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Physical exercise for people with Parkinson’s disease: a systematic review and network meta-analysis

2023· review· en· W4313546386 on OpenAlexfundno aff
Moritz Ernst, Ann‐Kristin Folkerts, Romina Gollan, Emma Lieker, Julia Caro-Valenzuela, Anne Adams, Nora Cryns, Ina Monsef, Antje Dresen, Mandy Roheger, Carsten Eggers, Nicole Skoetz, Elke Kalbe

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2023
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersDefence and Security AcceleratorNational Center for Research ResourcesNational Institute on AgingParkinsonfondenOregon Clinical and Translational Research InstituteNational Institutes of HealthXunta de GaliciaDivision of Graduate EducationPhysiotherapy Research FoundationUniversidade Federal do ParanáNatural Sciences and Engineering Research Council of CanadaStockholms Läns LandstingKarolinska InstitutetVetenskapsrådetNational Natural Science Foundation of ChinaShanghai Municipal Education CommissionConselho Nacional de Desenvolvimento Científico e TecnológicoGun och Bertil Stohnes StiftelseScience and Technology Commission of Shanghai MunicipalityCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São PauloInternational Parkinson and Movement Disorder SocietyEuropean CommissionShanghai Education Development FoundationU.S. Department of Veterans Affairs
KeywordsMeta-analysisMedicineMEDLINERandomized controlled trialPhysical therapyQuality of life (healthcare)Confidence intervalAdverse effectPhysical medicine and rehabilitationDiseaseSystematic reviewPsychological interventionMotor symptomsGaitRelative riskParkinson's diseaseInternal medicinePsychiatry

Abstract

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BACKGROUND: Physical exercise is effective in managing Parkinson's disease (PD), but the relative benefit of different exercise types remains unclear. OBJECTIVES: To compare the effects of different types of physical exercise in adults with PD on the severity of motor signs, quality of life (QoL), and the occurrence of adverse events, and to generate a clinically meaningful treatment ranking using network meta-analyses (NMAs). SEARCH METHODS: An experienced information specialist performed a systematic search for relevant articles in CENTRAL, MEDLINE, Embase, and five other databases to 17 May 2021. We also searched trial registries, conference proceedings, and reference lists of identified studies up to this date. SELECTION CRITERIA: We included randomized controlled trials (RCTs) comparing one type of physical exercise for adults with PD to another type of exercise, a control group, or both. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data. A third author was involved in case of disagreements. We categorized the interventions and analyzed their effects on the severity of motor signs, QoL, freezing of gait, and functional mobility and balance up to six weeks after the intervention using NMAs. Two review authors independently assessed the risk of bias using the risk of bias 2 (RoB 2) tool and rated the confidence in the evidence using the CINeMA approach for results on the severity of motor signs and QoL. We consulted a third review author to resolve any disagreements. Due to heterogeneous reporting of adverse events, we summarized safety data narratively and rated our confidence in the evidence using the GRADE approach. MAIN RESULTS: We included 156 RCTs with a total of 7939 participants with mostly mild to moderate disease and no major cognitive impairment. The number of participants per study was small (mean 51, range from 10 to 474). The NMAs on the severity of motor signs and QoL included data from 71 (3196 participants), and 55 (3283 participants) trials, respectively. Eighty-five studies (5192 participants) provided safety data. Here, we present the main results. We observed evidence of beneficial effects for most types of physical exercise included in our review compared to a passive control group. The effects on the severity of motor signs and QoL are expressed as scores on the motor scale of the Unified Parkinson Disease Rating Scale (UPDRS-M) and the Parkinson's Disease Questionnaire 39 (PDQ-39), respectively. For both scales, higher scores denote higher symptom burden. Therefore, negative estimates reflect improvement (minimum clinically important difference: -2.5 for UPDRS-M and -4.72 for PDQ-39). Severity of motor signs The evidence from the NMA (71 studies; 3196 participants) suggests that dance has a moderate beneficial effect on the severity of motor signs (mean difference (MD) -10.32, 95% confidence interval (CI) -15.54 to -4.96; high confidence), and aqua-based, gait/balance/functional, and multi-domain training might have a moderate beneficial effect on the severity of motor signs (aqua-based: MD -7.77, 95% CI -13.27 to -2.28; gait/balance/functional: MD -7.37, 95% CI -11.39 to -3.35; multi-domain: MD -6.97, 95% CI -10.32 to -3.62; low confidence). The evidence also suggests that mind-body training and endurance training might have a small beneficial effect on the severity of motor signs (mind-body: MD -6.57, 95% CI -10.18 to -2.81; endurance: MD -6.43, 95% CI -10.72 to -2.28; low confidence). Flexibility training might have a trivial or no effect on the severity of motor signs (MD 2.01, 95% CI -4.82 to 8.98; low confidence). The evidence is very uncertain about the effects of strength/resistance training and "Lee Silverman Voice training BIG" (LSVT BIG) on the severity of motor signs (strength/resistance: MD -6.97, 95% CI -11.93 to -2.01; LSVT BIG: MD -5.49, 95% CI -14.74 to 3.62; very low confidence). Quality of life The evidence from the NMA (55 studies; 3283 participants) suggests that aqua-based training probably has a large beneficial effect on QoL (MD -14.98, 95% CI -23.26 to -6.52; moderate confidence). The evidence also suggests that endurance training might have a moderate beneficial effect, and that gait/balance/functional and multi-domain training might have a small beneficial effect on QoL (endurance: MD -9.16, 95% CI -15.68 to -2.82; gait/balance/functional: MD -5.64, 95% CI -10.04 to -1.23; multi-domain: MD -5.29, 95% CI -9.34 to -1.06; low confidence). The evidence is very uncertain about the effects of mind-body training, gaming, strength/resistance training, dance, LSVT BIG, and flexibility training on QoL (mind-body: MD -8.81, 95% CI -14.62 to -3.00; gaming: MD -7.05, 95% CI -18.50 to 4.41; strength/resistance: MD -6.34, 95% CI -12.33 to -0.35; dance: MD -4.05, 95% CI -11.28 to 3.00; LSVT BIG: MD 2.29, 95% CI -16.03 to 20.44; flexibility: MD 1.23, 95% CI -11.45 to 13.92; very low confidence). Adverse events Only 85 studies (5192 participants) provided some kind of safety data, mostly only for the intervention groups. No adverse events (AEs) occurred in 40 studies and no serious AEs occurred in four studies. AEs occurred in 28 studies. The most frequently reported events were falls (18 studies) and pain (10 studies). The evidence is very uncertain about the effect of physical exercise on the risk of adverse events (very low confidence). Across outcomes, we observed little evidence of differences between exercise types. AUTHORS' CONCLUSIONS: We found evidence of beneficial effects on the severity of motor signs and QoL for most types of physical exercise for people with PD included in this review, but little evidence of differences between these interventions. Thus, our review highlights the importance of physical exercise regarding our primary outcomes severity of motor signs and QoL, while the exact exercise type might be secondary. Notably, this conclusion is consistent with the possibility that specific motor symptoms may be treated most effectively by PD-specific programs. Although the evidence is very uncertain about the effect of exercise on the risk of adverse events, the interventions included in our review were described as relatively safe. Larger, well-conducted studies are needed to increase confidence in the evidence. Additional studies recruiting people with advanced disease severity and cognitive impairment might help extend the generalizability of our findings to a broader range of people with PD.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.359
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0580.009
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.142
GPT teacher head0.390
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations193
Published2023
Admission routes1
Has abstractyes

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