Quality of life trajectories following geriatric hip fracture surgery: a growth mixture modelling approach

TL;DR

This study identifies four different quality of life patterns in elderly patients after hip fracture surgery and finds factors that predict these patterns to help guide personalized care.

Contribution

The study introduces a growth mixture modeling approach to identify distinct QoL trajectories and their associated factors after hip fracture surgery.

Findings

Four QoL trajectories were identified, including a consistently high QoL group and a notably decreased QoL group.

Osteosarcopenia and lower pre-fracture QoL predicted the poorest recovery trajectory.

Older age and worse cognition predicted a partially declined then stable trajectory.

Abstract

Hip fractures remain a serious threat, particularly among the elderly. Characterizing longitudinal patterns of quality of life (QoL) is important to understand recovery after hip fracture. Identifying subgroups with similar trajectories can help design tailored rehabilitation strategies. This study aimed to investigate the trajectories of QoL over one year following hip fracture surgery and to identify factors associated with each trajectory class.

This longitudinal study utilized a hip fracture registry database from a single medical center. QoL was assessed using the EuroQoL 5-dimension 3-level (EQ-5D-3L) questionnaire at admission, 6 months, and 1 year following hip fracture surgery. Growth mixture modelling was applied to identify subgroups of patients experiencing different trajectories of QoL. Baseline characteristics were compared between groups, and multivariate multinomial logistic regression was used to examine factors associated with trajectory group membership.

Three hundred and eighty-two patients with hip fracture (mean age 80.2; 71.3% female) experienced four distinct QoL trajectories after surgery that were identified: the consistently high QoL group (60.47%) maintained near-optimal QoL throughout follow-up, the partially declined then stable group (21.99%) showed a moderate drop at 6 months with stabilization by 1 year, the notably decreased QoL group (12.83%) demonstrated a steep and persistent decline, representing the poorest recovery, and the recovered Qol group (4.71%) started with the lowest baseline QoL but showed continuous improvement over one year. Multivariate multinomial regression showed that osteosarcopenia, a lower pre-fracture EQ-5D-3L utility score, and poorer activity of daily living predicted a notably decreased QoL trajectory, while older age and worse cognition predicted a partially declined then stable trajectory. No baseline covariates significantly predicted the recovered trajectory.

Four QoL trajectories within one year following hip fracture surgery in elderly patients were explored. Age, comorbidity burden, musculoskeletal health, cognitive status, baseline QoL, and functional independence were significantly associated with trajectory membership. Routine assessment of these factors can help guide personalized management to help maintain QoL and prevent further decline.

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