Evidence map›Paper›PMID 31798948›Full record

ArticleBMJ open sport & exercise medicine2019

Robust Exponential Decreasing Index (REDI): adaptive and robust method for computing cumulated workload.

Issa Moussa, Arthur Leroy, Guillaume Sauliere, Julien Schipman, Jean-François Toussaint, Adrien Sedeaud

Abstract read
In one paragraph

Article in BMJ open sport & exercise medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

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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

6 authors.

Issa MoussaIRMES, Institut National du Sport de l'Expertise et de la Performance, Paris, France.ORCID 0000-0002-8397-9677
Arthur LeroyIRMES, Institut National du Sport de l'Expertise et de la Performance, Paris, France.ORCID 0000-0003-0806-8934
Guillaume SauliereIRMES, Institut National du Sport de l'Expertise et de la Performance, Paris, France.
Julien SchipmanIRMES, Institut National du Sport de l'Expertise et de la Performance, Paris, France.
Jean-François ToussaintIRMES, Institut National du Sport de l'Expertise et de la Performance, Paris, France.
Adrien SedeaudIRMES, Institut National du Sport de l'Expertise et de la Performance, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe purpose of this study was to define a new index the Robust Exponential Decreasing Index (REDI), which is capable of an improved analysis of the cumulative workload. This allows for precise control of the decreasing influence of load over time. Additionally, REDI is robust to missing data that are frequently present in sport.

methods200 cumulative workloads were simulated in two ways (Gaussian and uniform distributions) to test the robustness and flexibility of the REDI, as compared with classical methods (acute:chronic workload ratio and exponentially weighted moving average). Theoretical properties have been highlighted especially around the decreasing parameter.

resultsThe REDI allows practitioners to consistently monitor load with missing data as it remains consistent even when a significant portion of the dataset is absent. Adjusting the decreasing parameter allows practitioners to choose the weight given to each daily workload. DISCUSSION: Computation of cumulative workload is not easy due to many factors (weekends, international training sessions, national selections and injuries). Several practical and theoretical drawbacks of the existing indices are discussed in the paper, especially in the context of missing data; the REDI aims to settle some of them. The decreasing parameter may be modified according to the studied sport. Further research should focus on methodology around setting this parameter.

conclusionThe robust and adaptable nature of the REDI is a credible alternative for computing a cumulative workload with decreasing weight over time.

Indexed as

cumulated workloadindexmissing datamonitoringtraining load

Identifiers

PMID31798948
PMCPMC6863659

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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.