| Literature DB >> 35020217 |
Tzvika Greenbaum1, Laurent Pitance2, Ron Kedem3, Alona Emodi-Perlman4.
Abstract
BACKGROUND: The mouth-opening muscular performance in patients with temporomandibular disorders (TMDs) is unclear. Understanding the impairments of this muscle group within specific TMDs is important to develop proper management strategies.Entities:
Keywords: jaw-opening force; mouth-opening force; muscle strength; suprahyoid muscle; temporomandibular disorders; temporomandibular joint
Mesh:
Year: 2022 PMID: 35020217 PMCID: PMC9303535 DOI: 10.1111/joor.13303
Source DB: PubMed Journal: J Oral Rehabil ISSN: 0305-182X Impact factor: 3.558
Search strategy (all databases); date of all searches: Nov. 11, 2020
| Database | Search strategy | Number of identified record |
|---|---|---|
| Embase | (‘mouth opening’ OR ‘jaw opening’ OR suprahyoid* OR ‘supra hyoid*’) AND (strength OR force$ OR power OR endurance) | 694 |
| MEDLINE | (("mouth opening" or "jaw opening" or suprahyoid* or ‘supra hyoid*’) and (strength or force? or power or endurance)).mp. | 500 |
| CINHAL | ("mouth opening" OR "jaw opening" OR suprahyoid* OR "supra hyoid*") AND (strength OR force# OR power OR endurance) | 127 |
| Web of Science | Search Strategy: ("mouth opening" OR "jaw opening" OR suprahyoid* OR "supra hyoid*") AND (strength OR force? OR power OR endurance) | 653 |
| Scopus | Search Strategy: TITLE‐ABS‐KEY ("mouth opening" OR "jaw opening" OR suprahyoid* OR "supra hyoid*") AND TITLE‐ABS‐KEY (strength OR force OR power OR endurance) | 431 |
| Cochrane CENTRAL | Search Strategy: ("mouth opening" OR "jaw opening" OR suprahyoid* OR ‘supra hyoid*’) AND (strength OR force? OR power OR endurance) | 101 |
| Total | 2506 | |
| Total after removing duplicates | 1051 | |
FIGURE 1Eligibility criteria for systematic review
FIGURE 2PRISMA flowchart of included and excluded studies
list of full text excluded and the reason for exclusion
| Study | Reason for exclusion |
|---|---|
| Nakamura, 2019 | Language (Japanese) |
| Slater, 2009 | Population (Cadaver) |
| Peck, 2000 | Outcome measure |
| Mimura, 1989 | Language (Japanese) |
| Lida, 2014 | Abstract only |
| Rodriguez, 2015 | Outcome measure |
| Pal, 2011 | Outcome measure |
| Chen, 2000 | Outcome measure |
| Ikebe, 2008 | Outcome measure |
| Namiki, 2020 | Abstract only |
| Hara, 2019 | Abstract only |
| Bolt, 1986 | Abstract only |
| Manda, 2016 | Outcome measure |
| Bakker, 1995 | Outcome measure |
| Nagashima, 1997 | Outcome measure |
| Hansdottir, 2004 | Outcome measure |
| Stefanie, 2010 | Abstract only |
| Johansson, 2014 | Outcome measure |
| Takanobu, 2001 | Outcome measure |
| Madani 2020 | Outcome measure |
| Nitzan, 1997 | Outcome measure |
| Abbink, 1998 | Outcome measure |
| De Felicio, 2007 | Language (Portuguese) |
| Clark, 1991 | Outcome measure |
| Koc 2012 | Outcome measure |
| Lin, 2010 | Outcome measure |
| Kilinc, 2015 | Outcome measure |
| Williams, 1988 | Outcome measure |
| Suenaga, 2000 | Outcome measure |
| Kameda, 2020 | Outcome measure |
| Tuijt, 2010 | Population (not described) |
| Wakasugi, 2017 | Population (Age) |
| Van, 1990 | Population (Age) |
| Ishida, 2015 | Outcome measure |
| Ma, 2013 | Outcome measure |
| Uchida, 1999 | Outcome measure |
| Osborn, 1995 | Outcome measure |
| Gelb, 1984 | Abstract only |
| Beom, 2015 | Population |
| Yoshida, 2006 | Language (Japanese) |
| Hara, 2018 | Language (Japanese) |
| Lequeux, 2005 | Outcome measure |
| Oh, 2020 | Outcome measure |
| Peck, 2002 | Outcome measure |
| Chandran, 2012 | Abstract only |
| Machida, 2017 | Population (Age) |
| Hara, 2018 | Population (Age) |
| Yuka, 2020 | Population (Age) |
| Yoshida, 2019 | Population (Age) |
| Yoshimi, 2018 | Population (Age) |
| Kajisa, 2018 | Population (Age) |
Characteristics of included studies
| Study | Design | Participants | Measurement instrument | Outcome measure |
|---|---|---|---|---|
| Brunton, 2018 | Cross‐sectional | Healthy ( | Adjustable rigid extra‐oral device (ad hoc) | Maximal mouth opening force/strength |
| Curtis, 2019 | Cross‐sectional | Healthy ( | Hand‐held dynamometer | Maximal mouth opening force/strength |
| Häggman‐Henrikson, 2018 | Clinical trial | TMD ( | Adjustable rigid extra‐oral device (ad hoc) | Mouth opening endurance |
| Hara, 2018 | Cross‐ sectional | Healthy ( | Jaw‐opening sthenometer (Livert) | Maximal mouth opening force/strength |
| Lida, 2013 | Case control | Healthy (age <70 year; | Jaw‐opening sthenometer (Livert) | Maximal mouth opening force/strength |
| Koyama, 2005 | Reliability study | Healthy ( | Adjustable rigid extra‐oral device | Maximal mouth opening force/strength |
| Ogawa, 2020 | RCT | Healthy men ( | Jaw‐opening sthenometer (Livert) | Maximal mouth opening force/strength |
| Ratnayake, 2020 | Case control | TMD ( | Adjustable rigid extra‐oral device | Maximal mouth opening force/strength |
| Sharkey, 1984 | Cross‐ sectional | Healthy ( | Adjustable rigid extra‐oral device | Maximal mouth opening force/strength |
| Takuro, 2018 | Cross‐ sectional | Healthy ( | Not described | Maximal mouth opening force/strength |
| Wänman, 2012 | Case control | TMD ( | Adjustable rigid extra‐oral device (ad hoc) | Mouth opening endurance |
| Watanabe, 1991 | Cross‐ sectional | Healthy ( | Adjustable rigid extra‐oral device (ad hoc) | Maximal mouth opening force/strength |
| Watanabe, 2001 | Cross‐ sectional | Healthy ( | Adjustable rigid extra‐oral device (ad hoc) | Maximal mouth opening force/strength |
| Xu, 2020 | Cross‐ sectional | Healthy ( | Adjustable rigid extra‐oral device (ad hoc) | Maximal mouth opening force/strength |
Main findings of included studies
| Population | Study | Main findings | Risk for bias |
|---|---|---|---|
| Healthy | Brunton, 2018 | Men had greater maximum opening force median values than women; Maximal mouth opening strength: Men 8 ± 6.6 kg; Women 4.2 ± 3.1 | Moderate |
| Curtis, 2019 | Age and sex significantly influenced the mouth opening maximal force; Maximal mouth opening strength: Male 24.9 ± 4.5; Female 14.7 ± 3.2 | Moderate | |
| Hara, 2018 | Sex significantly influenced the maximal mouth opening strength (Male >Female); Maximal mouth opening strength: Male 7.2 ± 2.3; Female 4.3 ± 1.7 | Moderate | |
| Koyama, 2005 | There was a significant gender difference in the average maximum mouth opening force. There was an extremely high correlation between first and second measurements ( | Moderate | |
| Lida, 2013 | Sex significantly influenced the maximal mouth opening strength (Male > Female); Maximal mouth opening strength: Male 9.7 ± 2.8; Female 5.9 ± 1.6 kg Male 9.7 ± 2.8; Female 5.9 ± 1.6 kg | Low | |
| Ogawa, 2020 | Maximal mouth opening strength: Group 1 (pre‐intervention) = 8.7(1.9); Group 2 (pre‐internevtion) = 8.6(1.5) | Moderate | |
| Ratnayake, 2020 | Maximal mouth opening strength: TMD free 4.8 ± 0.15; | Moderate | |
| Sharkey,1984 | Male were significantly stronger than female; Maximun maximal mouth‐opening force accured in the mid‐range Maximal mouth opening strength:Men 13.8 ± 6.1; Women 9.1 ± 2.0 | Moderate | |
| Takuro, 2018 | Men were significantly stronger than women; Maximal mouth opening strength: Men 9.2 ± 2.8; Women 6 ± 2.3 | High | |
| Watanabe,1991 | The theoretical maximal mouth opening strength was 32.55 ± 4.98 | High | |
| Watanabe, 2001 | The theoretical maximal mouth opening strength was 36.62 ± 9.42 | High | |
| Wänman, 2012 | Mean time to stop the jaw opening‐closing endurance task: Controls 278 ± 59 (seconds) | High | |
| Xu, 2020 | The median of maximal mouth opening strength was higher in males (5.5) than females (3.4) ( | Moderate | |
| TMD's | Häggman‐Henrikson, 2018 | The "general pain" TMD (according to DC/TMD) group had lower endurance than the "local pain" TMD group (DC/TMD) in both jaw opening and protrusions. No accurate numbers are described but rather only box plots | Moderate |
| Ratnayake, 2020 | With all five measurements used, this ICC was 0.996 (95% CI: 0.994 to 0.997), indicating extremely high reliability; TMD‐free participants had greater jaw‐opening forces than TMD patients (diagnosed according to DC‐TMD) both without and with adjustments for age, sex, height, and weight; No significant difference between TMD subgroups. Maximal mouth opening strength: TMD patients 1.8 ± 0.16; TMD free 4.8 ± 0.15 | Moderate | |
| Wänman, 2012 | Significant lower endurance was found for TMD's (diagnosed according to DC‐TMD) compared to healthy controls. Mean time to stop the jaw opening‐closing endurance task: TMD's 118 ± 96 (seconds); Controls 278 ± 59 | High |
(a) Risk of bias assessment of cross‐sectional studies according to the NIH quality assessment tool. (b) Risk of bias assessment of case‐control studies according to the SIGN quality assessment tool
| (a) | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Study | Design | Focused question | Comparable populations | Same exclusion criteria | Comparison participants/ non‐participants | Cases are clearly defined and differentiated from controls | It is clearly established that controls are non‐cases | Blinding of assessors | Exposure status is measured in a standard, valid and reliable way | Confounders are identified and considered | Confidence intervals are provided | Clear association between exposure and outcome | Applicability of study | Risk of Bias |
| Hֳaggman‐Henrikson, 2018 | Clinical trial | Yes | Yes | Yes | No | Yes | No | No | Yes | Yes | Yes | No | No | Moderate (7/12) |
| Lida, 2013 | Case control | Yes | Yes | Yes | No | Yes | Yes | No | Yes | Yes | Yes | Yes | Yes | Low (10/12) |
| Ratnayake, 2020 | Case control | Yes | Yes | No | No | Yes | Yes | No | Yes | Yes | Yes | Yes | Yes | Moderate (9/12) |
| Wֳanman, 2012 | Case control | Yes | Yes | Yes | No | Yes | Yes | No | Yes | No | No | No | No | High (6/12) |
|
SIGN | Methodology Checklist 4: Case‐control studies | ||
|---|---|---|---|
| Study identification (Include author, title, year of publication, journal title, pages) | |||
| Guideline topic: | Key Question No: | Reviewer: | |
|
Before completing this checklist, consider: 1. Is the paper really a case‐control study? If in doubt, check the study design algorithm available from SIGN and make sure you have the correct checklist. 2. Is the paper relevant to key question? Analyse using PICO (Patient or Population Intervention Comparison Outcome). IF NO REJECT (give reason below). IF YES complete the checklist. | |||
| Reason for rejection: Reason for rejection: 1. Paper not relevant to key question □ 2. Other reason □ (please specify): | |||
| Section 1: Internal validity | |||
| In an well conducted case control study: | Does this study do it? | ||
| 1.1 | The study addresses an appropriate and clearly focused question. |
Yes □ Can't say □ | No □ |
| Selection of subjects | |||
| 1.2 | The cases and controls are taken from comparable populations. |
Yes □ Can't say □ | No □ |
| 1.3 | The same exclusion criteria are used for both cases and controls. |
Yes □ Can't say □ | No □ |
| 1.4 | What percentage of each group (cases and controls) participated in the study? | Cases: Controls: | |
| 1.5 | Comparison is made between participants and non‐participants to establish their similarities or differences. |
Yes □ Can't say □ | No □ |
| 1.6 | Cases are clearly defined and differentiated from controls. |
Yes □ Can't say □ | No □ |
| 1.7 | It is clearly established that controls are non‐cases. |
Yes □ Can't say □ | No □ |
| Assessment | |||
| 1.8 | Measures will have been taken to prevent knowledge of primary exposure influencing case ascertainment. |
Yes □ Can't say □ |
No □ Does not apply □ |
| 1.9 | Exposure status is measured in a standard, valid and reliable way. |
Yes □ Can't say □ | No □ |
| Confounding | |||
| 1.10 | The main potential confounders are identified and taken into account in the design and analysis. |
Yes □ Can't say □ | No □ |
| Statistical analysis | |||
| 1.11 | Confidence intervals are provided. | Yes □ | No □ |
| Section 2: Overall assessment of the study | |||
| 2.1 | How well was the study done to minimise the risk of bias or confounding? |
High quality (++) □ Acceptable (+) □ Unacceptable – reject 0 □ | |
| 2.2 | Taking into account clinical considerations, your evaluation of the methodology used, and the statistical power of the study, do you think there is clear evidence of an association between exposure and outcome? |
Yes □ Can't say □ | No □ |
| 2.3 | Are the results of this study directly applicable to the patient group targeted by this guideline? | Yes □ | No □ |
| 2.4 | Notes. Summarise the authors conclusions. Add any comments on your own assessment of the study, and the extent to which it answers your question and mention any areas of uncertainty raised above. | ||
Unless a clear and well defined question is specified in the report of the review, it will be difficult to assess how well it has met its objectives or how relevant it is to the question you are trying to answer on the basis of the conclusions.
Study participants may be selected from the target population (all individuals to which the results of the study could be applied), the source population (a defined subset of the target population from which participants are selected), or from a pool of eligible subjects (a clearly defined and counted group selected from the source population. If the study does not include clear definitions of the source population it should be rejected.
All selection and exclusion criteria should be applied equally to cases and controls. Failure to do so may introduce a significant degree of bias into the results of the study.
Differences between the eligible population and the participants are important, as they may influence the validity of the study. A participation rate can be calculated by dividing the number of study participants by the number of eligible subjects. It is more useful if calculated separately for cases and controls. If the participation rate is low, or there is a large difference between the two groups, the study results may well be invalid due to differences between participants and non‐participants. In these circumstances, the study should be downgraded, and rejected if the differences are very large.
Even if participation rates are comparable and acceptable, it is still possible that the participants selected to act as cases or controls may differ from other members of the source population in some significant way. A well conducted case‐control study will look at samples of the non‐participants among the source population to ensure that the participants are a truly representative sample.
The method of selection of cases is of critical importance to the validity of the study. Investigators have to be certain that cases are truly cases, but must balance this with the need to ensure that the cases admitted into the study are representative of the eligible population. The issues involved in case selection are complex, and should ideally be evaluated by someone with a good understanding of the design of case‐control studies. If the study does not comment on how cases were selected, it is probably safest to reject it as a source of evidence.
Just as it is important to be sure that cases are true cases, it is important to be sure that controls do not have the outcome under investigation. Control subjects should be chosen so that information on exposure status can be obtained or assessed in a similar way to that used for the selection of cases. If the methods of control selection are not described, the study should be rejected. If different methods of selection are used for cases and controls the study should be evaluated by someone with a good understanding of the design of case‐control studies.
If there is a possibility that case ascertainment can be influenced by knowledge of exposure status, assessment of any association is likely to be biased. A well conducted study should take this into account in the design of the study.
The primary outcome measures used should be clearly stated in the study. If the outcome measures are not stated, or the study bases its main conclusions on secondary outcomes, the study should be rejected. Where outcome measures require any degree of subjectivity, some evidence should be provided that the measures used are reliable and have been validated prior to their use in the study.
Confounding is the distortion of a link between exposure and outcome by another factor that is associated with both exposure and outcome. The possible presence of confounding factors is one of the principal reasons why observational studies are not more highly rated as a source of evidence. The study should indicate which potential confounders have been considered, and how they have been allowed for in the analysis. Clinical judgement should be applied to consider whether all likely confounders have been considered. If the measures used to address confounding are considered inadequate, the study should be downgraded or rejected. A study that does not address the possibility of confounding should be rejected.
Confidence limits are the preferred method for indicating the precision of statistical results, and can be used to differentiate between an inconclusive study and a study that shows no effect. Studies that report a single value with no assessment of precision should be treated with extreme caution.
Rate the overall methodological quality of the study, using the following as a guide: High quality (++): Majority of criteria met. Little or no risk of bias. Results unlikely to be changed by further research. Acceptable (+): Most criteria met. Some flaws in the study with an associated risk of bias, Conclusions may change in the light of further studies. Low quality (0): Either most criteria not met, or significant flaws relating to key aspects of study design. Conclusions likely to change in the light of further studies.
| Criteria | Yes | No | Other (CD, NR, NA) |
|---|---|---|---|
| 1. Was the research question or objective in this paper clearly stated? | |||
| 2. Was the study population clearly specified and defined? | |||
| 3. Was the participation rate of eligible persons at least 50%? | |||
| 4. Were all the subjects selected or recruited from the same or similar populations (including the same time period)? Were inclusion and exclusion criteria for being in the study prespecified and applied uniformly to all participants? | |||
| 5. Was a sample size justification, power description, or variance and effect estimates provided? | |||
| 6. For the analyses in this paper, were the exposure(s) of interest measured prior to the outcome(s) being measured? | |||
| 7. Was the timeframe sufficient so that one could reasonably expect to see an association between exposure and outcome if it existed? | |||
| 8. For exposures that can vary in amount or level, did the study examine different levels of the exposure as related to the outcome (e.g., categories of exposure, or exposure measured as continuous variable)? | |||
| 9. Were the exposure measures (independent variables) clearly defined, valid, reliable, and implemented consistently across all study participants? | |||
| 10. Was the exposure(s) assessed more than once over time? | |||
| 11. Were the outcome measures (dependent variables) clearly defined, valid, reliable, and implemented consistently across all study participants? | |||
| 12. Were the outcome assessors blinded to the exposure status of participants? | |||
| 13. Was loss to follow‐up after baseline 20% or less? | |||
| 14. Were key potential confounding variables measured and adjusted statistically for their impact on the relationship between exposure(s) and outcome(s)? |
| Quality Rating (Good, Fair, or Poor) |
| Rater #1 initials: |
| Rater #2 initials: |
| Additional Comments (If POOR, please state why): |
CD, cannot determine; NA, not applicable; NR, not reported.