Internal quality control status for <scp>BNP</scp> and <scp>NT</scp>‐pro<scp>BNP</scp> in China from 2014 to 2017

Sun, Huizhen; Wang, Wei; Zhao, Haijian; Zhang, Chuanbao; He, Falin; Zhong, Kangping; Yuan, Shuai; Wang, Zhiguo

doi:10.1002/jcla.22643

Cited by 6 publications

(3 citation statements)

References 24 publications

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“…In the multicenter cohort study, the NT-proBNP measurement was based on four assays, and the variation among laboratories was not evaluated. However, the four assays used same antibodies and calibrator from the same vendor, and previous data showed that the between-method variability of NT-proBNP was not the predominant component of total variability [ 43 ], and the imprecision performance of measurement of NT-proBNP in China had improved with the significant decrease of current coefficient of variations [ 44 ]. Finally, although the validation cohort of the present study allowed the CRH score to be externally tested in a population with a distinct age distribution, it had relatively shorter duration of follow up compared with the derivation cohort.…”

Section: Discussionmentioning

confidence: 99%

Assessment of cardio-renal-hepatic function in patients with valvular heart disease: a multi-biomarker approach—the cardio-renal-hepatic score

Zhang

et al. 2023

BMC Med

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Background Valvular heart disease (VHD) can cause damage to extra-cardiac organs, and lead to multi-organ dysfunction. However, little is known about the cardio-renal-hepatic co-dysfunction, as well as its prognostic implications in patients with VHD. The study sought to develop a multi-biomarker index to assess heart, kidney, and liver function in an integrative fashion, and investigate the prognostic role of cardio-renal-hepatic function in VHD. Methods Using a large, contemporary, prospective cohort of 6004 patients with VHD, the study developed a multi-biomarker score for predicting all-cause mortality based on biomarkers reflecting heart, kidney, and liver function (N-terminal pro-B-type natriuretic peptide [NT-proBNP], creatinine, and albumin). The score was externally validated in another contemporary, prospective cohort of 3156 patients with VHD. Results During a median follow up of 731 (704–748) days, 594 (9.9%) deaths occurred. Increasing levels of NT-proBNP, creatinine, and albumin were independently and monotonically associated with mortality, and a weighted multi-biomarker index, named the cardio-renal-hepatic (CRH) score, was developed based on Cox regression coefficients of these biomarkers. The CRH score was a strong and independent predictor of mortality, with 1-point increase carrying over two times of mortality risk (overall adjusted hazard ratio [95% confidence interval]: 2.095 [1.891–2.320], P < 0.001). The score provided complementary prognostic information beyond conventional risk factors (C index: 0.78 vs 0.81; overall net reclassification improvement index [95% confidence interval]: 0.255 [0.204–0.299]; likelihood ratio test P < 0.001), and was identified as the most important predictor of mortality by the proportion of explainable log-likelihood ratio χ2 statistics, the best subset analysis, as well as the random survival forest analysis in most types of VHD. The predictive performance of the score was also demonstrated in patients under conservative treatment, with normal left ventricular systolic function, or with primary VHD. It achieved satisfactory discrimination (C index: 0.78 and 0.72) and calibration in both derivation and validation cohorts. Conclusions A multi-biomarker index was developed to assess cardio-renal-hepatic function in patients with VHD. The cardio-renal-hepatic co-dysfunction is a powerful predictor of mortality and should be considered in clinical management decisions.

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Section: Discussionmentioning

confidence: 99%

Assessment of cardio-renal-hepatic function in patients with valvular heart disease: a multi-biomarker approach—the cardio-renal-hepatic score

Zhang

et al. 2023

BMC Med

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“…13 As per ISO15139, quality indicators are defined as a "measure of the degree to which a set of inherent characteristics fulfil requirements". 15 As one of the quality indicators in the analysis phase, CV was used as an indicator of quality requirement/performance.…”

Section: Discussionmentioning

confidence: 99%

Stringent Internal Quality Control Procedures in Chemical Pathology Lead to Better Performance in External Proficiency Testing

Atzaz

Mehnaz²,

Zuhra³

et al. 2023

JRMC

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Objective: To assess impact of stringent Internal Quality Control (IQC) checks on performance of proficiency testing Material and methods: This was a Prospective study conducted between September 2020 and April 2021 at Chemical pathology lab of Fauji Foundation Hospital Rawalpindi. External quality control data (EQC) from the month of September was evaluated. As part of corrective action plan IQC checks were enforced, internal quality control (IQC) data of the month of September 2020 and April 2022 were assessed. Performance characteristics of routine chemistry analytes coefficient of variance (CV), standard deviations (SD)and Bias were calculated and compared using paired –T- test. Results: Proficiency testing report (NEQAPP) of cycle 10 round 1 showed 11% External Quality Control (EQC) failure among 18 biochemical parameters. Serum Creatinine and Total Protein failed acceptability criteria with Z-score of greater than 2. As part of corrective action IQC checks were done, which led to improvement in CV (SD) of these parameters. The next EQC lab report for routine chemistry analytes met the acceptability criteria with z-scores of all anaytes being less than 2. Conclusion: Precise & accurate IQC results lead to better performance in EQC results

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“…The percentage CV for monitoring the imprecision of measurements reflects the quality of the laboratory analysis phase [22]. In a study of 72 laboratories in China, the findings showed that using the Siemens BNP kits, the median CV ranged from 4.87% (interquartile range [IQR] 2.38) to 5.17% (IQR 3.33) [23].…”

Section: Discussionmentioning

confidence: 99%

Evaluation of Sigma value and quality goal index for brain natriuretic peptide test

Üstündağ¹

2020

Int J Med Biochem

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Evaluation of sigma value and quality goal index for brain natriuretic peptide test T he b-type or brain natriuretic peptide (BNP) is a member of the natriuretic peptide family that is involved in many biological events in the body, including regulation of blood pressure and blood volume [1][2][3]. BNP is mainly synthesized in the cardiac ventricle as proBNP, which is a prohormone consisting of 108 amino acids. ProBNP is cleaved in the circulation as an active hormone 32 amino acid structure that corresponds to the C-terminus of proBNP. The N terminal (NT) 76 amino acid NT-proBNP is an inactive protein. Both BNP and NT-proBNP have a wide range of clinical effects that increase cardiac stress and output [1][2][3]. Measurement of BNP levels to differentiate the causes of acute dyspnoea in patients admitted to the emergency de-partment has high diagnostic accuracy [3,4]. Heart failure (HF) is unlikely when the plasma BNP level is <100 pg/ml, and a level higher than 400 pg/ml is appropriate for ruling in acute HF, which makes it a suitable test for patient identification in emergency care settings [1][2][3][4]. However, recent studies suggested that there are significant differences in analytical performance among commercial methods for BNP immunoassays [5] An erroneous result, in which the difference between a test result and the corresponding true value exceeds the allowable total error (Tea), leads to medically significant errors. To improve patient safety, zero errors should be targeted in health services that cannot be possible in a real laboratory setting [6].Objectives: In this study, we aimed to evaluate the analytical process by determining the sigma values and quality goal index (QGI) of the brain natriuretic peptide (BNP) test parameter performed in our emergency laboratory. Methods: BNP levels were tested using a commercially available immunoassay autoanalyser (Advia Centaur XP; Siemens Healthcare Diagnostic Ltd., Muenchen, Germany). Bias was calculated by comparison with the group mean for each external quality assessment report, and an internal quality control-based approach was applied. The internal quality control results of the BNP test levels between September and December 2018 and external quality program reports were used in the coefficient of variation (CV) and bias calculations. The sigma metrics and QGI were calculated. Results: The sigma metric calculated from the external quality control was 2.1 and the QGI was 0.34. In the internal quality control study, the sigma level was 1.92, and the QGI was 0.55, as calculated at the 400 pg/ml level. The QGI level suggests that the problem in the BNP study was imprecision. Conclusion: Unsatisfactory sigma levels for BNP tests were achieved using both methods of calculating sigma metrics.

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Internal quality control status for BNP and NT‐proBNP in China from 2014 to 2017

Cited by 6 publications

References 24 publications

Assessment of cardio-renal-hepatic function in patients with valvular heart disease: a multi-biomarker approach—the cardio-renal-hepatic score

Assessment of cardio-renal-hepatic function in patients with valvular heart disease: a multi-biomarker approach—the cardio-renal-hepatic score

Stringent Internal Quality Control Procedures in Chemical Pathology Lead to Better Performance in External Proficiency Testing

Evaluation of Sigma value and quality goal index for brain natriuretic peptide test

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