O desempenho no Teste de Agachamento Profundo e lesões musculoesqueléticas: uma revisão sistemática

Bunn, Priscila dos Santos; Silva, Glória de Paula; Silva, Elirez Bezerra da

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Fisioterapia em Movimento

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Sumário

REVIEW ARTICLES • Fisioter. mov. 31 • 2018 • https://doi.org/10.1590/1980-5918.031.AO26 copiar

O desempenho no Teste de Agachamento Profundo e lesões musculoesqueléticas: uma revisão sistemática

Autoria SCIMAGO INSTITUTIONS RANKINGS

Resumo

Introdução:

O Teste de Agachamento Profundo (TAP) tem sido utilizado em avaliações pré-temporada de equipes esportivas e em cursos militares para classificar o risco de lesões musculoesqueléticas.

Objetivo:

Avaliar a associação do desempenho no TAP e o risco de lesões musculoesqueléticas.

Métodos:

Nesta revisão sistemática, uma pesquisa sem filtros de linguagem ou de tempo foi realizada nas bases de dados MEDLINE, SciELO, SCOPUS, SPORTDdiscuss, CINAHL e BVS com as seguintes palavras-título: predição de lesões, risco de lesão e agachamento profundo em dezembro de 2016. Perfil dos participantes, tamanho da amostra, classificação das lesões musculoesqueléticas, tempo de seguimento, desenho do estudo e os resultados foram extraídos dos estudos. A análise do risco de viés foi realizada com a Escala Newcastle-Ottawa.

Resultados:

Foram incluídos cinco estudos, utilizando diferentes análises, cujos resultados variaram. O odds ratio variou de 1,21 a 2,59 (IC 95% = 1,01-3,28); O risco relativo foi de 1,68 (IC 95% = 1,50 - 1,87), sensibilidade de 3 a 24%, especificidade de 90 a 99%, VPP de 42 a 63%, VPN de 72 a 75% e AUC de 51 a 58%.

Conclusão:

O TAP pode ser um teste cuja presença de disfunções de movimento é um preditor do risco de lesões musculoesqueléticas em indivíduos que praticam exercícios físicos. No entanto, devido às limitações metodológicas apresentadas, sugere-se cautela ao interpretar esses resultados. Registro PROSPERO: CRD4201706922.

Palavras-chave:
Movimento; Lesões Atléticas; Triagem

Study	Sample characteristics	Injury definition	Follow-up time
Butler et al., 2013²⁵25 Butler RJ, Contreras M, Burton LC, Plisky PJ, Goode A, Kiesel K. Modifiable risk factors predict injuries in firefighters during training academies. Work. 2013;46(1):11-7.	n = 108 firefighter students Age = NR	More than 3 days away from functions due to musculoskeletal pain	4 months
Bushman et al., 2015²⁶26 Bushman TT, Grier TL, Canham-Chervak MC, Anderson MK, North WJ, Jones BH. Pain on Functional Movement Screen Tests and Injury Risk. J Strength Cond Res. 2015;29(Suppl 11):S65-70.	n = 2476 soldiers Age = 18 -57 years old	Simple record of traumatic and non-traumatic injuries	6 months
Hotta et al., 2015²⁷27 Hotta T, Nishiguchi S, Fukutani N, Tashiro Y, Adachi D, Morino S, et al. Functional Movement Screen for Predicting Running Injuries in 18- to 24-Year-Old Competitive Male Runners. J Strength Cond Res. 2015;29(10):2808-15.	n = 84 male runners. Age = 18 - 24 years old	Two prerequisites were used: (1) The injury occurred as a result of participating in race or training events (traumatic injuries were excluded); (2) the injury was severe enough to prevent athletic activities for at least 4 weeks	6 months
Zalai et al., 2015²⁸28 Zalai D, Panics G, Bobak P, Csáki I, Hamar P. Quality of functional movement patterns and injury examination in elite-level male professional football players. Acta Physiol Hung. 2015;102(1):34-42.	n = 20 football players Age = 23 ± 1 years old	Injury that caused the athlete to be separated from his / her activities, according to the criterion: minimum (1-7 days); Moderate (8-28 days) and severe (> 28 days), according to Hägglund et al., (2005)³⁰30 Hägglund M, Waldén M, Bahr R, Ekstrand J. Methods for epidemiological study of injuries to professional football players: developing the UEFA model. Br J Sports Med. 2005;39(6):340-6..	6 months
Tee et al., 2016²⁹29 Tee JC, Klingbiel JF, Collins R, Lambert MI, Coopoo Y. Preseason Functional Movement Screen component tests predict severe contact injuries in professional rugby union players. J Strength Cond Res. 2016;30(11):3194-203.	n = 62 rugby players Age = NR	Considered only the serious injuries (time loss greater than 28 days), which were subdivided into contact injuries, non-contact injuries, or any injury (Fuller et al., 2006)³¹31 Fuller CW, Molloy MG, Bagate C, Bahr R, Brooks JH, Donson H, et al. Consensus statement on injury definitions and data collection procedures for studies of injuries in rugby union. Br J Sports Med. 2007;41(5):328-31..	6 months

Statistical analysis	Author	Results
Odds ratios	Butler et al., 2013²⁵25 Butler RJ, Contreras M, Burton LC, Plisky PJ, Goode A, Kiesel K. Modifiable risk factors predict injuries in firefighters during training academies. Work. 2013;46(1):11-7.	OR: 1.21 (CI 95% = 1.01-1.42)
Odds ratios	Bushman et al., 2015²⁴24 Margulis AV, Pladevall M, Riera-Guardia N, Varas-Lorenzo C, Hazell L, Berkman ND, et al. Quality assessment of observational studies in a drug-safety systematic review, comparison of two tools: the Newcastle-Ottawa Scale and the RTI item bank. Clin Epidemiol. 2014;6:359-68.	OR = 2.59 (CI 95% = 2.05-3.28); P < 0.01
Diagnostic accuracy	Bushman et al., 2015²⁴24 Margulis AV, Pladevall M, Riera-Guardia N, Varas-Lorenzo C, Hazell L, Berkman ND, et al. Quality assessment of observational studies in a drug-safety systematic review, comparison of two tools: the Newcastle-Ottawa Scale and the RTI item bank. Clin Epidemiol. 2014;6:359-68.	s = 3-24%; e = 90-99% PPV = 57 (42-63%); NPV= 66 (72-75%); AUC = 51-58%
Relative risk	Bushman et al., 2015²⁴24 Margulis AV, Pladevall M, Riera-Guardia N, Varas-Lorenzo C, Hazell L, Berkman ND, et al. Quality assessment of observational studies in a drug-safety systematic review, comparison of two tools: the Newcastle-Ottawa Scale and the RTI item bank. Clin Epidemiol. 2014;6:359-68.	RR* = 1.68 (CI 95% = 1.50 - 1.87);
Mann-Whitney Test.	Hotta et al., 2015²⁶26 Bushman TT, Grier TL, Canham-Chervak MC, Anderson MK, North WJ, Jones BH. Pain on Functional Movement Screen Tests and Injury Risk. J Strength Cond Res. 2015;29(Suppl 11):S65-70.	IG: 1.8 ± 0.7; NIG: 1.3 ± 0.7 com P < 0.01
Pearson’s correlate coefficient.	Zalai et al., 2015²⁸28 Zalai D, Panics G, Bobak P, Csáki I, Hamar P. Quality of functional movement patterns and injury examination in elite-level male professional football players. Acta Physiol Hung. 2015;102(1):34-42.	Statistical power = 0.56; IG = 1.67 ± 0.51; NIG = 2.21 ± 0.42; P < 0.05.
ES (Cohen)	Tee et al., 2016³⁰30 Hägglund M, Waldén M, Bahr R, Ekstrand J. Methods for epidemiological study of injuries to professional football players: developing the UEFA model. Br J Sports Med. 2005;39(6):340-6.	ES = 0.60 (IG versus NIG); ES (TI) = 1.04 (large) ES (NTI) = 0.20 (small)

Authors	Domains			Results
Authors	Selection	Comparability	Outcome	Score	Risk
Butler et al., 2013²⁵25 Butler RJ, Contreras M, Burton LC, Plisky PJ, Goode A, Kiesel K. Modifiable risk factors predict injuries in firefighters during training academies. Work. 2013;46(1):11-7.	^****	-	^**	^******	Uncertain
Bushman et al., 2015²⁴24 Margulis AV, Pladevall M, Riera-Guardia N, Varas-Lorenzo C, Hazell L, Berkman ND, et al. Quality assessment of observational studies in a drug-safety systematic review, comparison of two tools: the Newcastle-Ottawa Scale and the RTI item bank. Clin Epidemiol. 2014;6:359-68.	^***	^**	^*	^******	Low
Hotta et al., 2015²⁶26 Bushman TT, Grier TL, Canham-Chervak MC, Anderson MK, North WJ, Jones BH. Pain on Functional Movement Screen Tests and Injury Risk. J Strength Cond Res. 2015;29(Suppl 11):S65-70.	^***	-	^*	^****	High
Zalai et al., 2015²⁸28 Zalai D, Panics G, Bobak P, Csáki I, Hamar P. Quality of functional movement patterns and injury examination in elite-level male professional football players. Acta Physiol Hung. 2015;102(1):34-42.	^***	-	^*	^****	High
Tee et al., 2016³⁰30 Hägglund M, Waldén M, Bahr R, Ekstrand J. Methods for epidemiological study of injuries to professional football players: developing the UEFA model. Br J Sports Med. 2005;39(6):340-6.	^***	-	^*	^****	High

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[1] *PSB: Doctoral student, e-mail: priscilabunn@yahoo.com.br