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首页> 外文期刊>Clinical chemistry and laboratory medicine: CCLM >The diagnostic utility of brain natriuretic peptide in heart failure patients presenting with acute dyspnea: A meta-analysis
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The diagnostic utility of brain natriuretic peptide in heart failure patients presenting with acute dyspnea: A meta-analysis

机译:脑钠素在心力衰竭患者急性呼吸困难中的诊断价值:荟萃分析

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Heart failure with normal ejection fraction (HFNEF) accounts for approximately 50% of heart failure (HF) cases. To establish the utility of brain natriuretic peptide (BNP) in differentiating HF-related severe dyspnea from non-HF-related acute dyspnea, we used an estimation formula (eF) that was obtained from a series of three meta-regressions. We selected 60 out of 2721 case-control and follow-up studies that were published from 1998 to 2010. The heart failure levels (HFLs) were assessed using the New York Heart Association (NYHA) criteria. Random-effects meta-regression analyses of the natural logarithm (ln) of the BNP odds ratio (OR) were performed on the HFLs. The ln of the median BNP values (lnmBNP) was meta-regressed over the laboratory method (LM). A third meta-regression was performed on the HFLs to account for only the lnmBNP in the homogeneous LM subgroups. To determine the eF, the data from the diseased and control subjects were combined. The Bland-Altman method was used to detect eF bias. The overall BNP(OR) in the subgroup with severe HF was 35. The lnmBNP analysis showed that LM was a significant heterogeneity factor in the meta-regression (slope - 0.38; CI - 0.59 to - 0.16). The meta-regression of lnmBNP on the HFL resulted in the following calculation for eF: estimated HFL (eHFL) = (lnmBNP-3.157)/0.886. The Bland-Altman test revealed no significant difference (0.0997; 95% CI - 2.84 to 3.06) between HFL and eHFL. The severe eHFL showed a 78% accuracy. Based on the eF obtained from this meta-analysis, the BNP outcomes were shown to reliably diagnose severe dyspnea in HF and differentiate this condition from non-HF acute dyspnea.
机译:正常射血分数(HFNEF)的心力衰竭约占心力衰竭(HF)病例的50%。为了建立脑利钠肽(BNP)在区分HF相关的严重呼吸困难和非HF相关的急性呼吸困难中的作用,我们使用了从一系列三个元回归获得的估计公式(eF)。我们从1998年至2010年发表的2721例病例对照和随访研究中,选择了60例。使用纽约心脏协会(NYHA)的标准评估了心力衰竭水平(HFL)。对HFL进行了BNP比值比(OR)的自然对数(ln)的随机效应荟萃回归分析。 BNP中值(lnmBNP)的ln通过实验室方法(LM)进行了元回归。对HFL进行了第三次元回归,以仅解释同质LM亚组中的lnmBNP。为了确定eF,将来自患病和对照受试者的数据进行组合。 Bland-Altman方法用于检测eF偏倚。重度心力衰竭亚组的总BNP(OR)为35。lnmBNP分析表明,LM是荟萃回归的重要异质性因子(斜率-0.38; CI-0.59至-0.16)。 lnmBNP在HFL上的元回归导致对eF进行以下计算:估计HFL(eHFL)=(1nmBNP-3.157)/0.886。 Bland-Altman测试显示HFL和eHFL之间无显着差异(0.0997; 95%CI-2.84至3.06)。严重的eHFL显示出78%的准确性。根据从这项荟萃分析获得的eF,BNP结果显示出可以可靠地诊断HF的严重呼吸困难,并将这种情况与非HF急性呼吸困难区分开。

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