Kazmi Syed, Kambhampati Chandrasekhar, Rigby Alan S, Cleland John G F, Kazmi Khurram S, Cuthbert Joe, Pellicori Pierpaolo, Clark Andrew L
Department of Academic Cardiology, Hull University Teaching Hospital NHS Trust, Castle Hill Hospital, Hull, UK.
Department of Computer Science and Technology, University of Hull, Hull, UK.
Eur J Heart Fail. 2025 May;27(5):881-888. doi: 10.1002/ejhf.3400. Epub 2024 Aug 6.
Understanding the pattern of disease progression in chronic heart failure (HF) may inform patient care and healthcare system design. We used a four-state Markov model to describe the disease trajectory of patients with HF.
Consecutive patients (n = 4918) were enrolled (median age 75 [67-81] years, 61.3% men, 44% with HF and reduced ejection fraction). We generated a model by observing events during the first 2 years of follow-up. The model yielded surprisingly accurate predictions of how a population with HF will behave during subsequent years. As examples, the predicted transition probability from hospitalization to death was 0.11; the observed probabilities were 0.13, 0.14, and 0.16 at 3, 4, and 5 years, respectively. Similarly, the predicted transition intensity for rehospitalization was 0.35; the observed probabilities were 0.38, 0.34, and 0.35 at 3, 4, and 5 years, respectively. A multivariable model including covariates thought to influence outcome did not improve accuracy. Predicted average life expectancy was approximately 10 years for the unadjusted model and 13 years for the multivariable model, consistent with the observed mortality of 41% at 5 years.
A multistate Markov chain model for patients with chronic HF suggests that the proportion of patients transitioning each year from a given state to another remains constant. This finding suggests that the course of HF at a population level is more linear than is commonly supposed and predictable based on current patient status.
了解慢性心力衰竭（HF）的疾病进展模式可为患者护理和医疗系统设计提供依据。我们使用四状态马尔可夫模型来描述HF患者的疾病轨迹。
连续纳入4918例患者（中位年龄75[67 - 81]岁，男性占61.3%，44%的患者HF伴射血分数降低）。我们通过观察随访前2年的事件生成了一个模型。该模型对HF人群在后续几年的行为表现做出了惊人准确的预测。例如，从住院到死亡的预测转移概率为0.11；在3年、4年和5年时观察到的概率分别为0.13、0.14和0.16。同样，再次住院的预测转移强度为0.35；在3年、4年和5年时观察到的概率分别为0.38、0.34和0.35。包含被认为会影响结局的协变量的多变量模型并未提高预测准确性。未调整模型的预测平均预期寿命约为10年，多变量模型为13年，与5年时41%的观察到的死亡率一致。
慢性HF患者的多状态马尔可夫链模型表明，每年从给定状态转变为另一种状态的患者比例保持不变。这一发现表明，在人群水平上，HF的病程比通常认为的更具线性，并且可根据当前患者状态进行预测。
