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Plasma Lactate Dehydrogenase Levels Predict Mortality in Acute Aortic Syndromes: A Diagnostic Accuracy and Observational Outcome Study.

ABSTRACT: In acute aortic syndromes (AAS), organ malperfusion represents a key event impacting both on diagnosis and outcome. Increased levels of plasma lactate dehydrogenase (LDH), a biomarker of malperfusion, have been reported in AAS, but the performance of LDH for the diagnosis of AAS and the relation of LDH with outcome in AAS have not been evaluated so far.This was a bi-centric prospective diagnostic accuracy study and a cohort outcome study. From 2008 to 2014, patients from 2 Emergency Departments suspected of having AAS underwent LDH assay at presentation. A final diagnosis was obtained by aortic imaging. Patients diagnosed with AAS were followed-up for in-hospital mortality.One thousand five hundred seventy-eight consecutive patients were clinically eligible, and 999 patients were included in the study. The final diagnosis was AAS in 201 (20.1%) patients. Median LDH was 424 U/L (interquartile range [IQR] 367-557) in patients with AAS and 383 U/L (IQR 331-460) in patients with alternative diagnoses (P < 0.001). Using a cutoff of 450 U/L, the sensitivity of LDH for AAS was 44% (95% confidence interval [CI] 37-51) and the specificity was 73% (95% CI 69-76). Overall in-hospital mortality for AAS was 23.8%. Mortality was 32.6% in patients with LDH ≥ 450 U/L and 16.8% in patients with LDH < 450 U/L (P = 0.006). Following stratification according to LDH quartiles, in-hospital mortality was 12% in the first (lowest) quartile, 18.4% in the second quartile, 23.5% in the third quartile, and 38% in the fourth (highest) quartile (P = 0.01). LDH ≥ 450 U/L was further identified as an independent predictor of death in AAS both in univariate and in stepwise logistic regression analyses (odds ratio 2.28, 95% CI 1.11-4.66; P = 0.025), in addition to well-established risk markers such as advanced age and hypotension. Subgroup analysis showed excess mortality in association with LDH ≥ 450 U/L in elderly, hemodynamically stable and in nonsurgically treated patients.Plasma LDH constitutes a biomarker of poor outcome in patients with AAS. LDH is a rapid and universally available assay that could be used to improve risk stratification and to individualize treatment in patient groups where options are controversial.

SUBMITTER: Morello F

PROVIDER: S-EPMC4753927 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundPrevious studies have shown that alterations in the gut microbiota are closely associated with Acute Coronary Syndrome (ACS) development. However, the value of gut microbiota for early diagnosis of ACS remains understudied.MethodsWe recruited 66 volunteers, including 29 patients with a first diagnosis of ACS and 37 healthy volunteers during the same period, collected their fecal samples, and sequenced the V4 region of the 16S rRNA gene. Functional prediction of the microbiota was performed using PICRUSt2. Subsequently, we constructed a nomogram and corresponding webpage based on microbial markers to assist in the diagnosis of ACS. The diagnostic performance and usefulness of the model were analyzed using boostrap internal validation, calibration curves, and decision curve analysis (DCA).ResultsCompared to that of healthy controls, the diversity and composition of microbial community of patients with ACS was markedly abnormal. Potentially pathogenic genera such as Streptococcus and Acinetobacter were significantly increased in the ACS group, whereas certain SCFA-producing genera such as Blautia and Agathobacter were depleted. In addition, in the correlation analysis with clinical indicators, the microbiota was observed to be associated with the level of inflammation and severity of coronary atherosclerosis. Finally, a diagnostic model for ACS based on gut microbiota and clinical variables was developed with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.963 (95% CI: 0.925-1) and an AUC value of 0.948 (95% CI: 0.549-0.641) for bootstrap internal validation. The calibration curves of the model show good consistency between the actual and predicted probabilities. The DCA showed that the model had a high net clinical benefit for clinical applications.ConclusionOur study is the first to characterize the composition and function of the gut microbiota in patients with ACS and healthy populations in Southwest China and demonstrates the potential effect of the microbiota as a non-invasive marker for the early diagnosis of ACS.

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Plasma Lactate Dehydrogenase Levels Predict Mortality in Acute Aortic Syndromes: A Diagnostic Accuracy and Observational Outcome Study.

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