Early intervention to restore function and maintain healthy trajectory

Comparing a new multimorbidity index with other multimorbidity measures for predicting disability trajectories

BACKGROUND

The optimal multimorbidity measures for predicting disability trajectories are not universally agreed upon. We developed a multimorbidity index among middle-aged and older community-dwelling Chinese adults and compare its predictive ability of disability trajectories with other multimorbidity measures.

METHODS

This study included 17,649 participants aged ≥50 years from the China Health and Retirement Longitudinal Survey 2011-2018. Two disability trajectory groups were estimated using the total disability score differences calculated between each follow-up visit and baseline. A weighted index was constructed using logistic regression models for disability trajectories based on the training set (70 %). The index and the condition count were used, along with the pattern identified by the latent class analysis to measure multimorbidity at baseline. Logistic regression models were used in the training set to examine associations between each multimorbidity measure and disability trajectories. C-statistics, integrated discrimination improvements, and net reclassification indices were applied to compare the performance of different multimorbidity measures in predicting disability trajectories in the testing set (30 %).

RESULTS

In the newly developed multimorbidity index, the weights of the chronic conditions varied from 1.04 to 2.55. The multimorbidity index had a higher predictive performance than the condition count. The condition count performed better than the multimorbidity pattern in predicting disability trajectories.

LIMITATION

Self-reported chronic conditions.

CONCLUSIONS

The multimorbidity index may be considered an ideal measurement in predicting disability trajectories among middle-aged and older community-dwelling Chinese adults. The condition count is also suggested due to its simplicity and superior predictive performance.

Personal Factors Associated With Postconcussion Symptoms 3 Months After Mild Traumatic Brain Injury

OBJECTIVE

To describe personal factors in patients with mild traumatic brain injury (MTBI) and 2 control groups and to explore how such factors were associated with postconcussion symptoms (PCSs).

DESIGN

Prospective cohort study.

SETTING

Level 1 trauma center and outpatient clinic.

PARTICIPANTS

Participants (N=541) included patients with MTBI (n=378), trauma controls (n=82), and community controls (n=81).

MAIN OUTCOME MEASURES

Data on preinjury health and work status, personality, resilience, attention deficit/hyperactivity, and substance use. Computed tomography (CT) findings and posttraumatic amnesia were recorded. Symptoms were assessed at 3 months with the British Columbia Postconcussion Symptom Inventory and labeled as PCS+ if ≥3 symptoms were reported or the total score was ≥13. Predictive models were fitted with penalized logistic regression using the least absolute shrinkage and selection operator (lasso) in the MTBI group, and model fit was assessed with optimism-corrected area under the curve (AUC) of the receiver operating characteristic curve.

RESULTS

There were few differences in personal factors between the MTBI group and the 2 control groups without MTBI. Rates of PCS+ were 20.8% for the MTBI group, 8.0% for trauma controls, and 1.3% for community controls. In the MTBI group, there were differences between the PCS+ and PCS- group on most personal factors and injury-related variables in univariable comparisons. In the lasso models, the optimism-corrected AUC for the full model was 0.79, 0.73 for the model only including personal factors, and 0.63 for the model only including injury variables. Working less than full time before injury, having preinjury pain and poor sleep quality, and being female were among the selected predictors, but also resilience and some personality traits contributed in the model. Intracranial abnormalities on CT were also a risk factor for PCS.

CONCLUSIONS

Personal factors convey important prognostic information in patients with MTBI. A vulnerable work status and preinjury health problems might indicate a need for follow-up and targeted interventions.

Effects of starting position, distance and ending point in a walking speed test among older adults

AIMS

This study examined the effects of the starting position, distance and ending point on walking speed in older adults with both the usual and maximum walking speeds.

METHODS

In total, 101 older community-dwellers aged between 60 and 74 years were included in this cross-sectional study. Participants were instructed to walk two distances (i.e., 10 and 25 m) at usual and maximum speeds twice. The paired t-test was used to examine the effects of starting positions (static start vs. dynamic start) and ending points (known vs. unknown ending point) on walking speed. Analysis of variance was used to explore walking speed differences among 4, 6, 8, 10, 15, 20 and 25 m walking tests.

RESULTS

Differences in walking speed between static start and dynamic start became larger with a decrease in the walking distance (Cohen's d: 4 m > 6 m > 10 m), and differences were larger in tests at the maximum walking speed (Cohen's d = 0.28-0.85) compared with those at usual walking speed (Cohen's d = 0.21-0.67). The walking speed increased with distance, but no significant changes were found among 10, 15, 20 and 25 m tests at the usual speed. Trivial speed differences were observed in walking speed between known (mean = 1.23-1.82 m/s) and unknown ending points (mean = 1.27-1.86 m/s; Cohen's d < 0.20).

CONCLUSIONS

Test parameters, particularly the starting position and walk distance, do influence walking speed measured in the short-distance walking speed test among older adults. Geriatr Gerontol Int ••; ••: ••-•• Geriatr Gerontol Int 2020; ••: ••-••.