Four distinct nursing dependency trajectories were identified in AMI patients, with age, marital status, depressive and anxiety symptoms, social support, and history of underlying diseases showing independent class-specific associations with trajectory membership.
Key Findings
Results
Four distinct latent classes of nursing dependency trajectories were identified in patients with acute myocardial infarction using growth mixture modeling.
The four trajectory classes were: High Independence-Slow Improvement Type (C1), Moderate Dependency-Rapid Deterioration Type (C2), High Dependency-Significant Improvement Type (C3), and High Dependency-Slow Aggravation Type (C4).
The study included 260 AMI patients admitted to Linquan County People's Hospital between January 2024 and January 2026.
Nursing dependency was assessed at four time points: baseline after emergency treatment (T1), day 3 after admission (T2), discharge (T3), and 1 month after discharge (T4).
The Care Dependency Scale (CDS) was used as the measurement instrument across all four time points.
Results
The largest trajectory class was High Dependency-Significant Improvement Type, comprising approximately one-third of patients.
C3 (High Dependency-Significant Improvement Type) included 90 patients, representing 34.6% of the sample.
C1 (High Independence-Slow Improvement Type) included 66 patients (25.4%).
C2 (Moderate Dependency-Rapid Deterioration Type) included 54 patients (20.8%).
C4 (High Dependency-Slow Aggravation Type) included 50 patients (19.2%).
Results
Substantial interindividual heterogeneity in nursing dependency trajectories was observed among AMI patients.
The study identified four distinct longitudinal trajectory patterns rather than a single uniform trajectory, demonstrating heterogeneity in recovery patterns.
Trajectory classes ranged from high independence with slow improvement to high dependency with slow aggravation.
Both improving and deteriorating trajectories were identified, suggesting divergent clinical courses among AMI patients.
Growth mixture modeling was the statistical approach used to capture this heterogeneity.
Results
Age, marital status, depressive symptoms, anxiety symptoms, social support, and history of underlying diseases were independently associated with trajectory-class membership.
Multinomial logistic regression was used to identify factors independently associated with trajectory-class membership.
These factors showed 'independent class-specific associations with trajectory membership,' suggesting differential effects across trajectory classes.
Both clinical characteristics (age, history of underlying diseases) and psychosocial characteristics (depressive symptoms, anxiety symptoms, social support, marital status) were identified as associated factors.
The study assessed these as clinical and psychosocial characteristics evaluated subsequent to trajectory identification.
Methods
This was a single-center longitudinal observational study with the baseline defined as the time point after successful emergency treatment and recovery of consciousness.
The study was conducted at Linquan County People's Hospital.
The enrollment period spanned January 2024 to January 2026.
The total sample size was 260 AMI patients.
The study design was a single-center longitudinal observational study with four assessment time points spanning from hospital admission through one month post-discharge.
Conclusions
The authors concluded that the effectiveness of interventions targeting the identified associated factors requires prospective evaluation.
The study identifies factors that 'may help identify patients requiring closer nursing assessment and individualized follow-up.'
The authors explicitly noted that 'the effectiveness of interventions targeting these factors requires prospective evaluation.'
The observational design of the study limits causal inference about the identified associated factors.
The findings are framed as informing clinical assessment rather than prescribing specific interventions.
What This Means
This research suggests that patients recovering from acute myocardial infarction (heart attack) do not all follow the same path when it comes to how much nursing care they need over time. By studying 260 heart attack patients at four points in time — from shortly after emergency treatment through one month after hospital discharge — researchers identified four distinct groups: patients who started out relatively independent and slowly improved, patients who had moderate dependency but rapidly got worse, patients who started with high dependency but improved significantly, and patients who started with high dependency and slowly continued to worsen. The largest group (about 35% of patients) started highly dependent on nursing care but improved significantly over time.
The research also found that certain characteristics were linked to which group a patient fell into. These included age, whether the patient was married, whether they experienced depression or anxiety, how much social support they had, and whether they had pre-existing health conditions. This suggests that both medical and psychosocial factors play a role in how a heart attack patient's care needs evolve over time.
This research suggests that treating all heart attack patients as if they will follow the same recovery path may miss important differences between individuals. Identifying which trajectory group a patient is likely to belong to — based on their age, mental health status, social circumstances, and medical history — could help healthcare teams provide more targeted monitoring and follow-up care. However, the authors caution that while these factors are associated with different care trajectories, further research would be needed to determine whether interventions aimed at these factors can actually change outcomes.
Ren T, Zhang Y, Wang Y, Du J, He J. (2026). Latent Classes of Nursing Dependency Trajectories and Associated Factors in Patients with Acute Myocardial Infarction.. Journal of visualized experiments : JoVE. https://doi.org/10.3791/73289