ABSTRACT
BACKGROUND: The central venous-to-arterial carbon dioxide difference (Pcv-aCO2) is a biomarker for tissue perfusion, but the diagnostic value of Pcv-aCO2 in bacteria bloodstream infections (BSI) caused by gram-negative (GN) bacteria remains unclear. This study evaluated the expression levels and diagnostic value of Pcv-aCO2 and procalcitonin (PCT) in the early stages of GN bacteria BSI. METHODS: Patients with BSI admitted to the intensive care unit at Guangdong Provincial People's Hospital between August 2014 and August 2017 were enrolled. Pcv-aCO2 and PCT levels were evaluated in GN and gram-positive (GP) bacteria BSI patients. RESULTS: A total of 132 patients with BSI were enrolled. The Pcv-aCO2 (8.32 ± 3.59 vs 4.35 ± 2.24 mmHg p = 0.001) and PCT (30.62 ± 34.51 vs 4.92 ± 6.13 ng/ml p = 0.001) levels were significantly higher in the GN group than in the GP group. In the diagnosis of GN bacteria BSI, the area under the receiver operating characteristic curve (AUROC) for Pcv-aCO2 was 0.823 (95% confidence interval (CI): 0.746-0.900). The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 71.90%, 88.00%, 74.07% and 78.21%, respectively. The AUROC for PCT was 0.818 (95% CI: 0.745-0.890). The sensitivity, specificity, PPV and NPV were 57.90%, 94.67%, 71.93% and 74.67%, respectively. CONCLUSIONS: Pcv-aCO2 and PCT have similar and high diagnostic value for the early diagnosis of BSI caused by GN bacteria.
Subject(s)
Bacteremia , Gram-Negative Bacterial Infections , Sepsis , Humans , Procalcitonin , Gram-Negative Bacterial Infections/diagnosis , Gram-Negative Bacterial Infections/microbiology , ROC Curve , Gram-Negative Bacteria , Early Diagnosis , Bacteria , Retrospective Studies , Bacteremia/diagnosis , Bacteremia/microbiologyABSTRACT
Red blood cell distribution width (RDW) was frequently assessed in COVID-19 infection and reported to be associated with adverse outcomes. However, there was no consensus regarding the optimal cutoff value for RDW. Records of 98 patients with COVID-19 from the First People's Hospital of Jingzhou were reviewed. They were divided into two groups according to the cutoff value for RDW on admission by receiver operator characteristic curve analysis: ≤11.5% (n = 50) and >11.5% (n = 48). The association of RDW with the severity and outcomes of COVID-19 was analyzed. The receiver operating characteristic curve indicated that the RDW was a good discrimination factor for identifying COVID-19 severity (area under the curve = 0.728, 95% CI: 0.626-0.830, p < 0.001). Patients with RDW > 11.5% more frequently suffered from critical COVID-19 than those with RDW ≤ 11.5% (62.5% vs. 26.0%, p < 0.001). Multivariate logistic regression analysis showed RDW to be an independent predictor for critical illness due to COVID-19 (OR = 2.40, 95% CI: 1.27-4.55, p = 0.007). A similar result was obtained when we included RDW > 11.5% into another model instead of RDW as a continuous variable (OR = 5.41, 95% CI: 1.53-19.10, p = 0.009). RDW, as an inexpensive and routinely measured parameter, showed promise as a predictor for critical illness in patients with COVID-19 infection. RDW > 11.5% could be the optimal cutoff to discriminate critical COVID-19 infection.