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. 2013 Aug 5;8(8):e70305.
doi: 10.1371/journal.pone.0070305. Print 2013.

Mycobacterium tuberculosis bacteremia in a cohort of hiv-infected patients hospitalized with severe sepsis in uganda–high frequency, low clinical suspicion [corrected] and derivation of a clinical prediction score

Affiliations

Mycobacterium tuberculosis bacteremia in a cohort of hiv-infected patients hospitalized with severe sepsis in uganda–high frequency, low clinical suspicion [corrected] and derivation of a clinical prediction score

Shevin T Jacob et al. PLoS One. .

Erratum in

  • PLoS One. 2013;8(8). doi:10.1371/annotation/0a53f994-bfe2-45db-9dbb-97fdfea023c5

Abstract

Background: When manifested as Mycobacterium tuberculosis (MTB) bacteremia, disseminated MTB infection clinically mimics other serious blood stream infections often hindering early diagnosis and initiation of potentially life-saving anti-tuberculosis therapy. In a cohort of hospitalized HIV-infected Ugandan patients with severe sepsis, we report the frequency, management and outcomes of patients with MTB bacteremia and propose a risk score based on clinical predictors of MTB bacteremia.

Methods: We prospectively enrolled adult patients with severe sepsis at two Ugandan hospitals and obtained blood cultures for MTB identification. Multivariable logistic regression modeling was used to determine predictors of MTB bacteremia and to inform the stratification of patients into MTB bacteremia risk categories based on relevant patient characteristics.

Results: Among 368 HIV-infected patients with a syndrome of severe sepsis, eighty-six (23%) had MTB bacteremia. Patients with MTB bacteremia had a significantly lower median CD4 count (17 vs 64 lymphocytes/mm(3), p<0.001) and a higher 30-day mortality (53% vs 32%, p = 0.001) than patients without MTB bacteremia. A minority of patients with MTB bacteremia underwent standard MTB diagnostic testing (24%) or received empiric anti-tuberculosis therapy (15%). Independent factors associated with MTB bacteremia included male sex, increased heart rate, low CD4 count, absence of highly active anti-retroviral therapy, chief complaint of fever, low serum sodium and low hemoglobin. A risk score derived from a model containing these independent predictors had good predictive accuracy [area under the curve = 0.85, 95% CI 0.80-0.89].

Conclusions: Nearly 1 in 4 adult HIV-infected patients hospitalized with severe sepsis in 2 Ugandan hospitals had MTB bacteremia. Among patients in whom MTB was suspected, standard tests for diagnosing pulmonary MTB were inaccurate for correctly classifying patients with or without bloodstream MTB infection. A MTB bacteremia risk score can improve early diagnosis of MTB bacteremia particularly in settings with increased HIV and MTB co-infection.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Prevalence of MTB in blood culture compared to other causes of bacteremia among HIV-infected patients (n = 368).
[NTS = non-typhoidal Salmonella; NTM = non-tuberculous mycobacteria].
Figure 2
Figure 2. Kaplan-Meier survival curves comparing 30-day mortality between patients with MTB bacteremia and patients without MTB bacteremia.
Figure 3
Figure 3. Receiver operating characteristic curves of final logistic regression model containing all independent predictors (sex, CD4 count, HAART status, fever, heart rate, hemoglobin, and sodium) compared to logistic regression model with HIV-associated predictors only (CD4 count and HAART status only) [CD4 = CD4+ T-cell count; HAART = highly active anti-retroviral therapy; AUC = area under the curve].
Figure 4
Figure 4. Risk of MTB bacteremia corresponding to MTB bacteremia risk score totals.

References

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