Longitudinal study on the trajectory and influencing factors of cognitive dysfunction in lung transplantation patients
Bibliographic record
Abstract
INTRODUCTION: Lung transplantation is an effective method for treating end-stage lung disease. It prolongs the survival time of patients, improves the quality of life, and prevents the degree of mental disability. In particular, postoperative cognitive dysfunction (POCD) is one of the complications after lung transplantation. Despite this, longitudinal studies on the identification and heterogeneity of cognitive dysfunction subgroup trajectories in transplant patients are lacking. Therefore, our study aimed to evaluate the factors that influence POCD in lung transplant patients. METHODS: This prospective longitudinal study included patients who underwent lung transplantation at the transplant center of Wuxi People's Hospital from September 2022 to September 2023. Patients with lung transplants were evaluated at 8 days (T1), 1 month (T2), 3 months (T3), and 6 months (T4) after the operation. The general information questionnaire evaluated cognitive functions using the Montreal Cognitive Assessment (MoCA) numerical rating scale (NRS) and the digital pain assessment to obtain the POCD values. Latent category growth model (LCGM) analysis was used to identify heterogeneous POCD subgroups in the four observation periods. Univariate and logistic regression analyses were used to identify factors affecting POCD classification and independent risk factors. RESULTS: Based on clinical outcomes, 79 patients completed all four surveys, of whom 16 were lost during the follow-up period (loss rate, 16.8%). The cognitive function by MoCA NRS score was 14.18 ± 5.32 points on day 8 (T1), 22.51 ± 5.13 points at 1 month (T2), 25.44 ± 3.61 at 3 months (T3), and 27.04 ± 3.03 points at 6 months (T4) after lung transplantation, showing an increasing trend. The LCGM, used to fit the trajectory of MoCA scores, observed a heterogeneous trajectory of changes in lung transplant patients. Based on this analysis, patients could be divided into two categories: those with high risk (25,32%) and those with low risk (54,68%). The single-factor analysis identified that POCD values were affected by early postoperative rehabilitation exercise, degree of pain, intensive care unit (ICU) stay time, and donor lung cold ischemia time (all P < 0.05). Using the low-risk group as the reference class, logistic regression analysis showed that the model could correctly classify the subjects. CONCLUSION: Our 6-month observation of lung transplant patients showed that the degree of cognitive dysfunction had an overall downward trend and that patients could be divided into two trajectories of high and low risk for POCD. Early postoperative rehabilitation exercise, degree of pain, ICU stay time, and donor lung cold ischemia time were all influencing factors for POCD in lung transplant patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".