Evidence map›Paper›PMID 37639172›Full record

ArticleAging clinical and experimental research2023

Kinect-based objective assessment for early frailty identification in patients with Parkinson's disease.

Ludi Xie, Ronghua Hong, Zhuang Wu, Lei Yue, Kangwen Peng, Shuangfang Li, Jingxing Zhang, Xijin Wang, Lingjing Jin, Qiang Guan

Abstract read
PubMed Publisher
In one paragraph

Article in Aging clinical and experimental research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Ludi Xie *Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
Ronghua Hong *Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
Zhuang WuDepartment of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
Lei YueDepartment of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
Kangwen PengDepartment of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
Shuangfang LiDepartment of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
Jingxing ZhangDepartment of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
Xijin WangDepartment of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
Lingjing JinDepartment of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China. lingjingjin@tongji.edu.cn.
Qiang GuanDepartment of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China. guanqianglu@126.com.
Tongji University · CNTongji Hospital · CNShanghai Sunshine Rehabilitation Center · CN

Funding

Innovative Research Group Project of the National Natural Science Foundation of China 81974198
6 · The paper itself

Abstract

backgroundFrailty is common in Parkinson's disease (PD) and increases vulnerability to adverse outcomes. Early detection of this syndrome aids in early intervention.

aimsTo objectively identify frailty at an early stage during routine motor tasks in PD patients using a Kinect-based system.

methodsPD patients were recruited and assessed with the Fried criteria to determine their frailty status. Each participant was recorded performing the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) extremity tasks with a Kinect-based system. Statistically significant kinematic parameters were selected to discriminate the pre-frail from the non-frail group.

resultsOf the fifty-two participants, twenty were non-frail and thirty-two were pre-frail. Decreased frequency in finger tapping (P = 0.005), hand grasping (P = 0.002), toe tapping (P = 0.002), and leg agility (P = 0.019) alongside reduced hand grasping speed (P = 0.030), lifting (P < 0.001) and falling speed (P < 0.001) in leg agility were observed in the pre-frail group. Amplitude in leg agility (P = 0.048) and amplitude decrement rate (P = 0.046) in hand grasping showed marginally significant differences between two groups. Moderate discriminative values were found in frequency and speed of the extremity tasks to identify pre-frailty with sensitivity, specificity, and area under the curve (AUC) in the range of 45.00-85.00%, 68.75-100%, and 0.701-0.836, respectively. The combination of frequency and speed in extremity tasks showed moderate to high discriminatory ability, with AUC of 0.775 (95% CI 0.637-0.913, P < 0.001) for upper limb tasks and 0.909 (95% CI 0.832-0.987, P < 0.001) for lower limb tasks. When combining these features in both upper and lower limb tasks, the AUC increased to 0.942 (95% CI 0.886-0.999, P < 0.001).

conclusionsOur findings demonstrated the promise of utilizing Kinect-based kinematic data from MDS-UPDRS III tasks as early indicators of frailty in PD patients.

Indexed as

FrailtyParkinson DiseaseHandHumansLower ExtremityUpper ExtremityFrailtyKinectObjective assessmentParkinson’s disease

Identifiers

PMID37639172
OpenAlexW4386209135

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.