Measuring Serum Amyloid A for Infection Prediction in Aneurysmal Subarachnoid Hemorrhage

Azurmendi, Leire; Degos, Vincent; Tiberti, Natalia; Kapandji, Natacha; Sánchez, Paola; Sarrafzadeh, Asita; Puybasset, Louis; Turck, Natacha; Sanchez, Jean‐Charles

doi:10.1021/acs.jproteome.5b00391

Cited by 21 publications

(18 citation statements)

References 55 publications

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“…In children with a variety of viral infections, SAA concentrations increased during the acute phase of infection [38]. In a small number of aSAH patients it has also been already proposed as an infection marker [12]. In agreement with this, in the present study we have found that, at admission, SAA concentrations in patients who develop an infection were significantly higher than those who did not.…”

Section: Discussionsupporting

confidence: 90%

“…We therefore combined aSAH clinical parameters with known blood diagnostic biomarkers of infection (SAA, CRP, NP, and WBC) in order to find the most effective combination to predict the infection. The combination of SAA, WBC, WFNS, and age showed 100% SP (95% CI, 100-100) and 64.3% SE (95% CI, 50-78.6); interestingly all four parameters included in this panel had already been described individually as markers of infection [12,29,31,32].…”

Section: Discussionmentioning

confidence: 65%

“…However, for aSAH patients, no blood biomarkers are available in clinical practice. We recently showed that neopterin (NP) and serum amyloid A (SAA) could be promising predictive markers of infection as their plasma concentrations were significantly higher in patients developing infection during hospitalization compared to those who did not [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

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Infection prediction for aneurysmal subarachnoid hemorrhage patients at hospital admission: combined panel of serum amyloid A and clinical parameters

Azurmendi¹,

Sarrafzadeh²,

Tiberti³

et al. 2017

J Transl Sci

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Purpose: Nosocomial infections are some of the main causes of worsening outcomes and death in aneurysmal subarachnoid hemorrhage patients. We hypothesize that combination of clinical parameters and blood biomarkers could increase the capacity of individual markers to dichotomize the patients at risk of infections. Methods:The present study included 104 patients (69 infected/35 non-infected) from two independent European cohorts. Accuracy of biomarkers (serum amyloid A, C-reactive protein, neopterin and WBC) and clinical parameters (WFNS, GCS and age) were evaluated at hospital admission using receiver operating characteristic curves. The most accurate panel combination was obtained using Panelomix. Results:At hospital admission, the most sensitive parameters for the stratification of patients at risk of developing an infection were SAA and the WFNS. To reach a SP of 100% (95% CI, 100-100), SE values of 26.9% (95% CI, 15.9-38.1) and 31.9% (95% CI, 21.7-43.5) were obtained respectively. Moreover, the combination of SAA, WBC, WFNS, and age significantly improved the SE to 64.3% (95% CI, 50-78.6). Conclusions:At hospital admission the panel SAA, WBC, WFNS, and age appear as a promising tool for predicting in-hospital infections, which could lead to a better management of patients and in their associated outcomes.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 65%

Section: Introductionmentioning

confidence: 99%

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Infection prediction for aneurysmal subarachnoid hemorrhage patients at hospital admission: combined panel of serum amyloid A and clinical parameters

Azurmendi¹,

Sarrafzadeh²,

Tiberti³

et al. 2017

J Transl Sci

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“…SAA1/2 has already been described as a potential marker of inflammation and infection in several pathological conditions, including stroke and subarachnoid hemorrhage, [35]. In a case-controlled study involving 54 patients, levels of acute-phase proteins were significantly higher in stroke patients who developed an infection during the month preceding a cerebrovascular event than in those who did not develop one.…”

Section: Discussionmentioning

confidence: 99%

Proteomic discovery and verification of serum amyloid A as a predictor marker of patients at risk of post-stroke infection: a pilot study

et al. 2017

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BackgroundPost-stroke infections occur in 20–36% of stroke patients and are associated with high morbidity and mortality rates. Early identification of patients at risk of developing an infection could improve care via an earlier treatment leading to a better outcome. We used proteomic tools in order to discover biomarkers able to stratify patients at risk of post-stroke infection.MethodsThe post hoc analysis of a prospective cohort study including 40 ischemic stroke patients included 21 infected and 19 non-infected participants. A quantitative, isobaric labeling, proteomic strategy was applied to the plasma samples of 5 infected and 5 non-infected patients in order to highlight any significantly modulated proteins. A parallel reaction monitoring (PRM) assay was applied to 20 additional patients (10 infected and 10 non-infected) to verify discovery results. The most promising protein was pre-validated using an ELISA immunoassay on 40 patients and at different time points after stroke onset.ResultsTandem mass analysis identified 266 proteins, of which only serum amyloid A (SAA1/2) was significantly (p = 0.007) regulated between the two groups of patients. This acute-phase protein appeared to be 2.2 times more abundant in infected patients than in non-infected ones. These results were verified and validated using PRM and ELISA immunoassays, which showed that infected patients had significantly higher concentrations of SAA1/2 than non-infected patients at hospital admission, but also at 1, 3, and 5 days after admission.ConclusionsThe present study demonstrated that SAA1/2 is a promising predictor, at hospital admission, of stroke patients at risk of developing an infection. Further large, multicenter validation studies are needed to confirm these results. If confirmed, SAA1/2 concentrations could be used to identify the patients most at risk of post-stroke infections and therefore implement treatments more rapidly, thus reducing mortality.Electronic supplementary materialThe online version of this article (doi:10.1186/s12014-017-9162-0) contains supplementary material, which is available to authorized users.

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“…Furthermore, blood biomarker levels should be linked not just with general measures of prognosis such as disability or death, but with specific causes of worsening that culminate in poor outcome. Several studies have focused on biomarkers of stroke-associated infections such as IL-6, the Th1/Th2 profile, copeptin, procalcitonin or the recently described serum amyloid A 31. However, the accuracy, sensitivity and specificity of all these biomarkers are still not adequate for clinical use.…”

Section: Biological Datamentioning

confidence: 99%

Principles of precision medicine in stroke

Hinman

Rost

Leung

et al. 2016

J Neurol Neurosurg Psychiatry

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The era of precision medicine has arrived and conveys tremendous potential, particularly for stroke neurology. The diagnosis of stroke, its underlying aetiology, theranostic strategies, recurrence risk and path to recovery are populated by a series of highly individualised questions. Moreover, the phenotypic complexity of a clinical diagnosis of stroke makes a simple genetic risk assessment only partially informative on an individual basis. The guiding principles of precision medicine in stroke underscore the need to identify, value, organise and analyse the multitude of variables obtained from each individual to generate a precise approach to optimise cerebrovascular health. Existing data may be leveraged with novel technologies, informatics and practical clinical paradigms to apply these principles in stroke and realise the promise of precision medicine. Importantly, precision medicine in stroke will only be realised once efforts to collect, value and synthesise the wealth of data collected in clinical trials and routine care starts. Stroke theranostics, the ultimate vision of synchronising tailored therapeutic strategies based on specific diagnostic data, demand cerebrovascular expertise on big data approaches to clinically relevant paradigms. This review considers such challenges and delineates the principles on a roadmap for rational application of precision medicine to stroke and cerebrovascular health.Precision medicine is broadly defined as tailored diagnosis and therapy for each individual patient.

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Measuring Serum Amyloid A for Infection Prediction in Aneurysmal Subarachnoid Hemorrhage

Cited by 21 publications

References 55 publications

Infection prediction for aneurysmal subarachnoid hemorrhage patients at hospital admission: combined panel of serum amyloid A and clinical parameters

Infection prediction for aneurysmal subarachnoid hemorrhage patients at hospital admission: combined panel of serum amyloid A and clinical parameters

Proteomic discovery and verification of serum amyloid A as a predictor marker of patients at risk of post-stroke infection: a pilot study

Principles of precision medicine in stroke

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