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炎症负担指数:骨关节炎患者中骨关节炎与全因死亡率的关系。

Inflammatory burden index: associations between osteoarthritis and all-cause mortality among individuals with osteoarthritis.

机构信息

Departments of Bone and Joint Surgery, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, PR China.

Department of Orthopaedics, Yueyang People's Hospital, No. 263 Baling Road, Yueyang, 414000, Hunan, PR China.

出版信息

BMC Public Health. 2024 Aug 13;24(1):2203. doi: 10.1186/s12889-024-19632-1.

DOI:10.1186/s12889-024-19632-1
PMID:39138465
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11323649/
Abstract

BACKGROUND

The newly described inflammatory burden index (IBI) reflects a patient's inflammatory burden. This study aimed to estimate the association between IBI, osteoarthritis (OA), and all-cause mortality in patients with OA.

METHODS

We extracted the data of adults from the National Health and Nutrition Examination Survey database between 1999 and 2018. After using appropriate survey weights to correct for sample bias, we conducted multivariate logistic regression analyses to explore the association between IBI and OA across three models: in the unadjusted model, partially adjusted model (adjusting age, sex, race, education level, marital status, PIR, BMI, smoking status, drinking status, stroke, CVD, DM, and hypertension) and fully adjusted model (which included additional variables: HBA1C, ALT, AST, BUN, TC, and HDL). And the odds ratios (OR) and 95% confidence intervals (CI) were calculated. Similarly, using comparable survey weights and covariates adjustments, we employed Cox proportional hazards regression analysis to investigate the association between IBI and all-cause mortality in the other 3 models. The Cox proportional hazards regression models were fitted to calculate the hazard ratios (HR) and 95% CI of the association between IBI and all-cause mortality. A restricted cubic spline (RCS) was used to explore the nonlinear relationships between association effects. Subgroup analysis was performed to validate the reliability of their effects.

RESULTS

In total, 22,343 eligible participants were included. Multiple logistic regression models revealed that participants with the highest IBI had 2.54 times (95%CI, 2.23, 2.90)) higher risk of OA than those with the lowest IBI in Model 1, whereas the OR was 1.21 (95%CI, 1.03, 1.42) in Model 2 and 1.23 (95%CI,1.05, 1.45) in Model 3. Multiple Cox regression models showed participants with the highest IBI had 186% (95%CI, 1.50, 2.31) times risk of developing all-cause death than those with the lowest IBI in Model 1. This trend remained stable in Models 2 (HR,1.54; 95%CI,1.22, 1.95) and 3 (HR, 1.41; 95%CI, 1.10, 1.80). The RCS revealed a significant positive association between IBI and OA risk. With respect to the association between IBI and all-cause mortality, a slight decrease in mortality was observed from the lowest quartile to the second quartile of IBI, and the mortality risk increased with increasing IBI. Subgroup analyses showed that age, cardiovascular disease, and hypertension were pivotal in the association of IBI with all-cause mortality, whereas the association of IBI with OA remained stable after stratification by other factors such as sex, race, education level, marital, smoking, and drinking status, hypertension, and most serological indices.

CONCLUSIONS

This study provides evidence of a positive association between IBI, OA, and all-cause mortality. IBI may be a promising signature for assessing the inflammatory burden in patients with OA, which, in turn, is conducive to precise references for high-risk population recognition, anti-inflammatory guidance, and reducing mortality intervention.

摘要

背景

新描述的炎症负担指数(IBI)反映了患者的炎症负担。本研究旨在评估 IBI 与骨关节炎(OA)和 OA 患者全因死亡率之间的关系。

方法

我们从 1999 年至 2018 年的国家健康和营养检查调查数据库中提取了成年人的数据。在使用适当的调查权重校正样本偏差后,我们进行了多变量逻辑回归分析,以在三个模型中探讨 IBI 与 OA 之间的关联:未调整模型(调整年龄、性别、种族、教育水平、婚姻状况、PIR、BMI、吸烟状况、饮酒状况、中风、CVD、DM 和高血压)、部分调整模型(包括 HBA1C、ALT、AST、BUN、TC 和 HDL 等其他变量)和完全调整模型。并计算了比值比(OR)和 95%置信区间(CI)。同样,使用可比的调查权重和协变量调整,我们在其他 3 个模型中使用 Cox 比例风险回归分析研究了 IBI 与全因死亡率之间的关联。使用 Cox 比例风险回归模型计算了 IBI 与全因死亡率之间关联的风险比(HR)和 95%CI。限制性立方样条(RCS)用于探索关联效应的非线性关系。进行亚组分析以验证其效果的可靠性。

结果

共纳入 22343 名符合条件的参与者。多因素逻辑回归模型显示,在模型 1 中,IBI 最高的参与者患 OA 的风险比 IBI 最低的参与者高 2.54 倍(95%CI,2.23,2.90),而在模型 2 中 OR 为 1.21(95%CI,1.03,1.42),在模型 3 中为 1.23(95%CI,1.05,1.45)。多因素 Cox 回归模型显示,在模型 1 中,IBI 最高的参与者发生全因死亡的风险比 IBI 最低的参与者高 186%(95%CI,1.50,2.31)。这一趋势在模型 2(HR,1.54;95%CI,1.22,1.95)和 3(HR,1.41;95%CI,1.10,1.80)中保持稳定。RCS 显示 IBI 与 OA 风险之间存在显著的正相关。关于 IBI 与全因死亡率之间的关系,从 IBI 的最低四分位数到第二四分位数,死亡率略有下降,随着 IBI 的增加,死亡率风险增加。亚组分析表明,年龄、心血管疾病和高血压是 IBI 与全因死亡率关联的关键因素,而 IBI 与 OA 的关联在按性别、种族、教育水平、婚姻状况、吸烟和饮酒状况、高血压和大多数血清学指标等其他因素分层后仍然稳定。

结论

本研究提供了 IBI、OA 和全因死亡率之间存在正相关的证据。IBI 可能是评估 OA 患者炎症负担的有前途的标志物,这有助于对高危人群的识别、抗炎指导和降低死亡率干预提供更精确的参考。

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