Article Text

Multicentre, observational, retrospective cohort of hyperkalaemia burden at haemodialysis facility-level in China: the Visualize-HD study protocol
  1. Xinju Zhao,
  2. Li Zuo
  1. Department of Nephrology, Peking University People's Hospital, Beijing, China
  1. Correspondence to Dr Li Zuo; zuoli{at}


Objectives Hyperkalaemia is a potentially life-threatening disorder in patients undergoing haemodialysis (HD). Excess mortality and hospitalisation have been associated with hyperkalaemia (HK) after the long (2-day) interdialytic interval (LIDI) in patients on thrice a week HD compared with the short (1-day) interdialytic interval. Moreover, not much research has been conducted in China on the descriptive epidemiology and management of HK among different HD centres. The aim of this study is to address this evidence gap by investigating the risk factors associated with HK clinical burden at the HD facility level, current HD centres management patterns, serum potassium management patterns, as well as the risk factors associated with crude mortality in China.

Design Multicentre, observational, retrospective cohort study.

Setting This study plans to enrol 300 HD centres across China. Haemodialysis centres having ≥100 patients on maintenance HD within 3 years before study initiation, with participation willingness, routine blood collection post-LIDI and death records will be included.

Participants Patients aged ≥18 years and on chronic HD for ≥3 months will be considered eligible. Summary data about serum potassium, characteristics of patients, facility practice patterns will be collected at HD facility level and death records will be at the patient level.

Primary and secondary outcome measures The primary outcome will be to examine the association between suspected risk factors and HK prevalence at HD facility level. Suspected risk factors include dialysis prescriptions and serum potassium testing frequency, characteristics of patients and related medication usage. The secondary outcome will be to determine the HK prevalence, serum potassium management pattern and risk factors associated with crude mortality. The primary and secondary outcomes will be analysed using regression models. Exploratory outcomes will further investigate the risk factors associated with serum potassium ≥6.0 and ≥6.5 mmol/L.

Conclusion The study is expected to provide insights to improve dialysis practice patterns and understand the clinical burden of HK.

Ethics and dissemination This study protocol was reviewed and approved by the Institutional Review Boards and Ethics Committee of Peking University People’s Hospital (Approval number: 2020PHB324-01). The results will be disseminated through national and international presentations and peer-reviewed publications.

Trial registration number NCT05020717.

  • GENERAL MEDICINE (see Internal Medicine)
  • Vascular medicine

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  • This is a nationwide, multicentre, observational, retrospective cohort with a large sample size.

  • The protocol is planned to occur in four stages: site screening, haemodialysis-centre enrolment, data collection and statistical analysis.

  • A regression model will examine the association between suspected risk factors and the outcomes of interest.

  • With respect to secondary outcomes, Poisson regression will explore the association of facility-level risk factors with crude mortality.

  • A limiting factor of this study is the analysis of only facility-level data.


The prevalence of patients on maintenance haemodialysis (HD) in China is predicted to expand further by 2025, thereby escalating the burden on HD facility centres.1 Hyperkalaemia (HK) is a potentially life-threatening complication in the end-stage kidney disease (ESKD) associated with ventricular arrhythmias and sudden cardiac arrest.2–4 Approximately, 90% of the ingested potassium (K+) load is excreted primarily in the urine and the remaining in the faeces.2 Patients on maintenance HD have no or little residual renal function (RRF), thereby increasing the likelihood of HK occurrence.5 Potassium usually accumulates during the interdialytic interval.6 HD treatment removes excess of serum potassium that amasses between two dialysis sessions to control pre-dialysis HK, simultaneously preventing intradialytic and post-dialysis hypokalaemia.2

The most serious manifestations of HK include muscle weakness or paralysis, cardiac arrhythmias and cardiac conduction abnormalities. As serum potassium is a crucial determinant of resting membrane potential, fluctuation in its concentrations may increase intradialytic cell membrane polarisation leading to cardiac arrhythmia.2 Potassium accumulation leads to an impairment in the functioning of the heart muscle,7 which may cause serious cardiovascular events. Besides cardiac-related problems, HK can also cause paraesthesia, nausea, dyspnoea, hypotension and muscle weakness leading to flaccid paralysis and metabolic acidosis, contributing to chronic kidney disease progression.8 9 HD treatment is a non-physiological process. Notably, excess mortality and hospitalisation have been associated with HK after the long (2-day) interdialytic interval (LIDI) in patients on thrice a week HD compared with the short (1-day) interdialytic interval.10 11 Clinically significant arrhythmias are associated with dialytic cycle, and it has been speculated that potassium accumulation plays a major role.7

However, there is a lack of adequate study on the prevalence of HK and its association with adverse outcomes for patients with HD in China. Data from a retrospective observational study conducted on 52 734 patients in the USA receiving in-centre HD showed that the proportion of patients with serum potassium levels ≥5.0 and ≥5.5 mmol/L after LIDI was 49% and 24%, respectively.7 Nevertheless, China is very different from developed countries and western countries in terms of race, economy, medical insurance policies and medical practice patterns. Due to limited medical resources in China, the proportion of patients on HD treatment twice a week is much higher than in other countries.12 Thus, we assume the HK prevalence in China may be higher than that in western regions. In a previous study, serum potassium level ≥5.6 mmol/L was correlated with an increased all-cause mortality and cardiac deaths in patients with HD. The unadjusted HR calculated from various serum potassium categories is U-shaped, with the best survival observed at serum potassium levels of 4.6–5.6 mmol/L.13 However, the precise relationship between serum potassium and all-cause mortality of patients on maintenance HD has not been established yet.14

The K dialysate concentrations have been selected empirically in practice which might influence HK prevalence and mortality. The Dialysis Outcomes and Practice Patterns Study (DOPPS) and the Potassium and Cardiac Rhythm Trends in Maintenance HD study suggested that dialysate K+ (K+ D) concentrations of <2 mmol/L should be avoided.15 Furthermore, a higher incidence of pre-dialysis HK after LIDI is associated with patients on K+ D ≤2 versus ≥3 mmol/L as lower K+ D is generally used to manage HK.2 A retrospective cohort observational study in USA found that the highest 3-year death rate was associated with a high K+ D bath >3.0 mEq/L.16 Moreover, excessive serum and dialysate K+ gradient was shown to be associated with a higher risk of cardiac arrhythmia.12 The K dialysate concentration of 1 mmol/L is rarely used in China.

To date, no descriptive epidemiology data are available in China that evaluate serum potassium management patterns among different HD centres. Furthermore, not much is known about novel risk factors affecting serum potassium levels in patients with maintenance HD, let alone their effects on long-term outcomes, such as the 3-year mortality at a facility level. Additionally, some serum potassium management strategies are empirical which need more evidence for decision-making.

To address these limitations, the present study will be conducted to explore HK prevalence, the risk factors associated with HK clinical burden in Chinese patients with HD, current management patterns of HD centres and serum potassium, as well as the risk factors associated with crude mortality.

Methods and analysis

Study design

Visualize-HD (protocol V.1.0, D1843L000024, dated 15 July 2020) is a multicentre, observational, retrospective cohort study on HD-centre level in China. The study procedure is planned to be executed in four stages as shown in figure 1.

Figure 1

Study procedure. HD, haemodialysis.

Stage 1 (site screening)

The study plans to enrol 300 HD centres in 13 months (30 sites/month) across Mainland China (covers all the 31 provinces in Mainland China) from 15 August 2021 to 15 August 2022. HD centres willing to participate must have ≥100 chronic patients on maintenance HD within 3 years before the study initiation, routine blood collections post-LIDI and death records. Patients aged ≥18 years and on chronic HD for ≥3 months will be considered eligible. Since this is a retrospective study, the death records (3 years backward) are recorded. A retrospective study design was chosen due to a lack of data.

Those HD centres conducting blood tests on days other than post-LIDI, providing inadequate data required by the study protocol and non-compliance with the study-specified procedures, will be excluded.

Stage 2 (HD-centre enrolment)

Hospital-affiliated HD facilities and independent and private HD centres, which will meet the above inclusion criteria, will be enrolled. After ethics committee approval (Peking University People’s Hospital; 2020PHB324-01) and signing of the contract, training will be provided to investigators at each HD centre about the content of the survey form, data collection, reporting procedure and quality control requirement.

Stage 3 (data collection)

Retrospective (patient records 3 years backward) data will be extracted from the hospital information system, quality control and death records of each HD centre. The study survey form is a comprehensive record of HD facility name and ID, facility practice pattern characteristics such as dialysate concentrations of K+, Ca2+, Na+ (mmol/L), routine serum potassium testing frequency, number of dialysis sessions per 2 weeks, length of dialysis session (minutes) and patient’s characteristics, which include demographics and laboratory variables and serum potassium levels. This consists of a single round of blood tests in a given facility, and collecting proportions of patients with different potassium levels (and so on for other indices) at the time of inclusion and 3 years before. Besides that, data about death records will include age, gender, date of death and primary cause of ESKD and death, last serum potassium range and comorbid condition before death. This survey collects facility-level data and not patient-level data. However, death records will be on patient level. The laboratory data of the dead patients are collected in a range, not specific data. Collecting more detailed data only on the deceased patients may help us to understand the basic characteristics and causes of death, which may provide the basis for our next stage study design in the future and focus on these patients in daily clinical practice. Facility-level and patient-level data collection as illustrated in figure 2.

Figure 2

Facility-level and patient-level data collection. HD, haemodialysis.

Information on k-binding drugs as well as medicines that affect K metabolism, such as angiotensin-converting enzyme inhibitor (ACEi), angiotensin receptor blocker (ARB), mineralocorticoid receptor antagonists, angiotensin receptor-neprilysin inhibitor and diuretics will be collected as well. Detailed information about the serum potassium management key factors will be collected in the survey form from each of the 300 HD facilities and will be further merged to generate an overall summary.

Haemodialysate concentrations of K+, Ca2+, Na+

A higher incidence of pre-dialysis HK after the LIDI is associated with dialysate K+ ≤2 versus ≥3 mmol/L,2 whereas another study reported an association of 3-year death rate with a high K+ dialysate bath >3.0 mEq/L.16 The K dialysate concentration of 1 mmol/L is rarely used by clinicians in China. Thus, according to the aforementioned research results in the introduction section and clinical practice in China, we have selected 2.0, 2.5 and 3.0 mmol/L concentrations, and in the questionnaire, we designed ‘other’ concentration choice for this question. With respect to the European Best Practice Guidelines and National Kidney Foundation’s Kidney Disease Outcomes Quality Initiative clinical practice guidelines, we have chosen calcium dialysate concentrations of 1.50 and 1.25 mmol/L, respectively. Given the lack of consensus on ideal dialysate concentrations, the chosen concentrations of calcium dialysate for the survey form will be studied in the categories of 1.25, 1.50 and 1.75 mmol/L, whereas sodium dialysate will be studied in the categories of <136; ≥136, <138; ≥138, <140; ≥140, <142; ≥142 mmol/L, respectively.

Serum potassium testing frequency

The survey form will collate data from HD centres about routine serum potassium testing frequency in three sections (once/month, once/2 months and once/3 months) from HD centres.

Dialysis frequency and length of dialysis session

The Renal Association Clinical Practice Guideline on HD (UK) recommended a minimum of 12 hours per week (thrice a week) for managing patients with HK having minimal residual function.17 The frequency of dialysis and the length of dialysis sessions should be associated with potassium clearance by dialysis treatment, which might serve as the potential risk factors. Thereafter, this survey form will also gather data from HD centres about the frequency and length of dialysis sessions for the management of serum potassium by including information about the number of HD sessions per 2 weeks (26) and the length (min) of each session (<210, ≥210 to ≤240, >240 to ≤270 and >270).

Patient’s characteristics—serum potassium levels after LIDI and demographics

Data from a retrospective cohort observational study on patients receiving thrice a week in-centre HD revealed that serum potassium levels of 5.5–6.0 were associated with an increased risk of hospitalisation (adjusted OR, 1.68; 95% CI, 1.22 to 2.30) and serum potassium levels of 6.0–6.5 mEq/L with death. The referent category for this study was 4.0–4.5 mEq/L.7 There is no universally accepted definition of HK; therefore, studies use various thresholds such as 5.0, 5.5 or 6.0 mEq/L. Usually, pre-dialysis serum potassium levels ≥5.0 mEq/L are associated with increased mortality.12 Therefore, the survey questionnaire will collect data from the different constitution ratio of predefined serum potassium levels after LIDI from a single round blood test in the range of ((0–3.5), (3.5–5.0), (5.0–5.5), (5.5–6.0), (6.0–6.5), (6.5–7.0) and ~7.0 mmol/L), and the concentration of 3.5–5.0 can be used as reference.

Demographic variables associated with serum potassium management will include age in years (18–44, 45–64, 65–74, >75). Furthermore, RRF data will be classified in survey form in the following cut-offs: <400, 400–1000 and ≥1000 mL/day, because RRF is a powerful predictor of survival in patients with maintenance HD and the presence of any urine output (>100 mL/day) was associated with a 65% lower risk of death.18 Subsequently, comorbidities further contribute to a decline in RRF as the Study of Heart and Renal Protection reported that the annual rate of decline was 3.8±2.5, 2.5±4.8 and 1.9±3.6 for patients with cystic kidney disease, diabetic nephropathy and glomerulonephritis, respectively.19 The survey form will also collate data about the primary cause of ESKD as specified in online supplemental material 1, and the history of comorbid conditions, which include coronary heart disease, congestive heart failure, calciphylaxis, cancer (non-skin), carpal tunnel syndrome, cerebrovascular disease, gastrointestinal bleeding, hypertension, hyperlipidaemia, lung disease, peripheral vascular disease, recurrent cellulitis, hepatitis B, hepatitis C and diabetes. Moving forward to dialysis vintage, a retrospective cohort study divided it into eight categories and 1 to <2 years was used as a reference because the risk of mortality is lowest in this group.20 Similarly, in our survey form, dialysis vintage will be given in the ranges of <1, 1–5, 5–10 and >10 years. Furthermore, the increased risk of developing HK in patients with HD is associated with the use of ACEi or ARBs. Therefore, serum potassium concentration should be closely monitored when these medications are co-prescribed.21 The survey form will also gather information about medication use as specified in online supplemental material 1, and clinical variables such as serum albumin (g/L), haemoglobin (g/L), intact phosphorus (mmol/L), calcium (mmol/L), intact parathyroid hormone (pg/mL) in ranges as specified in online supplemental material 1. The rationale behind testing the blood of patients who are on maintenance HD every month is that intervention in response to laboratory results will be beneficial for their health.22

Patient and public involvement

All aspects of this study (development of the research question, study design and conduct of the trial, interpretation of results and editing of the final manuscript for publication) are taking place independently of patients and public involvement. The results will be disseminated to participants by their physicians.

Stage 4 (statistical analysis)

The overall summary of data from each facility will be generated. Continuous variables will be summarised by descriptive statistics, whereas categorical variables will be summarised using frequency and percentages. A categorical variable approach was used for dialysate K, Ca and Na due to two reasons. First, this design will reduce the data-collecting burden for investigators. As some of the sites have a routine database for patients undergoing HD, it will enable quick access to categorical data on the Institutional Review Board approval. Second, we believe that the categorical variable approach fits the facility-level study design without undermining the study power. For example, to conduct a univariate analysis of the association between an outcome and dialysate Na+ concentration at a facility level, if we take dialysate Na+ as a continuous variable, only the facility-level mean or median will be used to represent the dialysate Na+ of a certain facility; but if we take it as a categorical variable, the percentage of patients receiving dialysate Na+ of each category (<136, 136–138, 138–140, 140–142 or ≥142 mmol/L) will be used. The categorical variable approach conveys enough information about the distribution of dialysate Na+ patients received within a certain facility. All analyses will be based on a full analysis set (FAS), and all eligible facilities will be included. The FAS is an analysis set that is as complete as possible and is closest to the intention-to-treat population. The missing data will be imputed using the method of multiple imputation.23

To examine the association between suspected risk factors and the outcomes of interest (HK at the facility level), a regression model will be used. The prevalence of HK at each HD facility in the current status will be defined as the proportion of patients with serum potassium>5.0 mmol/L after LIDI. Probit regression will be used to examine the association of suspected risk factors with facility-level HK prevalence. The candidate risk factors include but are not limited to the key serum potassium management factors (eg, dialysis frequency, dialysate potassium concentration and serum potassium testing frequency) and other factors (eg, length of dialysis/session, patients’ dialysis vintage and comorbidities). For facility-level variables with m categories, there will be m proportions at all categories for each facility. The categories of each risk factor may be consolidated according to the clinical practice in the model to avoid over-parameterisation. A variable selection procedure within multivariate analysis will be processed using the stepwise algorithm within the regression model, with the cut-off value of 0.10 will be a set variable for inclusion or exclusion. A sensitivity analysis will be conducted to change the serum potassium cut-off to ≥5.5 mmol/L with the same analysis method for the primary outcome.

For secondary outcomes, Poisson regression will be used to explore the association of facility-level risk factors with crude mortality. The facility-level crude mortality will be calculated as the ratio of the number of death records to the number of patients on maintenance HD during the past 3 years. The age and gender, the primary cause of ESKD and death, dialysis vintage on death and the comorbidity condition will be transformed into facility-level categorical variables. For exploratory outcomes, a similar method as mentioned above will be used.

A two-sided significance level of 0.05 (α=0.05) will be used for all testing. All statistical analyses will be performed using Microsoft Excel 2019 (Microsoft, Redmond, Washington, USA) and SAS V.9.4 (SAS Institute, Cary, North Carolina, USA).

Sample size

For risk factor regression analysis, generally 10–15 observations are needed for each candidate factor. Assuming there are 20–30 candidate factors to be included in the analysis, a total of 300 HD facilities are necessary to meet the objective.

Study objectives and endpoints

The primary objective of the study will be to evaluate the risk factors associated with HK clinical burden in Chinese patients with maintenance HD at the facility level. The secondary objectives will be to determine HK clinical burden, serum potassium management pattern, as well as the risk factors associated with crude mortality at the facility level. In addition, exploratory objectives will further investigate the risk factors associated with serum potassium≥6.0 and ≥6.5 mmol/L at the facility level. The study endpoints for each objective are described in detail in figure 3. All the study data will be collected and analysed at HD facility level, and not at the patient level (except for data about death records during the past 3 years, which will be collected at the patient level and analysed at HD facility level).

Figure 3

Study endpoints for Visualize-HD. ACEi, angiotensin-converting enzymes inhibitor; ARB, angiotensin receptor blocker; ESKD, end-stage kidney disease; HD, hemodialysis; LIDI, long (2-day) interdialytic interval; MRA, mineralocorticoid receptor antagonists; sK, serum potassium.

Data monitoring

After the preparation and completion of all data collection fields by authorised research centre staff, these survey forms will be promptly reviewed, signed and dated by investigators at each site. A contract research organisation (CRO) company will be contracted to build an electronic data collecting system to conduct the cohort. The data will be stored in the server from this CRO company. The investigator will be responsible for the accuracy of source files (eg, original documents, data and records related to clinical trials), which are stored and organised in a database. The study will be conducted in accordance with the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use Guideline for Good Clinical Practice.


The population of Chinese patients with ESKD is increasing, thereby necessitating the need to understand more about dialysis practices.24 HD facility is the primary healthcare provider for ESKD in China and works on prolonging life expectancy and improving the quality of life of patients by intermittent potassium clearance.25–27 Therefore, it can be assumed that HK disease burden would be associated with dialysis-related factors. The management of a dialysis centre deserves more attention, which includes centre-development planning, equipment configuration, medical staff training, complications in diagnosis and treatment, patient education and quality control.28 Previous research results about dialysis practice patterns were limited by non-uniform research methods.29 Hence, the present observational cohort study will provide insights to improve dialysis practice patterns by enrolling 300 HD centres and summarising data on serum potassium after LIDI, facility practice pattern, characteristics of patients associated with serum potassium management and death records at each centre. This will help in describing the clinical burden of HK and risk factors associated with the burden of HK on HD facilities.

The present study will evaluate key serum potassium management factors as there is a lack of consensus on the ideal dialysate potassium concentration, dialysis dose and serum potassium testing frequency in worldwide dialysis prescription.12 Typically, clinical practice guidelines do not currently provide recommendations on the prescription of K+ D concentrations; therefore, many clinicians apply a ‘Rule of 7s’, in which the sum of serum potassium and K+ D concentrations of a patient should be ≈7 mEq/L.30 Many cohort studies point to the hazards of lower potassium dialysate <2 mEq/L, and the evidence for risk is highest for patients with pre-dialysis serum potassium<5 mEq/L.12 Numerous algorithms have been suggested by various investigators for managing dialysate potassium levels according to pre-dialysis serum potassium; however, results remain inconclusive.12 Moreover, there is little information on how much serum potassium level contributes to all-cause mortality and on the association between serum potassium levels and adverse outcomes following the LIDI.15 Therefore, this study will analyse the clinical burden of HK by collecting the constitution ratio of different serum potassium levels after LIDI in the following ranges: ((0−3.5), (3.5−5.0), (5.0−5.5), (5.5−6.0), (6.0−6.5), (6.5−7.0) and ~7.0 mmol/L).

Facility-level studies could provide useful insights for patients on dialysis and may compensate for patient-level studies, which are time-consuming and resource-consuming. Hence, the present study will include a large sample size of 300 HD centres and more comprehensive characteristics in study survey form as specified in online supplemental material 1 to provide robust data on HK burden at the facility level. The present study could highlight factors providing opportunities for improvement in HK burden at the facility level. Data from the DOPPS prospective cohort study found that facility-level haemoglobin was associated positively with patient mortality and identified modifiable practices to improve patients’ survival.31 Our study survey questionnaire is in accordance with DOPPS II, the main focus of which is not only to collect patient-level data but also on many different aspects of facility-level HD practices such as dialysis prescription, water quality, dialyser reuse practices, staffing patterns, nutrition, vascular access and health maintenance.32 33 A multicentre study of patients on HD in China’s major cities indicated equivalent survival in the twice a week and thrice a week dialysis groups regardless of RRF.34 Our study will also determine the proportion of patients on different dialysis frequency prescriptions among various HD centres.

Usually, Chinese nephrologists in large hospitals, who have experience and knowledge about dialysis are involved in decision-making of dialysing patients with ESKD by providing them treatment in their affiliated dialysis facilities, which allowed the researchers to design the study at the facility level.35 Statistical adjustment (regression modelling) is the principal mechanism to consider the differences in covariates on the primary outcomes which, if not accounted for, may result in confounding. Regression models will be fitted to the data to adjust for the influence of observed covariates. We acknowledge that statistical adjustment for observed covariates adjustment for confounding bias is unlikely to account for all sources of variation; thus, ‘adjusted’ estimates will be reported with explicit reference to these potential limitations. Multivariate regression models will include potential risk factors including key serum potassium management factors (eg, dialysis frequency, dialysate potassium concentration, serum potassium testing frequency) and other factors (eg, length of dialysis/session, patients dialysis vintage, RRF, aetiology of ESKD, comorbidities, medication use), as well as potential confounding variables that are available to be collected including age, sex, etc.

We acknowledge the study has a limitation that only facility-level data will be analysed. Level data of patients are subjected to further investigation on detailed outcomes associated with HK in patients on HD. Nevertheless, this is the first, nationwide, large sample size cohort study to explore HK clinical burden and investigate the risk factors associated with the burden on HD facility level. This study will aim to generate contemporary evidence to fill epidemiological research gaps in HK and explore risk factors associated with HK disease burden in Chinese patients on HD. At this point, the study is expected to proceed to phase 2, depending on the results of the current survey.

Ethics statements

Patient consent for publication


The medical writing and editorial support for the preparation of this manuscript was provided by Anwesha Mandal and Dr Tanushree Goswami of Indegene Pvt. Ltd, India.


Supplementary materials

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.


  • Contributors XZ and LZ were involved in the conception, design of research, manuscript editing and manuscript revision. LZ approved the final version of the manuscript.

  • Funding The Visualize-HD study was supported by AstraZeneca (Grant number: N/A). A grant from ZGC Nephrology & Blood Purification Innovation Alliance (Grant number: N/A) was obtained for this study. The funding body played no role in the design of the study and collection, analysis and interpretation of data and in writing the manuscript.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.