# Identifying subphenotypes of patients undergoing post‐operative delirium assessment

**Authors:** Emily Margaret Louise Bowman, Daniel F. McAuley, Bernadette McGuinness, Anthony P. Passmore, David Beverland, Henrik Zetterberg, Jonathan M. Schott, Amanda Heslegrave, Elena Veleva, Rhiannon Laban, Aoife Sweeney, Emma L. Cunningham

PMC · DOI: 10.1002/alz.70516 · Alzheimer's & Dementia · 2025-07-16

## TL;DR

This study identifies two distinct subphenotypes of patients with delirium after surgery, differing in age, education, depression, pain, and biomarkers of brain damage.

## Contribution

The study introduces a novel subphenotyping framework for post-operative delirium using clinical and biomarker data.

## Key findings

- Two subphenotypes of delirium patients were identified via latent class analysis.
- Class 1 showed worse cognitive function and higher CNS damage biomarkers.
- Class 2 had higher pain levels and morphine use.

## Abstract

Delirium has heterogeneous etiologies and clinical presentations and is often associated with poor outcomes. Its pathophysiological mechanisms remain largely hypothetical and without targeted pharmacological treatment. This work investigates subphenotypes of patients undergoing delirium assessment based on clinical features and fluid biomarkers.

We performed latent class analysis of an observational cohort of older adults undergoing elective surgery.

Two classes were identified, both containing individuals experiencing delirium symptoms, with a higher number in Class 1 (p < 0.001). Class 1 were older, less educated, and had more depression (p < 0.001). They performed worse in all pre‐operative cognitive assessments (p < 0.001) and had more markers of central nervous system damage: cerebrospinal fluid glial fibrillary acidic protein, neurofilament light chain, and soluble triggering receptor expressed on myeloid cells 2 (p < 0.001); plasma phosphorylated tau (p = 0.024); and amyloid beta 42/40 ratio (p < 0.001). Class 2 experienced more pain (p = 0.006) and received more morphine equivalents (p = 0.018).

Delirium and neighboring phenotypes should be investigated thoroughly in the newly dawning era of precision medicine, to establish novel treatments.

Latent class analysis identified two subphenotypes of patients.Both groups contained patients with delirium or its individual symptoms.Groups differed by age, education, depression, independent living, and pain levels.Groups differed by pre‐operative and post‐operative cognition.Groups differed by biomarker levels of neurodegeneration and neuronal injury.

Latent class analysis identified two subphenotypes of patients.

Both groups contained patients with delirium or its individual symptoms.

Groups differed by age, education, depression, independent living, and pain levels.

Groups differed by pre‐operative and post‐operative cognition.

Groups differed by biomarker levels of neurodegeneration and neuronal injury.

In post‐operative patients undergoing delirium assessment, two latent classes were identified, both containing people experiencing delirium symptoms, but with higher proportion in Class 1. Class 1 were also older, less educated and had more depression. They performed worse in all preoperative cognitive assessments and had more markers of CNS damage. Class 2 experienced more pain and received more morphine equivalents.

## Linked entities

- **Diseases:** delirium (MONDO:0045057)

## Full-text entities

- **Genes:** MAPT (microtubule associated protein tau) [NCBI Gene 4137] {aka DDPAC, FTD1, FTDP-17, MAPTL, MSTD, MTBT1}, TREM2 (triggering receptor expressed on myeloid cells 2) [NCBI Gene 54209] {aka AD17, PLOSL2, TREM-2, Trem2a, Trem2b, Trem2c}, GFAP (glial fibrillary acidic protein) [NCBI Gene 2670] {aka ALXDRD}
- **Diseases:** pain (MESH:D010146), Delirium (MESH:D003693), neurodegeneration (MESH:D019636), central nervous system damage (MESH:D002493), neuronal injury (MESH:D009410), depression (MESH:D003866)
- **Chemicals:** morphine (MESH:D009020)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12265012/full.md

## References

39 references — full list in the complete paper: https://tomesphere.com/paper/PMC12265012/full.md

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Source: https://tomesphere.com/paper/PMC12265012