Chinese herbal medicines for skin and soft tissue infections

  • Protocol
  • Intervention

Authors

  • Yun Fei Wang,

    1. Longhua Hospital affiliated to Shanghai University of Traditional Chinese Medicine, Department of Traditional Chinese Surgery, Shanghai, Shanghai, China
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  • Hua Fa Que,

    Corresponding author
    1. Longhua Hospital affiliated to Shanghai University of Traditional Chinese Medicine, Department of Traditional Chinese Surgery, Shanghai, Shanghai, China
    • Hua Fa Que, Department of Traditional Chinese Surgery, Longhua Hospital affiliated to Shanghai University of Traditional Chinese Medicine, 725 South Wan-ping Road, Shanghai, Shanghai, 200032, China. quehuafa@126.com.

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  • Yong-Jun Wang,

    1. Longhua Hospital affiliated to Shanghai University of Traditional Chinese Medicine, Department of Orthopedics and Traumatology, Shanghai, China
    2. Longhua Hospital affiliated to Shanghai University of Traditional Chinese Medicine, Research Institute of Spine Diseases, Shanghai, China
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  • Xue Jun Cui

    1. Longhua Hospital affiliated to Shanghai University of Traditional Chinese Medicine, Centre of Clinical Evaluation, Shanghai, Shanghai, China
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Abstract

This is the protocol for a review and there is no abstract. The objectives are as follows:

To evaluate the effects and side effects of Chinese herbal medicines for healing skin and soft tissue infections.

Background

Skin and soft tissue infections (SSTIs) are common infections of the epidermis, dermis or subcutaneous tissue (Stevens 2005). They include impetigo; abscesses, cellulitis and erysipelas; infections following animal and human bites; soft tissue infections following animal contact; infections in people whose immune systems are compromised and infections related to iatrogenic procedures.

SSTIs were described by Celsus in the first century as 'calor, rubor, tumor and dolor' (heat, redness, swelling and pain) (Dryden 2010). They may be accompanied by signs and symptoms of systemic toxicity such as fever, malaise, nausea, hypothermia, tachycardia (more than 100 beats per minute) and hypotension (systolic blood pressure less than 90 mmHg or 20 mmHg below baseline).

For most people the condition is treatable with antibiotics (Morris 2001), but longer-term problems, such as persistent swelling, recurrent episodes, bacterial resistance and side effects of the medication, can occur. Many patients with SSTIs are therefore increasingly turning to complementary and alternative medicine (CAM), including Chinese herbal medicines, in order to alleviate their symptoms and reduce the side effects of medications.

Description of the condition

SSTIs are common and range in severity from minor, self limiting, superficial infections to life-threatening diseases, with or without open wounds/ulcers. There are many important underlying aetiologies, in particular diabetes. Classification of SSTIs can be based on anatomical site, clinical severity or microbial cause, however some classifications (such as that of the US Food and Drug Administration (FDA)) divide SSTIs into 'complicated' and 'uncomplicated' infections. Uncomplicated SSTIs are superficial infections amenable to treatment with antibiotics plus simple surgical incision where appropriate (e.g. simple abscesses, carbuncles, impetigo lesions, furuncles, cellulitis). Complicated SSTIs are infections involving the deeper tissues, such as subcutaneous tissue, fascia and skeletal muscle or SSTIs in people with co-morbidities such as diabetes mellitus, HIV and other immunocompromised states (FDA 1998). Complicated SSTIs can be non-necrotising or necrotising.

The microbial causes of SSTIs have been recorded over some years in the SENTRY Antimicrobial Surveillance Program database. Their report, which presented data over a seven-year period (1998 to 2004) ranked SSTIs by frequency of pathogen: Staphylococcus aureus (42.8%), Pseudomonas aeruginosa (11.1%), Escherichia coli (9.0%), Enterococcus spp. (7.3%), Klebsiella spp. (4.8%), Enterobacter spp. (4.7%), β-haemolytic streptococci (4.3%), coagulase-negative staphylococci (4.0%), Proteus mirabilis (2.5%) and Acinetobacter spp. (2.1%) (Fritsche 2007). However, with the rise in the number of community-acquired methicillin-resistant S. aureus (MRSA)-related infections (Kluytmans-Vandenbergh 2006; Purcell 2005), this picture may change in the future. 

SSTIs are frequently encountered in both community and hospital settings, but few published data are found on their incidence. According to the Centers for Disease Control and Prevention (CDC), 562,000 people were discharged with a hospital-acquired SSTIs and SSTIs were the third most common cause of nosocomial infections (Bounthavong 2010). A cohort study conducted in the USA from 1997 to 2002 indicated a higher incidence of 246 per 10,000 person-years (Ellis Simonsen 2006). In England alone, people admitted with a diagnosis of SSTIs took up to 360,000 bed-days (UKDOH 2001). The morbidity and treatment costs associated with SSTIs are high, and treatment has become more complex due to the increasing prevalence of multiple-drug resistant pathogens. During the past decade the prevalence of antibiotic resistance among Gram-positive cocci (particularly S. aureus) has increased sharply. A considerable variation in the MRSA rate has been noted between countries and continents. According to the report of the SENTRY Antimicrobial Surveillance Program, the highest MRSA rate was observed in North America (35.9%), compared with Latin America (29.4%) and Europe (22.8%). However, the MRSA rate varied considerably among European countries, ranging from 0.8% in Sweden to 50% in Portugal (Fritsche 2007). Variability in MRSA rates was also apparent in Latin America: Mexico (50%), Chile (38%), Brazil (29%), Argentina (28%) and Colombia and Venezuela combined (3%) (Moet 2007). Antibiotic resistance increases the length of stay in hospital, costs of treatment and mortality. A review of the epidemiology of severe S. aureus infections in Europe reported that the overall seven-day case fatality rate was 19% (Lamagni 2008). A US study reported that people with MRSA-infected surgical sites had a three times greater 90-day mortality rate and a greater duration of hospitalisation after infection (median additional days = 5; P < 0.001) than people infected by methicillin-sensitive S. aureus (MSSA). Median hospital charges were USD 92,363 for people with MRSA infections (Engemann 2003). 

Description of the intervention

Uncomplicated and complicated SSTIs are treated differently and have different clinical outcomes. Uncomplicated SSTIs are usually treated with local care with or without antibiotics, while the treatment of the most complicated SSTIs involves timely surgical debridement or drainage, appropriate antibiotic therapy, and resuscitation if required (Dryden 2010). The most frequently used broad-spectrum antibiotics to treat SSTIs are β-lactams, glycopeptides, oxazolidinones (Fung 2003). However, there is variation in practice and treatment options for SSTIs include many different oral and intravenous antibiotics. Infections are diagnosed and treated by general practitioners, emergency department doctors, dermatologists, paediatricians, surgeons and physicians from a variety of sub-specialties (British Lymphology Society 2007; CREST 2005; Eron 2003; Société Française de Dermatologie 2001; Stevens 2005). 

Conventional treatments for SSTIs include antibiotics, non-steroidal anti-inflammatory drugs (NSAIDs) and physical therapy. Treatment with antibiotics and NSAIDs is limited by high treatment costs, bacterial resistance and side effects. Many people may not be good candidates for these therapies because of their co-morbidities, advancing age or preference for Chinese herbal medicine treatment. Chinese herbal medicines have been shown to have the potential to reduce the adverse effects of medications.(Ernst 1995; Neil 1994; Westphal 1996). Chinese herbal medicines, which are natural substances, have been used to promote healing and alleviate pain in many countries, such as Singapore, Thailand and Japan. In China, many people with SSTIs are increasingly turning to CAM, including Chinese herbal medicines. However, they are not totally without side effects and, for example, some people have reported experiencing diarrhoea (H Maechel 1992), sleep disturbance (Wilkie 1994) and nephropathy (Lin 1994). 

Chinese herbal medicines form the main part of Traditional Chinese Medicine (TCM), which has been used for centuries in China. Within the framework of TCM Chinese herbal medicines always include herbs, animal or insect products, or minerals, however they are often combined in one formula. An audit of 117 original research reports involving TCM or other natural products in the Chinese Medical Journal (2000 to 2009) found that there were different materia medica described in these reports: 74.4% were derived exclusively from plant material, 10.3% from animals, 3.4% from fungi, 1.7% from minerals and 10.3% were of mixed (plant/animal/fungal/mineral) composition (Collins 2011). Chinese herbal medicines are now included in the national essential drugs list of China. The Chinese State Food and Drug Administration enforces strict controls on the sale, inspection, and record keeping relating to Chinese herbal medicines ( CPC 2010). Chinese herbal medicines are defined in this review as products derived from raw or refined plants or parts of plants (e.g. leaves, buds, flowers, stems, roots or tubers), minerals (e.g. borneol) and/or animals (e.g. prepared centipede or earthworm), and used for the treatment of disease. There are four kinds of herbal therapies: single herb, Chinese proprietary medicines, mixtures of different herbs and any one of the aforementioned three therapies plus Western pharmaceuticals, also known as integrative medicinal treatment (Liu 2008; Vickers 1999). 

TCM has unique theories regarding systems of diagnosis, aetiology and treatment. These theories are vital to its practice and include Yin-Yang, the five elements (fire, earth, metal, water and wood), Qi (vital energy) and blood, Zang-Fu (five viscera and six bowels), and channels and collaterals (meridian doctrine) (Cheng 2000; Liu 1991). Chinese herbalists prescribe the mixture of herbs depending on the signs and symptoms the patient is experiencing and other disease information derived from four examinations. The four examinations include: observation; listening and smelling; inquiring; and feeling the pulse and palpation. Chinese herbalists analyse these to detect the cause and location of the disease and the relationship between pathogenic factors and vital energy; they then prescribe the mixture of herbs. Although based on well-established and long-standing recipes, Chinese proprietary medicines are usually formulated as tablets or capsules for convenience, commercial reasons or palatability.

Herbal medicines have been used for SSTIs, and aim to clear heat and eliminate toxins, improve circulation and dispel blood stasis. They can be used orally or topically, alone or in combination with conventional Western medicine.

How the intervention might work

Depending on the symptoms or causes, various medicinal herbs are used for treating SSTIs. In China, Chinese herbs are generally considered to be effective and are commonly prescribed by physicians for patients with SSTIs. Some Chinese herbs are considered to have antibacterial and anti-inflammatory properties. In pharmacological experiments Radix scutellariae has been shown to have antiphlogistic properties (Huang 1990), Coptis chinensis has antibacterial activity against Gram-positive bacteria (Kim 2004) and Sophora flavescens has anti-inflammatory and antiproliferative activities (Zhou 2009). Although these properties have been observed, it is unclear how they work.

Why it is important to do this review

SSTIs cause a heavy public health and economic burden and many sufferers consult CAM practitioners for their symptoms. Therefore there is a need to review the current clinical evidence systematically to inform current practice and guide future studies on Chinese herbal medicines for SSTIs.

Objectives

To evaluate the effects and side effects of Chinese herbal medicines for healing skin and soft tissue infections.

Methods

Criteria for considering studies for this review

Types of studies

Randomised controlled trials (RCTs) that evaluate the effects of herbal medicines for treating skin and soft tissue infections. We will exclude quasi-randomised trials because these trials are at high risk of selection bias.

Types of participants

People of any age with SSTIs irrespective of the diagnostic criteria used and underlying aetiologies (e.g. cellulitis, erysipelas, furuncles, simple abscesses, wound infections and deeper infections such as necrotising fasciitis, myositis and gas gangrene). We will exclude trials in people with diabetic gangrene or surgical site infections.

Types of interventions

Chinese herbal medicines applied systemically or topically (or both), including extracts from herbs, single herbs, Chinese proprietary medicines or a combination of herbs prescribed by a Chinese practitioner (called "individualised treatment"). There will be no limit on approval status, formulation or mode of administration for herbal medicines. 

We will group the interventions as follows:

  • single herb;

  • Chinese proprietary herbal medicine (a fixed formulation of herbs produced by a pharmaceutical company, usually taken as pills, capsules or tablets);

  • herbal mixture prescribed by herbalist (so called individualised treatment), usually tailored based on an individual's pattern of symptoms.

Comparison

Comparisons will include placebo, standard care (including antibiotics), a non-medical treatment (for example, surgical procedure) or other interventions used with the intention of glycaemic control, promotion of healing or wound care. We will consider studies with co-interventions as long as there is no systematic difference in co-interventions between arms.

Types of outcome measures

We will consider all reported outcomes at all time points.

Primary outcomes
  • Healing (healing is defined as either the resolution of all clinical signs and symptoms of infection, as assessed by laboratory test or as defined by trialists) either as time to healing or proportion healed.

Secondary outcomes
  • Adverse events

  • Duration of hospital stay

  • Duration of treatment

  • Costs

  • Mortality

Search methods for identification of studies

Electronic searches

We will search the following databases: 

  • Cochrane Wounds Group Specialised Register (latest);

  • Cochrane Skin Group Specialised Register (latest);

  • Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library - latest issue);

  • Ovid MEDLINE (1950 to current);

  • Ovid EMBASE (1980 to current);

  • Ovid CINAHL (1982 to current);

  • AMED (Allied and Complementary Medicine Database) (1985 to current). 

We will search the Cochrane Central Register of Controlled Trials (CENTRAL) (latest issue) using the search strategy (see Appendix 1).

We will adapt this strategy, where appropriate, for the other databases. We will combine the Ovid MEDLINE search with the Cochrane Highly Sensitive Search Strategy for identifying randomised trials in MEDLINE: sensitivity- and precision maximising version (2008 revision) (Lefebvre 2008). We will combine the Ovid EMBASE and Ovid CINAHL searches with the trial filters developed by the Scottish Intercollegiate Guidelines Network (SIGN 2008). There will be no restriction on the basis of date or language of publication.

Searching other resources

We will scrutinise citations within all obtained trials and review articles to identify any additional trials.

Data collection and analysis

Selection of studies

Two review authors will independently scan the title, abstract and keywords of every record retrieved to determine which studies require further assessment. We will retrieve the full article when the information given suggests the possibility that:

  1. the study compared Chinese herbal medicine with another intervention or control;

  2. the study had a prospective design.

If there is any doubt regarding these criteria from scanning the titles and abstracts, we will retrieve the full article for clarification. Then two review authors will independently read the full paper selected to determine which studies require further assessment. The selection should comply with "Criteria for considering studies" (above), such as "Types of studies", "types of participants", "types of interventions". If there is any doubt regarding these full articles,we will resolve disagreement by discussion with a third review author if necessary. We will contact the authors of trials to provide missing data if necessary.

Data extraction and management

Two review authors will independently extract data concerning details of study population, intervention and outcomes using a standard data extraction form specifically adapted for this review. The data extraction form includes the following items.

  1. General information: published/unpublished, title, authors, country of study, contact address, year of study, language of publication, year of publication, sponsor/funding organisation, setting.

  2. Methodological details: including criteria for 'Risk of bias' assessment (below).

  3. Intervention: descriptions of Chinese herbal medicines (dose, route, timing), descriptions of co-medication(s) (dose, route, timing).

  4. Participants: inclusion and exclusion criteria, total number and number in comparison groups, sex, age, baseline characteristics, withdrawals/losses to follow-up (reasons/description), subgroups.

  5. Outcomes: proportion healed, eradication of defined infection, mortality related to SSTIs or treatment, adverse events, duration of treatment, duration of hospitalisation, costs and time to healing.

Assessment of risk of bias in included studies

Two review authors will independently assess each included study using the Cochrane Collaboration tool for assessing risk of bias (Higgins 2008a). This tool addresses six specific domains, namely sequence generation, allocation concealment, blinding, incomplete outcome data, selective outcome reporting and other issues (e.g. if groups were similar at baseline for important prognostic indicators - area of redness and inflammation and generalised symptoms such as fever and malaise; and if co-interventions were avoided or similar between the treatment and control groups) (see Appendix 2 for details of the criteria on which we will base the judgement). We will assess blinding and completeness of outcome data for each outcome separately. We will complete a 'Risk of bias' table for each eligible study. We will discuss any disagreement amongst all review authors to achieve a consensus. 

We will present assessment of risk of bias using a 'Risk of bias' summary figure, which presents all of the judgements in a cross-tabulation of study by entry. This display of internal validity indicates the weight the reader may give the results of each study.

Measures of treatment effect

We will present dichotomous outcomes (e.g. proportion of infections healed, adverse events, mortality) as risk ratios (RR) with corresponding 95% confidence intervals (CI). We will present continuous data (e.g. duration of hospitalisation) as mean differences (MD) with corresponding 95% CI. We will consider time to event data (e.g. time to healing) if correctly analysed using survival methods which can account for censoring (i.e., just for the time that people were observed so it takes account of when they dropped out), it is inappropriate to report and analyse time to wound healing as if it were a continuous variable unless everyone healed and there was no loss to follow up.

Where a study involves more than two treatment arms, if relevant, we will present the additional treatment arms in comparisons. Where the additional treatment arms are not relevant, we will not extract these data. We will split the shared control group into two or more groups with smaller sample size, depending on the number of interventions studied, and include two or more comparisons (Higgins 2008b).

Unit of analysis issues

Comparisons that randomise or allocate clusters (e.g. clinics) but do not account for clustering during analysis have potential unit of analysis errors, resulting in artificially low P values and over-narrow confidence intervals. We will attempt to re-analyse studies with potential unit of analysis errors by calculating effective sample sizes where possible (Higgins 2008b). If a comparison is re-analysed then we will quote the P value and annotate it with 're-analysed'. If this is not possible we will report only the point estimate (Donner 2001).

Dealing with missing data

If data are missing from the trial reports, we will attempt to contact the trial authors to request these values. If this is not successful, we will impute replacement values to compare data by meta-analysis. If this is necessary, we will perform sensitivity analyses to assess how sensitive results are to reasonable changes in the assumptions that are made. Furthermore, we will also address the potential impact of missing data on the findings of the review in the Discussion section (Higgins 2008b).

At some degree of loss to follow-up data must lose credibility (Xia 2010). We are forced to make a judgement as to where this is for the trials likely to be included in this review. Should more than 40% (Xia 2010) of data be unaccounted for by eight weeks we will not extract these data or use them within analyses.

Assessment of heterogeneity

We will assess population, methodology, intervention and outcome measures in each study for clinical heterogeneity to see if the pooling of results is feasible. We will carry out assessment for heterogeneity using the Chi² test with significance being set at P value < 0.1. In addition we will use the I² statistic to estimate the total variation due to heterogeneity across studies (Higgins 2008b).

A number of options are available if heterogeneity is identified among a group of trials. Firstly, check again whether the data have been incorrectly extracted or entered into Review Manager (RevMan) 5 (RevMan 2011). Secondly, subgroup analyses or meta-regression should be conducted, if heterogeneity may be caused by severity of disease, patient characteristics or specific interventions. Thirdly, sensitivity analysis should be conducted if heterogeneity may be due to the presence of one or two outlying trials with results that conflict with the rest of the trials. It is advisable to perform analyses both with or without outlying trials as part of a sensitivity analysis. The fourth option, if there is no clinical or methodological heterogeneity and all studies are measuring the same underlying effect, it should be a fixed effect model. If there is clinical and/or methodological heterogeneity and the studies are measuring different underlying effect, but are still sufficiently similar to make a pooled result useful, then a random effects model should be used and the heterogeneity investigated using a priori sensitivity and subgroup analyses.

We will regard I² statistic values of less than 25% as representing low heterogeneity and we will use a fixed-effect model for meta-analysis. We will consider values between 25% and 75% to represent moderate levels of heterogeneity and we will use a random-effects model. If values of the I² statistic are higher than 75%, indicating a high level of heterogeneity, or if most of the evidence is non-blinded and subjective, meta-analysis is not appropriate and will not be undertaken.

Assessment of reporting biases

Funnel plots, plots of the trials' effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases. We will construct funnel plots if at least 10 studies are available for the meta-analysis of a primary outcome. Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single, large trials (Egger 1997).

Data synthesis

Two review authors will independently enter data into RevMan 5 using the duplicate data entry facility. We will summarise findings of individual studies in a narrative format. If there is sufficient homogeneity in populations, study design and outcome measures, we will pool results following assessment for statistical heterogeneity as described above.

Subgroup analysis and investigation of heterogeneity

To assess whether the treatment effect is modified by clinical and demographic variables, we will undertake a subgroup analysis if we identify trials which are conducted in people with diabetes and in non diabetic populations.

We will also repeat meta-analysis using a fixed-effect model with analysis using a random-effects model and vice versa, to establish the robustness of the results. If the conclusions are different, then we will explore the possible reasons by looking at the study characteristics.

Sensitivity analysis

If a sufficient number of trials are found, we will carry out sensitivity analysis to assess the robustness of the results as follows:

  1. exclusion of studies with inadequate or unclear (insufficient information to permit judgement) concealment of allocation;

  2. exclusion of studies in which outcome evaluation was not blinded or unclear (insufficient information to identify if outcome evaluation was blinded).

Acknowledgements

The authors would like to thank the peer referees (Jane Burch, Dayanathee Chetty, Olivier Chosidow), the Cochrane Wounds Group editors (David Margolis, Susan O’Meara) and Sally Bell-Syer. The authors would also like to thank Jenny Bellorini for copy editing the protocol.             

Appendices

Appendix 1. search strategy

#1  MeSH descriptor Herbal Medicine explode all trees
#2  MeSH descriptor Plants, Medicinal explode all trees
#3  MeSH descriptor Medicine, East Asian Traditional explode all trees
#4  MeSH descriptor Drugs, Chinese Herbal explode all trees
#5  (chinese NEAR/5 (herb* or medic* or drug*)):ti,ab,kw
#6  (herb* NEAR/5 (medic* or drug* or treatment* or therapy*)):ti,ab,kw
#7  (#1 OR #2 OR #3 OR #4 OR #5 OR #6)
#8  MeSH descriptor Soft Tissue Infections explode all trees
#9  MeSH descriptor Staphylococcal Skin Infections explode all trees
#10 MeSH descriptor Cellulitis explode all trees
#11 MeSH descriptor Erysipelas explode all trees
#12 MeSH descriptor Furunculosis explode all trees
#13 MeSH descriptor Abscess explode all trees
#14 MeSH descriptor Fasciitis, Necrotizing explode all trees
#15 MeSH descriptor Myositis explode all trees
#16 MeSH descriptor Gas Gangrene explode all trees
#17 (soft NEXT tissue NEXT infection* or skin NEXT infection* or SSIT):ti,ab,kw
#18 (cellulitis or erysipelas or furuncul* or abscess* or abscess* or "necrotizing fasciitis" or myositis or "gas gangrene"):ti,ab,kw
#19 (#8 OR #9 OR #10 OR #11 OR #12 OR #13 OR #14 OR #15 OR #16 OR #17 OR #18)
#20 (#7 AND #19) 

Appendix 2. 'Risk of bias' criteria

1.  Was the allocation sequence randomly generated?

Low risk of bias

The investigators describe a random component in the sequence generation process such as: referring to a random number table; using a computer random number generator; coin tossing; shuffling cards or envelopes; throwing dice; drawing of lots.

2.  Was the treatment allocation adequately concealed?

Low risk of bias

Participants and investigators enrolling participants could not foresee assignment because one of the following, or an equivalent method, was used to conceal allocation: central allocation (including telephone, web-based and pharmacy-controlled randomisation); sequentially numbered drug containers of identical appearance; sequentially numbered, opaque, sealed envelopes.

High risk of bias

Participants or investigators enrolling participants could possibly foresee assignments and thus introduce selection bias, such as allocation based on: using an open random allocation schedule (e.g. a list of random numbers); assignment envelopes were used without appropriate safeguards (e.g. if envelopes were unsealed or non­opaque or not sequentially numbered); alternation or rotation; date of birth; case record number; any other explicitly unconcealed procedure.

Unclear

Insufficient information to permit judgement of low or high risk of bias. This is usually the case if the method of concealment is not described or not described in sufficient detail to allow a definite judgement, for example if the use of assignment envelopes is described, but it remains unclear whether envelopes were sequentially numbered, opaque and sealed.

3.  Blinding - was knowledge of the allocated interventions adequately prevented during the study?

Low risk of bias

Any one of the following.

  • No blinding, but the review authors judge that the outcome and the outcome measurement are not likely to be influenced by lack of blinding.

  • Blinding of participants and key study personnel ensured, and unlikely that the blinding could have been broken.

  • Either participants or some key study personnel were not blinded, but outcome assessment was blinded and the non-blinding of others unlikely to introduce bias.

High risk of bias

Any one of the following.

  • No blinding or incomplete blinding, and the outcome or outcome measurement is likely to be influenced by lack of blinding.

  • Blinding of key study participants and personnel attempted, but likely that the blinding could have been broken.

  • Either participants or some key study personnel were not blinded, and the non-blinding of others likely to introduce bias.

Unclear

Any one of the following.

  • Insufficient information to permit judgement of low or high risk of bias.

  • The study did not address this outcome.

4.  Were incomplete outcome data adequately addressed?

Low risk of bias

Any one of the following.

  • No missing outcome data.

  • Reasons for missing outcome data unlikely to be related to true outcome (for survival data, censoring unlikely to be introducing bias).

  • Missing outcome data balanced in numbers across intervention groups, with similar reasons for missing data across groups.

  • For dichotomous outcome data, the proportion of missing outcomes compared with observed event risk not enough to have a clinically relevant impact on the intervention effect estimate.

  • For continuous outcome data, plausible effect size (difference in means or standardised difference in means) among missing outcomes not enough to have a clinically relevant impact on observed effect size.

  • Missing data have been imputed using appropriate methods.

High risk of bias

Any one of the following.

  • Reason for missing outcome data likely to be related to true outcome, with either imbalance in numbers or reasons for missing data across intervention groups.

  • For dichotomous outcome data, the proportion of missing outcomes compared with observed event risk enough to induce clinically relevant bias in intervention effect estimate.

  • For continuous outcome data, plausible effect size (difference in means or standardised difference in means) among missing outcomes enough to induce clinically relevant bias in observed effect size.

  • ‘As-treated’ analysis done with substantial departure of the intervention received from that assigned at randomisation.

  • Potentially inappropriate application of simple imputation.

Unclear

Any one of the following.

  • Insufficient reporting of attrition/exclusions to permit judgement of low or high risk of bias (e.g. number randomised not stated, no reasons for missing data provided).

  • The study did not address this outcome.

5.  Are reports of the study free of suggestion of selective outcome reporting?

Low risk of bias

Any of the following.

  • The study protocol is available and all of the study’s pre-specified (primary and secondary) outcomes that are of interest in the review have been reported in the pre-specified way.

  • The study protocol is not available but it is clear that the published reports include all expected outcomes, including those that were pre-specified (convincing text of this nature may be uncommon).

High risk of bias

Any one of the following.

  • Not all of the study’s pre-specified primary outcomes have been reported.

  • One or more primary outcomes is reported using measurements, analysis methods or subsets of the data (e.g. subscales) that were not pre-specified.

  • One or more reported primary outcomes were not pre-specified (unless clear justification for their reporting is provided, such as an unexpected adverse effect).

  • One or more outcomes of interest in the review are reported incompletely so that they cannot be entered in a meta-analysis.

  • The study report fails to include results for a key outcome that would be expected to have been reported for such a study.

Unclear

Insufficient information to permit judgement of low or high risk of bias. It is likely that the majority of studies will fall into this category.

6.  Other sources of potential bias

Low risk of bias

The study appears to be free of other sources of bias.

High risk of bias

There is at least one important risk of bias. For example, the study had extreme baseline imbalance.

Unclear

There may be a risk of bias, but there is either:

  • insufficient information to assess whether an important risk of bias exists; or

  • insufficient rationale or evidence that an identified problem will introduce bias.

Contributions of authors

Wang YF: conceived the review question, developed the protocol and co-ordinated the protocol development. Completed the first draft of the protocol and edited subsequent drafts. Made an intellectual contribution to the protocol, approved the final version of the protocol prior to submission.
Wang YJ: developed the protocol and performed part of writing or editing of the protocol. Made an intellectual contribution to the protocol and advised on part of the protocol.
Cui XJ: developed the protocol and performed part of writing or editing of the protocol. Made an intellectual contribution to the protocol and advised on part of the protocol.
Que HF: developed the protocol and performed part of writing or editing of the protocol. Made an intellectual contribution to the protocol, advised on part of the protocol and is guarantor of the work.

Contributions of editorial base:

Nicky Cullum: edited the protocol; advised on methodology, interpretation and protocol content. Approved the final protocol prior to submission.
Sally Bell-Syer: co-ordinated the editorial process. Advised on methodology, interpretation and content. Edited and copy edited the protocol.
Ruth Foxlee: designed the search strategy and edited the search methods section.

Declarations of interest

None known.

Sources of support

Internal sources

  • No sources of support supplied

External sources

  • NIHR/Department of Health (England), (Cochrane Wounds Group), UK.

Ancillary