-related PVO. The clinical, laboratory, and radiological findings were followed up with regard to an appropriate response to antimicrobial therapy. Nine patients were treated with antibiotics alone. We were able to identify the microorganism in 34 cases (75.6%). Ten cases in NC group were cured without recurrence, but one was not. Identification of the microorganisms did not have any significant influence on the treatment outcome, duration of antibiotic administration or normalization of laboratory profiles. For erythrocyte sedimentation rate (ESR) values over 55 mm/h and C-reactive protein (CRP) values of 2.75 mg/dL at fourth week after antibiotic administration by means of ROC curve analysis, we expect significantly high rates of treatment failure by Pearson chi(2) test (chi(2) = 4.344, Odds ratio = 5.15, p = 0.037, 95% CI 1.004-26.597). Even in patients with negative culture findings, it is expected that a good outcome will be achieved by the administration of cefazolin or vancomycin for about 6 weeks. It is concluded that antibiotics selected according to the etiological setting can be initiated without the need to start empirical antibiotics. In every instance at fourth week after the initiation of antibiotic therapy, the values of CRP and ESR can provide meaningful information regarding whether clinicians need to reevaluate the effectiveness of antibiotics by performing follow-up imaging studies and monitoring the patient's clinical manifestations.

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