Limits...
History of falls, gait, balance, and fall risks in older cancer survivors living in the community.

Huang MH, Shilling T, Miller KA, Smith K, LaVictoire K - Clin Interv Aging (2015)

Bottom Line: During follow-up, 59% of participants had one or more falls.Forward logistic regression revealed that a history of falls was a significant predictor of falls in the final model (odds ratio =6.81; 95% confidence interval =1.594-29.074) (P<0.05).Sensitivity and specificity for correctly identifying a faller using the positive history of falls were 74% and 69%, respectively.

View Article: PubMed Central - PubMed

Affiliation: Physical Therapy Department, School of Health Professions and Studies, University of Michigan-Flint, Flint, MI, USA.

ABSTRACT
Older cancer survivors may be predisposed to falls because cancer-related sequelae affect virtually all body systems. The use of a history of falls, gait speed, and balance tests to assess fall risks remains to be investigated in this population. This study examined the relationship of previous falls, gait, and balance with falls in community-dwelling older cancer survivors. At the baseline, demographics, health information, and the history of falls in the past year were obtained through interviewing. Participants performed tests including gait speed, Balance Evaluation Systems Test, and short-version of Activities-specific Balance Confidence scale. Falls were tracked by mailing of monthly reports for 6 months. A "faller" was a person with ≥1 fall during follow-up. Univariate analyses, including independent sample t-tests and Fisher's exact tests, compared baseline demographics, gait speed, and balance between fallers and non-fallers. For univariate analyses, Bonferroni correction was applied for multiple comparisons. Baseline variables with P<0.15 were included in a forward logistic regression model to identify factors predictive of falls with age as covariate. Sensitivity and specificity of each predictor of falls in the model were calculated. Significance level for the regression analysis was P<0.05. During follow-up, 59% of participants had one or more falls. Baseline demographics, health information, history of falls, gaits speed, and balance tests did not differ significantly between fallers and non-fallers. Forward logistic regression revealed that a history of falls was a significant predictor of falls in the final model (odds ratio =6.81; 95% confidence interval =1.594-29.074) (P<0.05). Sensitivity and specificity for correctly identifying a faller using the positive history of falls were 74% and 69%, respectively. Current findings suggested that for community-dwelling older cancer survivors with mixed diagnoses, asking about the history of falls may help detect individuals at risk of falling.

No MeSH data available.


Related in: MedlinePlus

Mean (± 1 standard deviation) of the Balance Evaluation Systems Test (BESTest) total score and the sub-scores of the six domains of BESTest in fallers and non-fallers.Notes: BESTest domains: I, biomechanical constraints; II, stability limits; III, anticipatory postural adjustments; IV, reactive postural response; V, sensory orientation; VI, stability in gait. Scores are as percentages (0%–100%) of the maximum points possible within the entire BESTest for the BESTest total score and within each domain for the BESTest sub-scores.
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f1-cia-10-1497: Mean (± 1 standard deviation) of the Balance Evaluation Systems Test (BESTest) total score and the sub-scores of the six domains of BESTest in fallers and non-fallers.Notes: BESTest domains: I, biomechanical constraints; II, stability limits; III, anticipatory postural adjustments; IV, reactive postural response; V, sensory orientation; VI, stability in gait. Scores are as percentages (0%–100%) of the maximum points possible within the entire BESTest for the BESTest total score and within each domain for the BESTest sub-scores.

Mentions: At baseline, fallers (1.00±0.241 m/s) and non-fallers (1.02±0.168 m/s) did not differ significantly in gait speeds. BESTest total scores did not differ between fallers (83.3%±7.65%) and non-fallers (82.6%±9.35%) (Figure 1). The sub-score of the sensory orientation domain of BESTest was not significantly different between fallers (86.9%±12.47%) and non-fallers (93.8%±5.69%) (P=0.02). No significant differences between groups were found in other BESTest domains (Figure 1). Fallers (73.7%±15.90%) and non-fallers (74.1%±20.66%) did not differ significantly in scores of ABC-6.


History of falls, gait, balance, and fall risks in older cancer survivors living in the community.

Huang MH, Shilling T, Miller KA, Smith K, LaVictoire K - Clin Interv Aging (2015)

Mean (± 1 standard deviation) of the Balance Evaluation Systems Test (BESTest) total score and the sub-scores of the six domains of BESTest in fallers and non-fallers.Notes: BESTest domains: I, biomechanical constraints; II, stability limits; III, anticipatory postural adjustments; IV, reactive postural response; V, sensory orientation; VI, stability in gait. Scores are as percentages (0%–100%) of the maximum points possible within the entire BESTest for the BESTest total score and within each domain for the BESTest sub-scores.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4581777&req=5

f1-cia-10-1497: Mean (± 1 standard deviation) of the Balance Evaluation Systems Test (BESTest) total score and the sub-scores of the six domains of BESTest in fallers and non-fallers.Notes: BESTest domains: I, biomechanical constraints; II, stability limits; III, anticipatory postural adjustments; IV, reactive postural response; V, sensory orientation; VI, stability in gait. Scores are as percentages (0%–100%) of the maximum points possible within the entire BESTest for the BESTest total score and within each domain for the BESTest sub-scores.
Mentions: At baseline, fallers (1.00±0.241 m/s) and non-fallers (1.02±0.168 m/s) did not differ significantly in gait speeds. BESTest total scores did not differ between fallers (83.3%±7.65%) and non-fallers (82.6%±9.35%) (Figure 1). The sub-score of the sensory orientation domain of BESTest was not significantly different between fallers (86.9%±12.47%) and non-fallers (93.8%±5.69%) (P=0.02). No significant differences between groups were found in other BESTest domains (Figure 1). Fallers (73.7%±15.90%) and non-fallers (74.1%±20.66%) did not differ significantly in scores of ABC-6.

Bottom Line: During follow-up, 59% of participants had one or more falls.Forward logistic regression revealed that a history of falls was a significant predictor of falls in the final model (odds ratio =6.81; 95% confidence interval =1.594-29.074) (P<0.05).Sensitivity and specificity for correctly identifying a faller using the positive history of falls were 74% and 69%, respectively.

View Article: PubMed Central - PubMed

Affiliation: Physical Therapy Department, School of Health Professions and Studies, University of Michigan-Flint, Flint, MI, USA.

ABSTRACT
Older cancer survivors may be predisposed to falls because cancer-related sequelae affect virtually all body systems. The use of a history of falls, gait speed, and balance tests to assess fall risks remains to be investigated in this population. This study examined the relationship of previous falls, gait, and balance with falls in community-dwelling older cancer survivors. At the baseline, demographics, health information, and the history of falls in the past year were obtained through interviewing. Participants performed tests including gait speed, Balance Evaluation Systems Test, and short-version of Activities-specific Balance Confidence scale. Falls were tracked by mailing of monthly reports for 6 months. A "faller" was a person with ≥1 fall during follow-up. Univariate analyses, including independent sample t-tests and Fisher's exact tests, compared baseline demographics, gait speed, and balance between fallers and non-fallers. For univariate analyses, Bonferroni correction was applied for multiple comparisons. Baseline variables with P<0.15 were included in a forward logistic regression model to identify factors predictive of falls with age as covariate. Sensitivity and specificity of each predictor of falls in the model were calculated. Significance level for the regression analysis was P<0.05. During follow-up, 59% of participants had one or more falls. Baseline demographics, health information, history of falls, gaits speed, and balance tests did not differ significantly between fallers and non-fallers. Forward logistic regression revealed that a history of falls was a significant predictor of falls in the final model (odds ratio =6.81; 95% confidence interval =1.594-29.074) (P<0.05). Sensitivity and specificity for correctly identifying a faller using the positive history of falls were 74% and 69%, respectively. Current findings suggested that for community-dwelling older cancer survivors with mixed diagnoses, asking about the history of falls may help detect individuals at risk of falling.

No MeSH data available.


Related in: MedlinePlus