Criteria for considering studies for this review
Types of studies
We will only include trials that are randomised or quasi-randomised. Quasi-random methods of assignment to interventions are systematic methods that are not truly random, such as allocation using alternation, date of birth, day of visit or medical record number.
If the trial report does not include a clear description of the method of randomisation, one of our review authors (HSS) will contact the trial authors to clarify whether proper random assignment took place. If the method of random assignment remains unclear, we will include the trial and describe its limitations. We will include parallel and cross-over trials that assess the efficacy of acupuncture or related interventions. We will include eligible studies regardless of language and publication status.
Types of participants
Adults (18 years or over) with CTS in one or both hands, as diagnosed by any validated criteria, including electrodiagnostic parameters such as nerve conduction velocity or relevant clinical diagnostic criteria with definite clinical symptoms and physical examination results. We will document and reference the study authors' diagnostic criteria for CTS in the table of included studies.
Types of interventions
We will include all types of acupuncture as well as related interventions that do not involve puncturing the skin, such as acupressure, laser acupuncture, and moxibustion (heat stimulation on acupoints by heating the mugwort herb). The control interventions will be no treatment, placebo/sham treatment, and relevant active interventions such as steroid nerve blocks, splints, surgery, drugs or physical therapy. We will allow co-interventions if they were given to both experimental and control groups equally.
Types of outcome measures
We will include studies if the protocol includes the measurement of at least one clinical outcome related to neuropathic symptoms (for example, response, frequency or intensity of pain, disability, quality of life or analgesic use). We will exclude studies reporting only physiological parameters, as well as studies with outcome measurement periods of less than three weeks from randomisation to final observation. We will assess all outcomes as short-term, defined as three months or less, and long-term, defined as greater than three months.
The primary outcome measure will be overall clinical improvement at short-term follow-up (less than or equal to three months), preferentially as measured by questionnaires such as patient global impression of change measured by any validated method (for example the seven-point Likert scale or similar). The primary outcome will be measured as either a continuous variable or a dichotomous outcome (e.g. patients improved or very improved versus no change or worsened).
Overall clinical improvement at long term (greater than three months), measured as for the primary outcome
Pain (e.g. a visual analogue scale (VAS), numerical rating scales (three months or less), measured as magnitude of change and as 30% and 50% improved.
Grip, pinch strength
Improvement in functional status and/or health-related quality of life parameters (measured, for example, by the Short Form 36 (SF-36) Health Survey (Hawthorne 2007), EuroQol5-D (EQ5-D))
Any adverse events, adverse events leading to cessation of treatment and serious adverse events defined as those which are fatal, life-threatening, or require prolonged hospitalisation
Summary of findings table
We will create a 'Summary of findings' table with the key outcomes of overall clinical improvement at short term follow-up, overall clinical improvement at long term follow-up and adverse events, using the GRADEprofiler software (GRADEpro 2008). We will use the five Grading of Recommendations Assessment, Development and Evaluation (GRADE) considerations (study limitations, consistency of effect, imprecision, indirectness and publication bias) to assess the quality of a body of evidence (studies that contribute data for the prespecified outcomes). We will use methods and recommendations described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We will justify all decisions to down- or up-grade the quality of studies using footnotes and we will make comments to aid reader's understanding of the review where necessary.
Search methods for identification of studies
We will search the Cochrane Neuromuscular Disease Group Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL) (current issue in The Cochrane Library), MEDLINE (January 1966 to present), EMBASE (January 1980 to present), AMED (January 1985 to present), CINAHL Plus (January 1937 to present), six Korean medical databases (i.e., DBPIA, Korea Institute of Science and Technology Information, The National Library of Korea, Korean traditional knowledge portal, OASIS and KoreaMed) from inception to present, and various Chinese medical databases (China Academic Journal from the China National Knowledge Infrastructure (CNKI) (http://oversea.cnki.net/kns55/), http://www.cqvip.com, Wanfang Data (http://www.wanfangdata.com/)) from inception to present.
We will also search the WHO International Clinical Trials Registry Platform (ICTRP) search portal (http://apps.who.int/trialsearch/) and the U.S. National Institutes of Health ClinicalTrials.gov (http://www.clinicaltrials.gov) for ongoing trials. There will be no language restriction in the search strategy. The detailed search strategy for MEDLINE is in Appendix 1. We will adapt this search strategy and language as appropriate for the other electronic databases.
We will also search the National Institute for Health Research Database of Abstracts and Reviews of Effects (DARE) and Health Technology Assessments (HTA) databases to identify reviews and assessments for inclusion in the 'Discussion' section. We will search National Health Service Economic Evaluation Database (NHS EED) for any available cost information and include any information on costs in the 'Discussion' section.
Searching other resources
We will review the reference lists of relevant articles and contact experts in the field (for example, authors of included studies) for information on additional trials, including unpublished or ongoing studies.
Data collection and analysis
Selection of studies
Two review authors (HSS and BCS) will independently screen the titles and abstracts of all retrieved references to assess whether or not studies satisfy the inclusion criteria. We will exclude any studies which clearly do not fulfil the inclusion criteria. Two review authors (HSS and BCS) will independently evaluate the full-text articles of possibly relevant studies to determine whether they meet the inclusion criteria. Authors will resolve any disagreement by discussion and consensus. We will identify and exclude duplicates and collate multiple reports of the same study so that each study rather than each report is the unit of interest in the review. We will include a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart to illustrate the study selection process (Moher 2009).
Data extraction and management
Two review authors (HSS and BCS) will independently extract data using a standard pre-defined data extraction form.
We will extract the following study characteristics.
Methods: study design, total duration of study, details of any 'run in' period, number of study centres and location, study setting, withdrawals, and date of study.
Participants: number of participants, mean age, age range, gender, severity of condition, diagnostic criteria, baseline characteristics, inclusion criteria, and exclusion criteria.
Interventions: intervention, comparison, concomitant medications, and excluded medications.
Outcomes: primary and secondary outcomes specified and collected, and time points reported.
Notes: funding for trial, and notable conflicts of interest of trial authors.
Two review authors (HSS and BCS) will independently extract outcome data from included studies. We will note in the 'Characteristics of included studies' tables if outcome data were not reported in a usable way. We will resolve disagreements by discussion. One review author (HSS) will transfer data into the Cochrane Collaboration's statistical software, Review Manager 2014, and a second author (BCS) will check the outcome data entries.
When reports require translation, the translator will extract data directly using a data extraction form, or an author (HSS) will extract data from the translation provided. Where possible a review author (BCS) will check numerical data in the translation against the study report.
Assessment of risk of bias in included studies
Two review authors (HSS and BCS) will use the Cochrane Collaboration's tool for assessing risk of bias to independently evaluate the risk of bias for each trial as high, low or unclear in the following seven domains (Higgins 2011).
Sequence generation (selection bias)
Allocation concealment (selection bias)
Blinding of participants and personnel (performance bias)
Blinding of outcome assessment (detection bias)
Incomplete outcome data (attrition bias)
Selective outcome reporting (reporting bias)
Other risk of bias (we will consider whether the unit of analysis was appropriate).
The review authors will resolve disagreements by discussion. Where information on risk of bias relates to unpublished data or correspondence with a trialist, we will note this in the 'Risk of bias' tables.
Measures of treatment effect
For dichotomous data we will use risk ratios (RRs) with 95% confidence intervals (CIs).
For continuous outcomes measured with the same scale we will use mean differences (MDs) and 95% CIs. If different scales have been used to measure the same underlying concept (for example, different measures of pain), we will use the standardised mean differences (SMDs) and 95% CIs.
We will undertake meta-analyses only where this is meaningful i.e. if the treatments, participants and the underlying clinical question are similar enough for pooling to make sense.
We will narratively describe skewed data reported as medians and interquartile ranges.
Where multiple trial arms are reported in a single trial, we will include only the relevant arms. If two comparisons (e.g. drug A versus placebo and drug B versus placebo) are combined in the same meta-analysis, we will halve the control group to avoid double-counting.
Unit of analysis issues
Bilateral involvement is common in CTS. We will seek information about the unit of randomisation (that is, hands or participants) for studies that include participants with bilateral CTS. If participants with bilateral CTS received interventions for both hands, we will examine the study reports to see whether analyses were conducted using methods that take into account the dependency of observations (for example, matched analyses, generalised estimating equations (GEE), methods for cluster randomise trials). If appropriate analyses are not reported, we will contact the authors for individual outcome data of each hand. If such data are not available, we will evaluate the degree of dependence by collecting the crude estimate of the number of randomised participants with bilateral involvement and use sensitivity analyses to evaluate whether the results for bilateral involvement in individual trials might change the conclusions.
Dealing with missing data
Data from intention-to-treat (ITT) analyses will be our first choice when available. If data for key study characteristics or primary outcomes are missing or incomplete, we will contact the trial authors to obtain the missing data, and we will record the analysis method. When missing data are not obtainable and are thought to introduce serious bias, we will explore the impact of including such studies in the overall assessment of results by a sensitivity analysis.
Assessment of heterogeneity
We will include various types of acupuncture in this review and this may lead to heterogeneity. We will assess clinical heterogeneity (namely differences in study populations, interventions, and outcomes) between studies qualitatively. If we judge studies to be sufficiently clinically homogenous, we will combine them using meta-analysis, and assess statistical heterogeneity using the I2 statistic for evaluating heterogeneity (Higgins 2002). I2 values of 50% and more indicate a substantial level of heterogeneity (Higgins 2003). If there is substantial heterogeneity, we will try to determine what the potential reasons are by examining individual study characteristics.
Assessment of reporting biases
For analyses including at least 10 trials, we will use funnel plots to assess possible reporting bias (Sterne 2011). Funnel plot asymmetry may be a result of reporting bias, but it may also be a result of other factors such as poor methodological quality of smaller studies, true effect size heterogeneity in different size studies or chance and we will interpret any observed asymmetry carefully (Sterne 2011).
We will combine data from individual studies when trials are sufficiently similar in terms of participants, intervention, control intervention, outcome measure, and timing of outcome assessment. We will use a random-effects model in all meta-analyses, and perform sensitivity analyses using a fixed-effect model. If meta-analyses are impossible, we will present the trials systematically and use the GRADE approach to assess the overall quality of the evidence. If the review includes more than one comparison that cannot be included in the same analysis, we will report the results for each comparison separately.
Subgroup analysis and investigation of heterogeneity
If sufficient studies are available, we will analyse subgroups based on acupuncture types (electrical acupuncture, laser acupuncture, acupressure, moxibustion, other types of heat stimulation on acupuncture points and other acupuncture-related interventions) to investigate different effects between types of acupuncture.
If sufficient studies are available, we will conduct sensitivity analyses to explore the influence of various study characteristics and to test the robustness of the results. We will repeat analyses excluding studies which have the following greater risk of bias:
high risk of bias (that is, in sequence generation, allocation concealment or blinding in the assessment of outcomes);
small sample sizes (less than 40 participants) (Moore 1998);
no available information about outcomes for individual hands, in studies where participants had bilateral CTS and received interventions for both hands but appropriate analyses were not conducted (Unit of analysis issues).
We will also test the robustness of the result by repeating all meta-analyses using fixed-effect models.
We will base our conclusions only on findings from the quantitative or narrative synthesis of included studies for this review. We will avoid making recommendations for practice and our implications for research will suggest priorities for future research and outline what the remaining uncertainties are in the area.