In England I have used the output area classification with success for over 10 years to identify social groups with higher rates of admission. I have found deprivation to be a very crude measure. Alas much of this is not published. but several studies regarding admission to the CCU. Also a couple of studies looking at outbreaks of a mystery disease. See below.

Hope this helps.

Beeknoo N, Jones R. Using Social Groups to Locate Areas with High Emergency Department Attendance, Subsequent Inpatient Admission and Need for Critical Care. British Journal of Medicine and Medical Research 2016; 18(6): 1-23. doi: 10.9734/BJMMR/2016/29208

Beeknoo N, Jones R. Using social groups to locate areas of high utilization of critical care. Brit J Healthcare Manage 2016; 22(11): 551-560.

Jones R. Year-to-year variation in deaths in English Output Areas (OA), and the interaction between a presumed infectious agent and influenza in 2015. SMU Medical Journal 2017; 4(2): 37-69.
http://smu.edu.in/content/dam/manipal/smu/smims/Volume4No2July2017/SMU%2...(July%202017)%20-%204.pdf

Jones R. Role of social group and gender in outbreaks of a novel agent leading to increased deaths, with insights into higher international deaths in 2015. Fractal Geometry and Nonlinear Analysis in Medicine and Biology 2017; 3(1): 1-7. doi: 10.15761/FGNAMB.1000146

Jones R. Different patterns of male and female deaths in 2015 in English and Welsh local authorities question the role of austerity as the primary force behind higher deaths. Fractal Geometry and Nonlinear Analysis in Medicine and Biology 2017; 3(1): 1-4. doi: 10.15761/FGNAMB.1000145

We thank Dr Pollock and colleagues for their interest in our recent study, which suggested that among patients with non-valvular atrial fibrillation in the UK, inappropriate underdosing was more than twice as common among patients starting on apixaban than those starting on dabigatran or rivaroxaban.

In our analyses, we assumed that patients with missing data on renal function were likely to have unimpaired renal function. Pollock et al expressed their concern regarding the possibility of significant bias resulting from misclassification of renal function among these patients, which could have resulted in the percentage of patients inappropriately prescribed a reduced dose NOAC being overestimated. Among our study population of 30,467 patients, 3856 (12.7%) had missing data on renal function (eGFR values).

Pollock and colleagues also queried the absence of bodyweight data in our results. We acknowledge that it may have been useful for the reader to see these data, although we presented data on BMI in Table 1 of our article as a proxy measure. Nevertheless, we can confirm that in our dataset very few patients had missing data on bodyweight (2.6% of patients starting on apixaban, 3.0% of those starting on dabigatran and 2.3% of those starting on rivaroxaban). Among patients with a recorded bodyweight, the mean bodyweight was 81.4 kg for patients starting on apixaban, 82.6 kg for those starting on dabigatran, and 82.0 kg for those starting on rivaroxaban. While it may be true that, among the general population as a whole, weight may not be recorded in many patient records in primary care, this is unlikely to be the case for specific patient populations, such as patients with NVAF, who will be having more regular contact with their primary care practitioner.

In response to these concerns, and to validate our assumption that patients with missing data on renal function were likely to have unimpaired renal function, we have performed a sensitivity analysis excluding patients with missing data on renal function and/or bodyweight (4418 patients; 14.5% of our study cohort). The results of the sensitivity analysis are shown in the Table and Figures below. Only very minimal differences were seen for apixaban (21.6% were inappropriately underdosed in the main analysis vs. 21.4% in the sensitivity analysis), for dabigatran (8.3% in the main analysis vs. 8.2% in the sensitivity analysis), and for rivaroxaban (9.1% in the main analysis vs. 8.4% in the sensitivity analysis)(Table and Figure 1). When dosing was evaluated according to degree of renal function (Figure 2), the data still showed that reduced doses were prescribed to patients with no evidence of renal impairment, with minimal or no difference seen between results of the main analysis and the sensitivity analysis: 26.7% vs. 26.6% for apixaban, 51.1% vs. 50.5% for dabigatran, and 10.3% in both analyses for rivaroxaban. Furthermore, in another ongoing study conducted by our team we have found that when we looked at eGFR values recorded further back in patients’ medical records (further than within the 1 year before the index date), among patients with no recorded value within the year before the index date, about 10% of these had an eGFR value indicating suboptimal renal function. This would translate into about 1% of patients in our current study being misclassified as having normal renal function based on this older eGFR reading. Therefore, we do not consider potential misclassification of renal function, or the inclusion of patients with missing data on bodyweight, to be significant sources of bias, and further analysis is highly unlikely to alter the conclusions of the study in this respect.

In response to the final point raised by Pollock et al, we would like to clarify that the aim of our study was not to ascertain whether a reduced dose such as 2.5 mg/day apixaban was the correct dose for an individual patient, but whether patients were prescribed an appropriate dose as specified on the EU drug label, based on the data recorded in THIN and CPRD databases. We provided a clear definition of appropriate and inappropriate dosing with respect to the EU label in our article.

Considering this further evidence from our study – that any effect of bias due to misclassification of renal function or bodyweight is likely to be very minimal – we are of the opinion that the inferences made in our article remain valid and justifiable.

The Table can be found here: https://blogs.bmj.com/bmjopen/files/2019/11/Garcia-Rodriguez-et-al-table...

Figure 1 can be found here: https://blogs.bmj.com/bmjopen/files/2019/11/Garcia-Rodriguez-et-al-figur...

Figure 2 can be found here: https://blogs.bmj.com/bmjopen/files/2019/11/Garcia-Rodriguez-et-al-figur...

Dear Sir or Madam

Re. Diagnosed prevalence of Ehlers-Danlos syndrome and hypermobility spectrum disorder in Wales, UK: a national electronic cohort study and case-control comparison.
Demmler J C, Atkinson M D, Reinhold E, Choy E, Lyons R A, Brophy S T
BMJ Open 2019;9:e031365

We write concerning the paper by Demmler et al., published in BMJ Open. We wish to raise the following concerns:

1. With regard to combining the Joint Hypermobility Syndrome (JHS) and Ehlers-Danlos syndromes (EDS) populations for analysis.

If one combines data from a cohort that is found to be ‘common’ (in this case ‘diagnosed JHS’) with one that is found to be ‘rare’ (in this case ‘diagnosed EDS’), the new combined cohort (i.e. diagnosed JHS/EDS) will be common. To then consider the rare cohort common is a fallacy.

Also, although individuals in a population with a previous diagnosis of JHS (i.e. prior to the 2017 international classification (1,2)) might have Hypermobile EDS (hEDS) by the current classification, it is not known how JHS segregates into Hypermobility Spectrum Disorder (HSD) and hEDS. A JHS population would need to be reassessed to confirm this, or modelling assumptions of the data would need to be applied.
In addition, it is not known what proportion of the EDS cohort have hEDS versus the rare Mendelian types of EDS. As such, there is no way of knowing whether or by what proportion the two cohorts represent the same or similar or different conditions.

Given the distribution of JHS to EDS in this study is approximately 6 to 1, the combined cohort would likely share the characteristics of the JHS cohort in a case-control analysis.
By combining the two populations to explore association with other aspects of health and wellbeing the opportunity to compare differences between the two groups is lost. Do the populations in this study differ? What evidence is there that JHS and EDS are behaving statistically in the same way or differently with regard to the parameters collected?

We surmise that the authors in part combined the two populations to identify a larger absolute value for prevalence that informs the need for education, training and healthcare resources. It is increasingly recognized that complex combinations of health concerns arise in HSD and hEDS alike. We recognise why HSD and hEDS would be considered together in this context.
However, by their nature the rare types of EDS will have different specific concerns that influence different education and training needs, and healthcare resource allocation. Rare disease status has significant impact on the way healthcare services plan care (e.g. direct commissioning of specialised services in the UK); or the way organisations support research ( e.g. The Office of Rare Diseases, The National Center for Advancing Translational Sciences, USA), for example.

Regardless of combining the prevalence, it remains necessary that we understand the size effect for each of the different patient populations, as specific needs may differ.

2. With regard to interchanging the term JHS with HSD and hEDS, and determining the prevalence of EDS:

The authors switch from the term JHS to a combination of HSD and hEDS. We recognize this inference. Nevertheless, at this time there is no evidence to inform how JHS segregates into HSD or hEDS, and this uncertainty was not clarified in the paper. There is no modelling of the data that might support inferences with regard to such segregation.
What proportion of the JHS group might add to the overall prevalence of hEDS? How does that modelling affect the prevalence of EDS over all when added to the EDS cohort data?
For example, by our estimate approximately 15% of the JHS cohort would need to have hEDS for this prevalence figure plus that from the EDS cohort to reach a population size of 50 per 100000 for EDS as a whole in this study. Even then that would be 1 in 2000 of the general population; and given that some of the EDS cohort would not have hEDS this would also infer that hEDS per se is rare as it would be a proportion of that EDS population.
If none of the JHS population had hEDS the prevalence calculation for EDS using only the EDS cohort data demonstrates EDS to be rare.
There are other ways to model the data, but we hope that this demonstrates our point.

Until reasonable evidence is available as to the segregation of JHS into hEDS and HSD, we believe studies such as that of Demmler et al. should present the data as found for JHS, or define the assumptions and models they are using to reach their conclusions. In addition, studies should avoid clustering JHS and EDS. The term EDS is a pleural (i.e. Ehlers-Danlos syndromes), grouping together disorders under the title.

Further studies are required to determine how common HSD, hEDS, and other forms of EDS are. Shared knowledge among members of the international medical and scientific community suggest that HSD is likely common; that more work is required to determine if hEDS is common or not; and, that other Mendelian types of EDS are rare or ultra-rare.

3. Concerning the combining the populations and the paper's Conclusion.

The authors conclude that “EDS/HSD are not rare conditions…”. This is asserted because the authors have combined the JHS and EDS populations. We question the reasoning for combining the populations above, but wish, here, to raise further concern about interpretation.

We are aware that this publication is being cited in public forums as saying ‘EDS is common’. At this time, from the data presented, there is no evidence to support that statement, for either hEDS or the rarer types of EDS. Even were it found that hEDS is not rare, it is that observation that would make most sense to assert given many forms of EDS are between rare and ultra-rare.

While there is no direct statement from the authors that ‘EDS is common’, we suggest that the opinion has arisen because of the way the whole paper, including the conclusion has been presented.

We respectfully request that the editors of BMJ Open and the paper’s authors consider the above.

Yours faithfully,

Dr. Alan J Hakim, Adjunct Associate Professor of Medicine, College of Medicine, PennState University, USA, & Consultant Rheumatologist, London

Dr Clair A. Francomano, Professor of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA

Dr. Marco Castori, Consultant and Director, Division of Medical Genetics, IRCCS Casa Sollievo della Sofferenza, Foggia, Italy

Prof. Fransiska Malfait, Associate Professor, Center for Medical Genetics, Ghent University Hospital, Ghent, Belgium.

References:

Malfait F, Francomano C, Byers P, et al. 2017. The 2017 international classification of the Ehlers–Danlos syndromes. Am J Med Genet Part C Semin Med Genet 175C:8–26.

Castori M, Tinkle B, Levy H, Grahame R, Malfait F, Hakim A. 2017. A framework for the classification of joint hypermobility and related conditions. Am J Med Genet C Semin Med Genet 175C:148-157.

Mark L Levy,1,9 Darragh Murnane2, Peter J Barnes,3,9 Mark Sanders,4 Louise Fleming,5 Jane Scullion,6,9 Chris Corrigan,7,9 Omar S Usmani8,9

1. Locum general practitioner, Clinical Lead NRAD (2011-2014)
2. King’s College London Faculty of Life Sciences & Medicine, School of Immunology & Microbial Sciences ; School of Life and Medical Sciences, University of Hertfordshire, Hatfield, Hertfordshire
3. National Heart & Lung Institute, Imperial College, London
4. Clement Clarke international Ltd (CCI) and founder of online museum of inhaler devices, www.inhalatorium.com.
5. Imperial College, London and the Royal Brompton and Harefield, NHS Foundation Trust
6. University Hospitals of Leicester
7. King’s College London Faculty of Life Sciences & Medicine, School of Immunology & Microbial Sciences
8. Imperial College London & Royal Brompton Hospital
9. Aerosol Drug ManagementImprovement Team (ADMIT), www.inhalers4u.org

In an attempt to address issues related to global warming contributed to by the use of pressurised, metered-dose inhalers (pMDIs), Wilkinson et al (1) have succeeded in generating a great deal of negative, potentially harmful media interest for patients who currently rely on these devices. They analysed the potential impact of switching therapy from pMDIs to dry powder inhalers (DPIs) in terms of both changes in greenhouse gas emissions and costs to the UK National Health Service based on prescribing information in England alone. This strategy was apparently devised in a vacuum, without regard to implications for threats to patient wellbeing and safety as a consequence of their being deprived of access to pMDI therapy for obstructive airways disease (asthma and COPD). Physicians are obliged to consider many factors when selecting the most appropriate inhaler device for patients other than the cost to the health care system if they wish the treatment to be effective; (2) these issues were not mentioned in this paper which, in our view, was heavily biased in favour of DPIs, which are seldom appropriate for use in young children, children, the elderly and infirm and those with considerable, irreversible airways obstruction. (3) In addition many patients rely on pMDIs for rapid relief of symptoms.

Their study addressed two possible switching scenarios in the United Kingdom (UK): (i) from pMDIs to currently prescribed DPIs, and (ii) to the cheapest available ‘equivalent’ DPIs based on drug content but not the instrinsic characteristics of the devices. While we agree with one of their conclusions that, with immediate effect, smaller volume HFA134a inhalers (e.g. Salamol) should be prioritised over larger volume or HFA227ea-containing inhalers (e.g. Ventolin) we have major reservations about their remaining assertions, and in particular their conclusion that switching patients’ medication from pMDIs to the cheapest available equivalent DPIs would result in large carbon savings, while ignoring the possible consequences for loss of disease control and consequent morbidity and mortality from obstructive airways diseases such as asthma, which might result in considerable patient harm.

In addition to potential harm from loss of disease control, the burden of suffering and anxiety to patients from this sort of approach to reporting is potentially further amplified by the “guilt factor” already instilled by recent headlines in the media prompted by the report, such as “Asthma inhalers are as bad for the environment as a 180-mile car journey”, “Asthma sufferers should switch to “green” inhalers to help the environment and save millions for the NHS” and “Some asthma inhalers are as bad for the environment as eating meat”. These messages clearly have the potential to stigmatise patients with asthma and COPD for taking their essential medication, and there are anecdotal reports of children, many of whom benefit particularly from pMDI therapy, not wanting to be seen using their inhalers in public. We know of no other situation in the National Health Service where patients are stigmatised for using licensed and approved medications, and the situation will doubtless further impact on the issue of compliance with therapy, which if undermined is another potential threat to their well-being, as well as impacting on morbidity and mortality. (4) Conversely, there was no mention in this commentary, or indeed in the media, that correct delivery of inhaled drugs by an inhaler device which can be used efficiently and reliably by individual patients improves symptoms and quality of life and reduces morbidity, mortality and hospital acute care costs. (5, 6) (3, 7-9)

Further to this last issue, there was correspondingly no mention or consideration of the potential consequences where switching “goes wrong”, resulting in disease destabilisation and the associated “carbon cost” of unnecessary emergency and hospital inpatient management (10); Goulet et al (11) estimated that the carbon footprint of a single bronchodilator dose administered with an electric nebuliser is a considerable 0.0294-0.0477 kg CO¬2-eq. Moorfields Eye Hospital estimate that the carbon footprint of a single patient visit is between 8-10 kg CO2-eq per patient, per visit. It is difficult to assess the current carbon footprint of medical air/oxygen supply, however the European Industry Gas Association lifecycle appraisal framework (document 167/11) identified that the majority of the carbon footprint for liquid gases arises during production and distribution, not during the use of those gases by the end-user. Therefore, unlike the propellant in pMDIs, it is difficult to reduce the carbon footprint of therapeutic gases simply by altering the in-use conditions. (12) One supplier of compressed gases, Linde, in their Corporate Responsibility report of 2017, reported that 5.7 million tonnes of CO2 were produced during liquid gas production, or 52% of their Scope 1 Direct emissions. So the footprint for air therapies is also likely to be significant.

Finally, Wilkinson’s comparison between the UK (70%) and Sweden (10%) pMDI use fails to account for potential differences in disease therapy indications in both countries. For example, both NICE (13) and SIGN/BTS (14) guidelines advocate the use of short-acting, beta-agonist (SABA) use as first line therapy for asthma, which may account for the high levels of prescribing in England. While they acknowledge that they have no idea what disease(s) are being treated in their analysis of prescribing in England, Wilkinson and colleagues have assumed that all patients can be summarily switched from pMDIs to DPIs irrespective of their age, the nature and severity of their disease, their ability to use DPIs efficiently (not all patients can use DPIs efficiently whereas all patients can use pMDIs efficiently if well instructed, with a spacer device), or their satisfaction or preference for the switched device which is a another known factor influencing therapeutic outcome.(15)They have also failed to discuss the fact that not all DPI drugs have clinically equivalent efficacy compared with that of the pMDIs currently in use. It is well known that poor inhaler technique and poor disease outcome are closely related and both NICE (13) and SIGN/BTS (14) guidelines emphasise the necessity of and carefully verifying the ability of individual patients to use inhalers efficiently before prescribing, yet the authors have omitted to address the cost effectiveness and possible carbon footprint of the workload involved in switching and training patients. Furthermore, there was no mention of the chaos familiar to many GPs when patients’ inhalers are switched to “cheaper equivalents” by Clinical Commissioning Group (CCG) employed pharmacists without face to face education and checking technique. Patients become confused when given an unfamiliar device, typically stop using it and in some cases require urgent health care as a consequence. What then often happens is that their GPs will reinstate the original medication. Perhaps the authors could have cited some of the disadvantages arising from switches of medication on non-medical grounds without the patient’s consent, with deterioration of disease control and increased health care utilization. (16) (5) Indeed, data show that stable patients on pMDI maintenance treatment for asthma (17) and COPD (18) achieve better healthcare outcomes than the same drug in a DPI.

While the authors do mention the use of maintenance and reliever regimes (MART and SMART) they do not emphasise the implications, for patient welfare or global warming, of the concerns raised by over usage of short-acting beta-agonists (SABA) as a result of poor education and/or poor overall disease control in patients with asthma. (19, 20) Clearly, simply switching from one SABA to another in this situation will not alter the considerable risk of poor health outcomes, including asthma deaths. (21-23) A strategy is required to eliminate the over usage of SABA by every patient. Combinations of inhaled corticosteroids and long-acting beta-agonists such as formoterol taken “as needed” for the management of mild/moderate asthma are now licensed in five countries based on evidence that they are safer than SABA, (24-27) and it seems very likely that this strategy will be implemented worldwide in the near future, and that it will prove safer and clinically more cost effective. As most of these combination drugs are currently delivered in DPIs this will have an impact on global warming and manufacturers will need to focus on reducing the effect of these on the carbon footprint.

There are considerable shortcomings in carbon footprint modelling in the Wilkinson et al paper. There is relatively scant justification for the carbon footprint of the DPI inhalers included as comparators in this study: in fact, all of the DPIs included in their modelling are assumed to possess the same global warming potential (GWP) as the Ellipta and Diskus devices of ~1kg CO2-eq per device. This is despite the widely different structures and contents of many DPI devices, in terms of parts and plastics involved in their manufacture. In their evidence and subsequent discussion on usage, Wilkinson et al also failed to mention the differential effects on the environment related to the stages of manufacture of pMDIs and DPIs. For example, in the case of GlaxoSmithKline products, the majority of the CO2 emissions from this company’s DPI devices arise from the production of the plastic container and the active pharmaceutical ingredients (APIs) fluticasone propionate (FP) and salmeterol xinafoate (SX), whereas the primary contributors with pMDIs are emissions resulting from actual usage of the devices, and at the end of the life of the device when it is disposed of. (28)
Furthermore it is not apparent that the lactose monohydrate included in DPI formulations is ever included in the Wilkinson or other models of GWP. Lactose monohydrate is a product of the dairy industry contributing considerably to the carbon footprint: for example one study (29) reported that the total carbon required to produce Whey Powder from raw milk is 13.1 kg CO2-eq per kg of Whey Powder product, a value apparently similar to other, international GWP estimates of Whey Powder production (in the USA). Dairy farming is well known to be carbon intensive, not least due to methane production by the herd, but also from the transport and processing of the Whey Powder products
Wilkinson’s approach of simply addressing the GWP of Inhaled Products is misleading; preferably the methodology of Jolliet et al(30) of a holistic Life Cycle Assessment should also be made. This was performed by Jeswani and Azapagic (31)for pMDIs made with HFA134, HFA227, HFA152 and a GSK dry powder inhaler Diskus device. Although the DPI outperformed the HFA134 and HFA227 inhaled devices for Global Warming Potential as expected, however human toxicity, marine eutrophication and fossil depletion are all worse for DPIs than HFA-based pMDIs, when the holistic life-cycle analysis is undertaken. Thus it may be the case that GWP is better for DPIs, but the full long-term environmental effects were actually worse for eight out of fourteen environmental impact metrics for DPIs than pMDIs. It was also noted by the authors (31) that once HFA152a switchover has been made, that pMDIs will have an equivalent carbon footprint to DPIs, but have improved environmental impact profile than DPIs.

While we are concerned about the environment and the effect humans are having on global warming, we are concerned that this article lacks balance in its discussion and conclusions and puts patients with asthma at risk of an attack through inappropriately stopping or switching inhalers. In our view, asthma and COPD management should focus on prescribing appropriate inhaler devices and ancillary equipment such as spacers that individual patients are able to use efficiently after appropriate education and in the context of management plans agreed with appropriately trained health care professionals. These factors should take priority. (32) There may be suitable opportunities to consider the “greenest” alternatives when patients commence therapy or alter it for reasons of poor disease control or inadequate inhaler technique.

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