References: Rapo-Pylkkö, S., Haanpää, M. & Liira, H. Chronic pain among community-dwelling elderly: A population-based clinical study. Scand. J. Prim. Health Care 34, 159–164. https://doi.org/10.3109/02813432.2016.1160628 (2016). (PMID: 10.3109/02813432.2016.116062827065337)
Vlaeyen, J. W. S. & Linton, S. J. Fear-avoidance and its consequences in chronic musculoskeletal pain: A state of the art. Pain 85, 317–332. https://doi.org/10.1016/s0304-3959(99)00242-0 (2000). (PMID: 10.1016/s0304-3959(99)00242-010781906)
Ge, L., Pereira, M. J., Yap, C. W. & Heng, B. H. Chronic low back pain and its impact on physical function, mental health, and health-related quality of life: A cross-sectional study in Singapore. Sci. Rep. 12, 20040. https://doi.org/10.1038/s41598-022-24703-7 (2022). (PMID: 10.1038/s41598-022-24703-7364146749681885)
Geneen, L. J. et al. Physical activity and exercise for chronic pain in adults: An overview of Cochrane Reviews. Cochrane Database Syst. Rev. 4, CD011279. https://doi.org/10.1002/14651858.cd011279.pub3 (2017). (PMID: 10.1002/14651858.cd011279.pub328436583)
Zhu, F. et al. Yoga compared to non-exercise or physical therapy exercise on pain, disability, and quality of life for patients with chronic low back pain. PLoS One 15, e0238544. https://doi.org/10.1371/journal.pone.0238544 (2020). (PMID: 10.1371/journal.pone.0238544328709367462307)
Vader, K., Doulas, T., Patel, R. & Miller, J. Experiences, barriers, and facilitators to participation in physical activity and exercise in adults living with chronic pain: A qualitative study. Disabil. Rehabil. 43, 1829–1837. https://doi.org/10.1080/09638288.2019.1676834 (2021). (PMID: 10.1080/09638288.2019.167683431613655)
Mielenz, T. J. et al. The association of pain levels and low physical activity among older women. Geriatrics (Basel) https://doi.org/10.3390/geriatrics6040103 (2021). (PMID: 10.3390/geriatrics604010334842712)
Larsson, C., Ekvall Hansson, E., Sundquist, K. & Jakobsson, U. Impact of pain characteristics and fear-avoidance beliefs on physical activity levels among older adults with chronic pain: A population-based, longitudinal study. BMC Geriatr. 16, 50. https://doi.org/10.1186/s12877-016-0224-3 (2016). (PMID: 10.1186/s12877-016-0224-3269122164765143)
American Society of Anesthesiologists Task Force on Chronic Pain Management; American Society of Regional Anesthesia and Pain Medicine. Practice guidelines for chronic pain management: An updated report by the American Society of Anesthesiologists Task Force on Chronic Pain Management. Anesthesiology 112, 810–833. https://doi.org/10.1097/ALN.0b013e3181c43103 (2010). (PMID: 10.1097/ALN.0b013e3181c43103)
Azfar, S. M., Murad, M. A., Azim, S. & Baig, M. Rapid assessment of physical activity and its association among patients with low back pain. Cureus 11, e6373. https://doi.org/10.7759/cureus.6373 (2019). (PMID: 10.7759/cureus.6373319386536957041)
Andersson, H. I. Increased mortality among individuals with chronic widespread pain relates to lifestyle factors: A prospective population-based study. Disabil. Rehabil. 31, 1980–1987. https://doi.org/10.3109/09638280902874154 (2009). (PMID: 10.3109/0963828090287415419874076)
Chung, H. et al. Prediction and feature importance analysis for severity of COVID-19 in South Korea using artificial intelligence: Model development and validation. J. Med. Internet Res. 23, e27060. https://doi.org/10.2196/27060 (2021). (PMID: 10.2196/27060337648838057199)
Almustafa, K. M. Covid19-Mexican-patients’ dataset (Covid19MPD) classification and prediction using feature importance. Concurr. Comput. 34, e6675. https://doi.org/10.1002/cpe.6675 (2022). (PMID: 10.1002/cpe.667534899078)
Devi, S. et al. Prediction and detection of cervical malignancy using machine learning models. Asian Pac. J. Cancer Prev. 24, 1419–1433. https://doi.org/10.31557/APJCP.2023.24.4.1419 (2023). (PMID: 10.31557/APJCP.2023.24.4.14193711616710352741)
Seok, M. et al. Sarcopenia prediction for elderly people using machine learning: A case study on physical activity. Healthcare (Basel) 11, 1334. https://doi.org/10.3390/healthcare11091334 (2023). (PMID: 10.3390/healthcare1109133437174876)
von Elm, E. et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for reporting observational studies. Int. J. Surg. 12, 1495–1499. https://doi.org/10.1016/j.ijsu.2014.07.013 (2014). (PMID: 10.1016/j.ijsu.2014.07.013)
Craig, C. L. et al. International physical activity questionnaire: 12-country reliability and validity. Med. Sci. Sports Exerc. 35, 1381–1395. https://doi.org/10.1249/01.Mss.0000078924.61453.Fb (2003). (PMID: 10.1249/01.Mss.0000078924.61453.Fb12900694)
Wong, C. K. et al. Prevalence, incidence, and factors associated with non-specific chronic low back pain in community-dwelling older adults aged 60 years and older: A systematic review and meta-analysis. J. Pain 23, 509–534. https://doi.org/10.1016/j.jpain.2021.07.012 (2022). (PMID: 10.1016/j.jpain.2021.07.01234450274)
Neblett, R. et al. The Central Sensitization Inventory (CSI): Establishing clinically significant values for identifying central sensitivity syndromes in an outpatient chronic pain sample. J. Pain 14, 438–445. https://doi.org/10.1016/j.jpain.2012.11.012 (2013). (PMID: 10.1016/j.jpain.2012.11.012234906343644381)
Nishigami, T. et al. Development and psychometric properties of a short form of central sensitization inventory in participants with musculoskeletal pain: A cross-sectional study. PLoS One 13, e0200152. https://doi.org/10.1371/journal.pone.0200152 (2018). (PMID: 10.1371/journal.pone.0200152299757546033441)
Lundberg, M., Grimby-Ekman, A., Verbunt, J. & Simmonds, M. J. Pain-related fear: A critical review of related measures. Pain Res. Treat. 2011, 494196. https://doi.org/10.1155/2011/494196 (2011). (PMID: 10.1155/2011/494196221910223236324)
Kikuchi, N., Matsudaira, K., Sawada, T. & Oka, H. Psychometric properties of the Japanese version of the Tampa Scale for Kinesiophobia (TSK-J) in patients with whiplash neck injury pain and/or low back pain. J. Orthop. Sci. 20, 985–992. https://doi.org/10.1007/s00776-015-0751-3 (2015). (PMID: 10.1007/s00776-015-0751-326201395)
The prevention of falls in later life. A report of the Kellogg International Work Group on the Prevention of Falls by the Elderly. Dan. Med. Bull. 34(Suppl 4), 1–24 (1987).
Soldatos, C. R., Dikeos, D. G. & Paparrigopoulos, T. J. Athens Insomnia Scale: Validation of an instrument based on ICD-10 criteria. J. Psychosom. Res. 48, 555–560. https://doi.org/10.1016/s0022-3999(00)00095-7 (2000). (PMID: 10.1016/s0022-3999(00)00095-711033374)
Tinetti, M. E., Mendes de Leon, C. F., Doucette, J. T. & Baker, D. I. Fear of falling and fall-related efficacy in relationship to functioning among community-living elders. J. Gerontol. 49, M140–M147. https://doi.org/10.1093/geronj/49.3.m140 (1994). (PMID: 10.1093/geronj/49.3.m1408169336)
Sertel, M., Aydogan Arslan, S., Tutun Yumin, E., Demirci, C. S. & Tarsuslu Simsek, T. Investigation of the relationship between physical activity, kinesiophobia and fear of falling in older adults with chronic pain. Somatosens. Mot. Res. 38, 241–247. https://doi.org/10.1080/08990220.2021.1958774 (2021). (PMID: 10.1080/08990220.2021.195877434334097)
Cai, Y., Leveille, S. G., Shi, L., Chen, P. & You, T. Chronic pain and circumstances of falls in community-living older adults: An exploratory study. Age Ageing 51, afab261. https://doi.org/10.1093/ageing/afab261 (2022). (PMID: 10.1093/ageing/afab261350618718782600)
Phelan, E. A. & Ritchey, K. Fall prevention in community-dwelling older adults. Ann. Intern. Med. 169, itc81–itc96. https://doi.org/10.7326/aitc201812040 (2018). (PMID: 10.7326/aitc20181204030508457)
Zbrońska, I. & Mędrela-Kuder, E. The level of physical activity in elderly persons with overweight and obesity. Rocz. Panstw. Zakl. Hig. 69, 369–373. https://doi.org/10.32394/rpzh.2018.0042.PMID:30525327 (2018). (PMID: 10.32394/rpzh.2018.0042.PMID:3052532730525327)
Bohannon, R. W. Grip strength: An indispensable biomarker for older adults. Clin. Interv. Aging 14, 1681–1691. https://doi.org/10.2147/CIA.S194543 (2019). (PMID: 10.2147/CIA.S194543316319896778477)
Lluch, E., Torres, R., Nijs, J. & Van Oosterwijck, J. Evidence for central sensitization in patients with osteoarthritis pain: A systematic literature review. Eur. J. Pain 18, 1367–1375. https://doi.org/10.1002/j.1532-2149.2014.499.x (2014). (PMID: 10.1002/j.1532-2149.2014.499.x24700605)
Druce, K. L. & McBeth, J. Central sensitization predicts greater fatigue independently of musculoskeletal pain. Rheumatology (Oxford) 58, 1923–1927. https://doi.org/10.1093/rheumatology/kez028 (2019). (PMID: 10.1093/rheumatology/kez02830815696)
Mohammadi, F. et al. Evaluation of effective features in the diagnosis of Covid-19 infection from routine blood tests with multilayer perceptron neural network: A cross-sectional study. Health Sci. 6, e1048. https://doi.org/10.1002/hsr2.1048 (2023). (PMID: 10.1002/hsr2.1048)
Stojanowski, J. et al. Artificial neural network—An effective tool for predicting the lupus nephritis outcome. BMC Nephrol. 23, 381. https://doi.org/10.1186/s12882-022-02978-2 (2022). (PMID: 10.1186/s12882-022-02978-2364436789706924)
Tsai, P. F. et al. A classification algorithm to predict chronic pain using both regression and machine learning—A stepwise approach. Appl. Nurs. Res. 62, 151504. https://doi.org/10.1016/j.apnr.2021.151504 (2021). (PMID: 10.1016/j.apnr.2021.151504348150008906500)
No Comments.