心力衰竭是慢性肾脏病(CKD)患者心血管不良结局的常见原因。左心房(LA)特征被认为与心力衰竭的发展有关。然而,洛杉矶的评估很复杂。尽管已经定义了各种参数,没有一个参数可以最好地定义LA函数。先导数据表明左心房体积/机械耦合指数(LACI)可能有用,但CKD数据缺乏。
■本研究的目的是在CKD患者队列中定义LACI,并评估其在评估LA功能和预测心力衰竭方面的价值。
■2021年至2023年在我们医院招募了一批CKD患者。对心力衰竭进行随访。LACI是体积与机械耦合指数,计算为心房收缩时LA体积指数与组织多普勒心肌速度之比。使用Spearman等级相关或Pearson等级相关计算LACI与超声心动图/血流动力学变量之间的相关性。接收器工作特征曲线(ROC)分析用于得出LACI,LVGLS的曲线下面积(AUC),LASr,LASct和LASI用于检测心力衰竭。采用Kaplan-Meier存活曲线比较基于LACI阈值的临床结果。采用多变量逻辑回归分析评估危险因素与LACI升高之间的关系。Cox比例风险回归用于确定心力衰竭的危险因素。
■LACI与NT-proBNP呈正相关,CK-MB,LAVI,E/e'与LASI(r=0.504、0.536、0.856、0.541和0.509,p<0.001);与LASr呈负相关(r=-0.509,p<0.001)。关于心力衰竭的ROC分析,LACI的AUC与LVGLS的AUC相当(0.588vs.509,p=0.464),LASr(0.588vs.0.448,p=0.132),LASct(0.588vs.0.566,p=0.971)和LASI(0.588vs.0.570,p=0.874)。LACI增加的心血管危险因素是年龄,BMI,糖尿病,甘油三酯,LA尺寸,LASr,LASI,E/A,E/e'和EF(p<0.05)。在16个月的中位随访期间(范围,6-28个月),无事件生存曲线显示LACI>5.0组心力衰竭风险较高(对数秩检验:P<0.001).LACI>5.0是心力衰竭的独立预测因子[OR:0.121,95%CI(0.020-0.740),p=0.022]。
■LACI可能被证明是评估CKD患者LA功能的有价值的工具,并可纳入LA的常规评估,用于CKD患者的预后评估和临床决策。
UNASSIGNED: Heart failure is a common cause of adverse cardiovascular outcomes in patients with chronic kidney disease (CKD). Left atrial (LA) characteristics are thought to be involved in the development of heart failure. However, LA assessment is complex. Though a variety of parameters have been defined, there is no single parameter that best defines LA function. Pilot data indicate that left atrial volumetric/mechanical coupling index (LACI) may be useful, but data with CKD are lacking.
UNASSIGNED: The objective of this study was to define LACI in a cohort of patients with CKD and to assess its value in evaluating LA function and predicting heart failure.
UNASSIGNED: A cohort of patients with CKD was enrolled at our hospital between 2021 and 2023. Follow-up was performed for heart failure. LACI is a volumetric to mechanical coupling index, calculated as the ratio of the LA volume index to the tissue-Doppler myocardial velocity at atrial contraction. Spearman\'s rank correlation or Pearson\'s correlation was used to calculate the correlation between LACI and echocardiographic/hemodynamic variables. Receiver operating characteristic curve (ROC) analysis was utilised to derive the area under the curve (AUC) for LACI, LVGLS, LASr, LASct and LASI for the detection of heart failure. Kaplan-Meier survival curves were employed to compare clinical outcomes based on LACI thresholds. A multivariable logistic regression analysis was employed to assess the relationship between risk factors and elevated LACI. Cox proportional hazards regression was used to identify risk factors for heart failure.
UNASSIGNED: LACI showed a positive correlation with NT-proBNP, CK-MB, LAVI, E/e\' and LASI (r = 0.504, 0.536, 0.856, 0.541 and 0.509, p < 0.001); and a negative correlation with LASr (r = -0.509, p < 0.001). On the ROC analysis for the determination of heart failure, the AUC of LACI was comparable to those of LVGLS (0.588 vs. 509, p = 0.464), LASr (0.588 vs. 0.448, p = 0.132), LASct (0.588 vs. 0.566, p = 0.971) and LASI (0.588 vs. 0.570, p = 0.874). The cardiovascular risk factors increased by LACI were age, BMI, diabetes, triglycerides, LA size, LASr, LASI, E/A, E/e\' and EF (p < 0.05). During a median follow-up of 16 months (range, 6-28 months), the event-free survival curves demonstrated a higher risk of heart failure in the group with LACI > 5.0 (log-rank test: P < 0.001). LACI > 5.0 was an independent predictor of heart failure [OR: 0.121, 95% CI (0.020-0.740), p = 0.022].
UNASSIGNED: LACI may prove to be a valuable tool for assessing LA function in patients with CKD, and could be integrated into the routine assessment of LA for the purpose of prognostic assessment and clinical decision-making in patients with CKD.