Development and validation of a prediction model for self-reported mobility decline in community-dwelling older adults

Collins, Gary S.; Garret, Angela; Conway, Oliver; Darton, Francis; Dutton, Susan; Garrett, Angela; Hagan, Daryl; Haywood, Damian; Hewitt, Aimi; Lamb, Sarah E; Marian, Ioana R; Morris, Alana; Nevay, Laura; Nicolson, P.J.; Sanchez‐Santos, Maria T; Bruce, Julie; Slark, Mandy; Vadher, Karan; Ward, Lesley; Watson, Marion; Williamson, Esther; Arden, N K; Barker, Karen; Collins, Gary S.; Fairbank, Jeremy; Fitch, Judith; French, David P.; Griffiths, Frances; Hanson, Zara; Hutchinson, Charles E.; Mallen, Christian; Stavros, Petrou

doi:10.1016/j.jclinepi.2022.09.002

Cited by 5 publications

(5 citation statements)

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“…Prior to conducting multivariate modelling, we will assess the non-linearity between continuous predictors and outcomes using fractional polynomials. This analysis helps determine whether each continuous variable should include quadratic or higher-order terms 23. To identify reliable predictors and address collinearity among independent variables, we will employ the LASSO regression analysis 24.…”

Section: Discussionmentioning

confidence: 99%

“…This analysis helps determine whether each continuous variable should include quadratic or higher-order terms. 23 To identify reliable predictors and address collinearity among independent variables, we will employ the LASSO regression analysis. 24 As the outcome event pertains to myocarditis development in children, we will use multiple logistic regression analyses 18 25–29 to construct an early prediction model for myocarditis.…”

Section: Discussionmentioning

confidence: 99%

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Establishment and validation of a prediction model for myocarditis in Chinese children below 14 years old: a protocol for a retrospective cohort study

Wu,

Ji,

Huang

et al. 2023

BMJ Open

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IntroductionPaediatric myocarditis, a rare inflammatory disease, often presents without clear early symptoms. Although cardiac troponin I levels can aid in diagnosing myocarditis, they are not definitive indicators. Troponin I levels frequently fluctuate within and outside the reference range, potentially causing misinterpretations by clinicians. Although a negative troponin I result is valuable for excluding myocarditis, its specificity is low. Moreover, the clinical diagnosis of paediatric myocarditis is exceptionally challenging, and accurate early-stage diagnosis and treatment pose difficulties. Currently, the Dallas criteria, involving cardiac biopsy, serves as the gold standard for myocarditis diagnosis. However, this method has several drawbacks and is unsuitable for children, resulting in its limited use.Methods and analysisIn this study, we will employ multiple logistic regression analysis to develop a predictive model for early childhood myocarditis. This model will assess the patient’s condition at onset and provide the probability of a myocarditis diagnosis. Model performance will be evaluated for accuracy and calibration, and the results will be presented through receiver operating characteristic (ROC) curves and calibration plots. Clinical decision curve analysis, in conjunction with ROC curve analysis, will be employed to determine the optimal cut-off value and calculate the net clinical benefit value for assessing clinical effectiveness. Finally, internal model validation will be conducted using bootstrapping.Ethics and disseminationApproval from the Clinical Research Ethics Committee of The Third Affiliated Hospital of Wenzhou Medical University has been obtained. The research findings will be disseminated through presentations at scientific conferences and publication in peer-reviewed journals.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Establishment and validation of a prediction model for myocarditis in Chinese children below 14 years old: a protocol for a retrospective cohort study

Wu,

Ji,

Huang

et al. 2023

BMJ Open

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“…The full description of this study 97 is available here: https://doi.org/10.1016/j.jclinepi.2022.09.002…”

Section: Methodsmentioning

confidence: 99%

“…97 36NIHR Journals Library www.journalslibrary.nihr.ac.uk TO DEVELOP A PROGNOSTIC TOOL USING THE OXFORD PAIN ACTIVITY AND LIFESTYLE…”

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confidence: 99%

Improving the understanding and management of back pain in older adults: the BOOST research programme including RCT and OPAL cohort

Williamson,

Sanchez-Santos,

Marian

et al. 2023

Programme Grants Appl Res

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Background Back pain frequently affects older people. Knowledge about back pain in older people and evidence to inform clinical care was lacking, particularly for older people with neurogenic claudication due to spinal stenosis, which is a debilitating condition. Objectives To understand and reduce the burden of back pain on older people by increasing knowledge about back pain in older people and developing evidence-based treatment strategies. Design We completed six work packages. These were not undertaken chronologically as there was overlap between work packages. Work package 1: Refine a physiotherapy intervention for neurogenic claudication. Work package 2: Feasibility of the Oxford Pain Activity and Lifestyle cohort study and Better Outcomes for Older people with Spinal Trouble randomised controlled trial. Work package 3: Development of a prognostic tool to identify when older people are at risk of mobility decline using data from the Oxford Pain Activity and Lifestyle cohort study. Work package 4: A randomised controlled trial of physiotherapy for neurogenic claudication and nested longitudinal qualitative study (Better Outcomes for Older people with Spinal Trouble randomised controlled trial). Work package 5: Predictors of participants’ response to treatment – prespecified subgroup analyses. Work package 6: Implementation planning. Setting Primary care and National Health Service Community and Secondary Care Trusts. Participants Community-dwelling adults over the age of 65 years and registered with primary care practices. Better Outcomes for Older people with Spinal Trouble trial participants reported back and/or leg pain consistent with neurogenic claudication. Interventions The Better Outcomes for Older people with Spinal Trouble programme was a physiotherapy-delivered combined physical and psychological group intervention for older people with neurogenic claudication. The comparator was a physiotherapy assessment and tailored advice (best practice advice). Main outcome measures The primary outcome for the Oxford Pain Activity and Lifestyle prognostic tool was mobility decline based on the EQ-5D-5L Mobility Question. The primary outcome for the Better Outcomes for Older people with Spinal Trouble trial was the Oswestry Disability Index at 12 months. Other outcomes included the Oswestry Disability Index walking item, 6-minute walk test and falls. The economic analyses used the EuroQol EQ-5D-5L to measure quality of life. Results Among Oxford Pain Activity and Lifestyle participants, 34% (1786/5304) reported back pain. A further 19.5% (1035/5304) reported back pain and associated leg pain, with 11.2% (n = 594/5304) reporting symptoms consistent with neurogenic claudication. Participants with back pain had worse quality of life compared to those without back pain and reported more adverse health states such as falls, frailty, low walking confidence and mobility decline. Those with neurogenic claudication were worst affected. At 2 years’ follow-up, among those reporting back pain at baseline, only 23% (489/2100) no longer reported symptoms. Recovery was lowest among participants reporting neurogenic claudication at baseline, with 90% still reporting symptoms. At 2 years’ follow-up, 18.6% of Oxford Pain Activity and Lifestyle participants reported mobility decline. Back pain with/without leg pain was not an independent predictor of mobility decline, but lower limb pain and the report of severe pain were independent predictors. Other predictors included slow walking pace, balance difficulties, low walking confidence, walking ability worse than last year, self-reported general health and comorbidity. In the Better Outcomes for Older people with Spinal Trouble trial, there was no significant difference in Oswestry Disability Index scores between treatment groups at 12 months (adjusted mean difference −1.4, 95% confidence interval −4.03 to 1.17), but at 6 months, scores favoured the Better Outcomes for Older people with Spinal Trouble programme (adjusted mean difference −3.7, 95% confidence interval −6.27 to −1.06). The Better Outcomes for Older people with Spinal Trouble programme resulted in greater improvements in the 6-minute walk test (mean difference 21.7 m, 95% confidence interval 5.96 to 37.38 m) and walking item (mean difference −0.2, 95% confidence interval −0.45 to −0.01) and reduced falls risk (odds ratio 0.6, 95% confidence interval 0.40 to 0.98) compared to best practice advice at 12 months. The probability that the Better Outcomes for Older people with Spinal Trouble programme is cost-effective ranged between 67% and 83% (National Health Service and Personal Social Services perspective) and between 79% and 89% (societal perspective) across cost-effectiveness thresholds between £15,000 and £30,000 per quality-adjusted life-year. From the embedded qualitative study, the Better Outcomes for Older people with Spinal Trouble programme was acceptable to participants, and enjoyable. Limitations Many of the data collected were self-reported and thus may be subject to recall bias or may have resulted in misclassification of participants. Conclusions Back pain is a substantial problem for older people, with the majority reporting persistent symptoms. We have developed an effective intervention to improve mobility and reduce falls in older people with neurogenic claudication; however, more effective interventions are needed for back pain generally. We have identified a set of self-reported questions that predict mobility decline in older people, so clinicians and their patients and families know when intervention is needed. Future work Develop and evaluate treatments for older people with back pain. Optimisation of the Better Outcomes for Older people with Spinal Trouble programme to better target pain-related disability. External validation of the Oxford Pain Activity and Lifestyle prognostic tool. Study registration This trial is registered as BOOST trial ISRCTN12698674. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Programme Grants for Applied Research programme (NIHR award ref: PTC-RP-PG-0213-20002) and is published in full in Programme Grants for Applied Research; Vol. 11, No. 9. See the NIHR Funding and Awards website for further award information.

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“…A nomogram serves as a visual representation of a complex mathematical formula, condensing statistical forecasting models into a single numerical estimate of the probability of an event for a given patient [12]. Within clinical practice, nomograms are commonly employed as risk prediction models for certain diseases [13] .However, in the context of older adults with diabetes, there is a dearth of research examining the risk factors associated with restricted life-space, and consequently, a scarcity of validated risk prediction models tailored to this population. Although scholars from other countries have developed machine learning model to predict the risk of restricted life-space in community-dwelling older adults [14], the model cannot be directly applied to the specific Chinese elderly diabetic population.…”

Section: Introductionmentioning

confidence: 99%

Risk factors and a nomogram prediction model for Restricted Life-Space in Chinese older adults with diabetes:A single-center cross-sectional study

Zhang

Guo

Zhang

et al. 2023

Preprint

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Background Physical activity is a crucial component of the treatment and management of diabetes, yet older individuals with diabetes generally exhibit insufficient physical activity levels. Life space mobility (LSM), which reflects the physical activity and psychological well-being of older individuals within their actual environment, poses challenges to the management of diabetes in this age group, significantly jeopardizing their physical and mental health. Aim The objective of this study is twofold: first, to investigate the risk factors associated with mobility restriction among older adults with diabetes mellitus; and second, to develop and verify a restricted life-space risk nomogram prediction model for this population by nomogram. Methods The convenient sampling method was employed to recruit participators aged 60 years and above from both the endocrinology clinic and health examination center situated in a Grade A hospital located in Anhui. These participators were then categorized into two groups: the Restricted Life-Space(RLS) group and the non-Restricted Life-Space group. The Least absolute shrinkage and selection operator (LASSO) regression was used to decrease data dimensionality and select features, while the C index and Brier score were employed to assess the model's discrimination and calibration, respectively. Receiver operating characteristic (ROC) curves and calibration curve were generated to visualize the performance of the model.Decision curve analysis (DCA) and clinical impact curve (CIC) were conducted to evaluate the clinical value of the model. The internal validity of the model was confirmed using the bootstrapping method, while external validation was performed to test its generalizability. Results A risk nomogram prediction model was developed using four predictors: fear of falling, decline of activities of daily living (ADL), lower limb hypofunction, and decline of vision.Internal validation of the model yielded the following results: a C index of 0.936, a goodness-of-fit test χ2 value of 1.21 with a corresponding P-value of 0.75, and a Brier score of 0.081. In the DCA, the threshold ranged from 0.1 to 0.95, and the clinical net benefit was consistently greater than 0. The CIC demonstrated that the predicted risk generated via the model was highly consistent with the actual risk. External validation of the model resulted in a C index of 0.932, a goodness-of-fit test χ2 value of 3.11 with a corresponding P-value of 0.60, and a Brier score of 0.106. Conclusion The risk nomogram prediction model constructed in this study based on the above four independent risk factors is noninvasive, inexpensive, and easily accessible, with high sensitivity, specificity, and utility, and provides a reference for the assessment and intervention of life-space mobility levels in older adults with diabetes.

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Development and validation of a prediction model for self-reported mobility decline in community-dwelling older adults

Cited by 5 publications

References 34 publications

Establishment and validation of a prediction model for myocarditis in Chinese children below 14 years old: a protocol for a retrospective cohort study

Establishment and validation of a prediction model for myocarditis in Chinese children below 14 years old: a protocol for a retrospective cohort study

Improving the understanding and management of back pain in older adults: the BOOST research programme including RCT and OPAL cohort

Risk factors and a nomogram prediction model for Restricted Life-Space in Chinese older adults with diabetes:A single-center cross-sectional study

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