Evidence map›Paper›PMID 40481856›Full record

ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2025

Predictive relationship in perioperative symptoms and step count for lung cancer patients.

Lijia Hou, Yang Zhao, Mingqi Zhang, Xiaobo Wang, Lihong Zhu, Tingting Chen, Xinyan Wu, Danfeng Gu

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Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

8 authors.

Lijia Hou *Wuxi Medical College, Jiangnan University, 1800 Lihu Avenue, Wuxi, 214122, Jiangsu Province, China.
Yang Zhao *Office of Hospital Administration, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, Binhu District, Wuxi, 214122, Jiangsu Province, China.
Mingqi ZhangWuxi Medical College, Jiangnan University, 1800 Lihu Avenue, Wuxi, 214122, Jiangsu Province, China.
Xiaobo WangWuxi Medical College, Jiangnan University, 1800 Lihu Avenue, Wuxi, 214122, Jiangsu Province, China.
Lihong ZhuDepartment of Burn and Plastic Surgery, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, Binhu District, Wuxi, 214122, Jiangsu Province, China.
Tingting ChenWuxi Medical College, Jiangnan University, 1800 Lihu Avenue, Wuxi, 214122, Jiangsu Province, China.
Xinyan WuWuxi Medical College, Jiangnan University, 1800 Lihu Avenue, Wuxi, 214122, Jiangsu Province, China.
Danfeng GuDepartment of Nursing, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, Binhu District, Wuxi, 214122, Jiangsu Province, China. 1308594635@qq.com.

Funding

Hospital Management Innovation Research Fund from Jiangsu Provincial Hospital Association JSYGY-2023-125
6 · The paper itself

Abstract

backgroundLung cancer patients' recovery is hindered by persistent symptoms, but the relationship between symptoms and physical activity is not well understood.

objectiveThe objective of this study is to examine changes in symptoms and physical activity among lung cancer patients and their short-term predictive relationship.

methodsNinety-six lung cancer patients (average age 59.70) were selected. Symptoms (pain, fatigue, distress, cough, dyspnea, and sleepiness) were monitored three times daily from preoperative to postoperative day 6 using the Ecological Momentary Assessment. Step count was continuously monitored via a smartwatch. Short-term trends in symptoms and step count were analyzed. A hierarchical linear model was used to examine the immediate and lagged correlations between symptoms and step count, with confounders controlled.

resultsSymptoms and step counts showed fluctuation with a jagged changing trajectory. Step count decreased significantly when symptoms were worse than the individual average (P < 0.001), except for cough. Symptoms were significantly reduced when step count significantly increased (P < 0.001). Pain (β =  - 73.384, P < 0.001) had a negative predictive effect on step count at the next moment, after controlling for step count. Step count at the same time had a significant effect on alleviating pain (β =  - 0.0002, P < 0.05), fatigue (β =  - 0.0003, P < 0.05), and sleepiness (β =  - 0.0003, P < 0.001), next moment, after controlling for symptoms. There was a significant intrinsic predictive effect between symptoms and step count (P < 0.001).

conclusionLung cancer patients experience fluctuations in symptoms and step count during the perioperative period. There is a significant relationship between symptoms and step count on the same day. Future studies could explore interventions to improve symptoms and mobility.

Indexed as

ExerciseLung NeoplasmsAdultAgedCoughDyspneaEcological Momentary AssessmentFatigueFemaleHumansMaleMiddle AgedPerioperative PeriodEcological momentary assessmentsLung cancerPerioperativePhysical activitySurgical treatment

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.