A press-released article generated media headlines about kimchi and obesity (Ref 1). Obesity was defined in the study as BMI ≥ 25, in accordance with Korean guidelines (Ref 2). That’s overweight in world health definitions (Ref 3). I’ll proceed using the word obesity, although that’s not what was studied.
Association does not mean causation although the press release inferred this “kimchi, may lower men’s overall risk of obesity.”
The healthy person confounder was (unusually) inverse in this study. The highest kimchi intake group was the least healthy in numerous characteristics. At baseline, those who consumed more kimchi were more likely to be obese and more likely to have abdominal obesity.
The claims had no consistency or rationale.
1) For total kimchi, it was claimed that, compared to < 1 serving of kimchi a day, 1-2 and 2-3 servings per day were associated with lower obesity in men only.
No claims were made for men beyond 3 servings a day.
No claims were made for men and abdominal obesity at any intake of kimchi.
No claims were made for women for obesity or abdominal obesity at any intake of kimchi.
This needed to be explained and it wasn’t. The researchers tried to argue that “Lactobacillus brevis and L. plantarum isolated from kimchi had an anti-obesity effect.” Why in men not women? Why at up to 3 servings but not higher? Why for obesity occasionally and not abdominal obesity ever?
The researchers also tr...
A press-released article generated media headlines about kimchi and obesity (Ref 1). Obesity was defined in the study as BMI ≥ 25, in accordance with Korean guidelines (Ref 2). That’s overweight in world health definitions (Ref 3). I’ll proceed using the word obesity, although that’s not what was studied.
Association does not mean causation although the press release inferred this “kimchi, may lower men’s overall risk of obesity.”
The healthy person confounder was (unusually) inverse in this study. The highest kimchi intake group was the least healthy in numerous characteristics. At baseline, those who consumed more kimchi were more likely to be obese and more likely to have abdominal obesity.
The claims had no consistency or rationale.
1) For total kimchi, it was claimed that, compared to < 1 serving of kimchi a day, 1-2 and 2-3 servings per day were associated with lower obesity in men only.
No claims were made for men beyond 3 servings a day.
No claims were made for men and abdominal obesity at any intake of kimchi.
No claims were made for women for obesity or abdominal obesity at any intake of kimchi.
This needed to be explained and it wasn’t. The researchers tried to argue that “Lactobacillus brevis and L. plantarum isolated from kimchi had an anti-obesity effect.” Why in men not women? Why at up to 3 servings but not higher? Why for obesity occasionally and not abdominal obesity ever?
The researchers also tried to argue that there was a J-shaped association, but there wasn’t. There were no significant results beyond 3 servings.
2) For baechu (cabbage) kimchi, it was claimed that men had lower odds of obesity and abdominal obesity in the highest consumption group vs lowest (but 2-3 servings made no difference to abdominal obesity).
For women, there was an isolated (statistically) significant result for baechu kimchi and lower odds of obesity (relative to < 1 serving) at 2-3 servings a day only (no other intake). There was an isolated result for baechu kimchi and lower odds of abdominal obesity (relative to < 1 serving) at 1-2 servings a day only (no other intake).
Why? Why differences in men and women? Why differences in some servings and not others? Why differences in baechu kimchi but not all kimchi?
3) For kkakdugi (radish) kimchi, the researchers abandoned servings in favour of zero consumption, below and above median consumption. Why? Did servings not give the desired result?
The abstract featured that above median consumption of kkakdugi kimchi was associated with 8% and 11% lower abdominal obesity in men and women respectively (when compared with zero consumption). The abstract didn’t highlight that the association with below average consumption of radish kimchi and abdominal obesity was stronger – 11% in men and 15% in women. The abstract also didn’t highlight that below median consumption was associated with lower general obesity in men and women.
Why? How does radish kimchi make a difference to abdominal obesity when all kimchi doesn’t? What’s the explanation for above average being ‘better’ than none, but below average being ‘better’ still?
The most sense in this paper came from the words: “This research was supported by grants from the World Institute of Kimchi.” “Two authors are members of the staff at the World Institute of Kimchi.”
Ref 1: Jung et al. Association between kimchi consumption and obesity based on BMI and abdominal obesity in Korean adults: a cross-sectional analysis of the Health Examinees study. BMJ Open. 2024. https://bmjopen.bmj.com/content/14/2/e076650
Ref 2: Kim et al. 2020 Korean Society for the Study of Obesity Guidelines for the Management of Obesity in Korea. J Obes Metab Syndr. 2021. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8277596/
Ref 3: Jonathan Q. Purnell. Definitions, Classification, and Epidemiology of Obesity. May 2023. https://www.ncbi.nlm.nih.gov/books/NBK279167/
Due to low recruitment into our trial, we have amended the primary endpoint of our study. The sections affected are summarised below:
1. Primary and secondary outcomes
The primary outcome is no longer the “time” to composite outcome but will now be a composite outcome of the following that will be categorised into a hierarchy according to clinical importance, to be used in the Win ratio analysis below:
• Death - any cause of death
• Severe COPD exacerbation -hospitalised and treated with OCS/Abx or both
• MACE (defined as non-fatal MI, nonfatal stroke and cardiovascular death)
• Hospitalisation with a primary cardiac cause - ischemia, arrythmia, or heart failure
• Moderate COPD exacerbation - not hospitalised but treated with OCS /Abx or both
• Cardiac Hospitalisation - hospitalisation for a cardiac cause other than ischemia, arrythmia or heart failure
• Respiratory Hospitalisation - hospitalisation for a respiratory cause other than COPD exacerbation
• Decrease in FEV1 or greatest FEV1 % drop - largest decrease in FEV1 from post-bronchodilator spirometry at baseline
• Mild COPD exacerbation - treated with increased inhalers / inhaler technique / addition of theophylline
• Higher SGRQ score at 12m and 24m (clinically important change > 4)
• Higher CAT score at 12m and 24m (clinically important change >2)
The secondary outcomes will remain the same, but...
Due to low recruitment into our trial, we have amended the primary endpoint of our study. The sections affected are summarised below:
1. Primary and secondary outcomes
The primary outcome is no longer the “time” to composite outcome but will now be a composite outcome of the following that will be categorised into a hierarchy according to clinical importance, to be used in the Win ratio analysis below:
• Death - any cause of death
• Severe COPD exacerbation -hospitalised and treated with OCS/Abx or both
• MACE (defined as non-fatal MI, nonfatal stroke and cardiovascular death)
• Hospitalisation with a primary cardiac cause - ischemia, arrythmia, or heart failure
• Moderate COPD exacerbation - not hospitalised but treated with OCS /Abx or both
• Cardiac Hospitalisation - hospitalisation for a cardiac cause other than ischemia, arrythmia or heart failure
• Respiratory Hospitalisation - hospitalisation for a respiratory cause other than COPD exacerbation
• Decrease in FEV1 or greatest FEV1 % drop - largest decrease in FEV1 from post-bronchodilator spirometry at baseline
• Mild COPD exacerbation - treated with increased inhalers / inhaler technique / addition of theophylline
• Higher SGRQ score at 12m and 24m (clinically important change > 4)
• Higher CAT score at 12m and 24m (clinically important change >2)
The secondary outcomes will remain the same, but with the addition of:
Time to a composite outcome (includes any) of:
i. All-cause mortality
ii. Hospitalisation for COPD exacerbation
iii. Hospitalisation for primary cardiac cause (ischaemia, arrhythmia or HF)
iv. MACE
2. Sample size estimation and recruitment target
We were unable to recruit the original sample size of 1,164 participants which would have achieved a power of 90% to detect a risk reduction of 25% in the intervention versus the control arm (hazard ratio=0.75). This calculation was based on a survival analysis of time-to-first event using a composite of mortality, MACE and cardiac or respiratory hospitalisation and required a total of 514 participants experiencing a primary endpoint event. Due to the impact of the pandemic which prevented recruitment over an 18 month period, and during which patients with COPD were much less likely to exacerbate (and hence be eligible for PACE), we closed recruitment at 280 participants. To capture additional information and increase power compared to a “time-to-first event” analysis, the primary outcome will be analysed using a Win Ratio approach. Assuming a Win ratio of 1.5 (54% of wins with the beta-blocker arm) and 10% of ties, this approach will lead to 76% power.
3. Statistical analysis
The primary statistical analysis will remain as intention to treat. However, the primary analysis will now be a hierarchical win ratio analysis of the primary composite endpoint: (1) all-cause mortality, (2) cardiac and respiratory hospital admissions, (3) MACE, (4) moderate COPD exacerbations, (5) decrease in FEV1, (6) mild COPD exacerbations, (7) QOL and symptom burden. Every participant randomised to the β-blocker arm will be paired with every participant randomised to the placebo arm. Within each of these pairs, we then proceed to compare outcomes according to the pre-specified hierarchy until a winner is called (or a tie)". The hierarchy of outcomes has been decided by the PACE Steering Committee made up of specialist physicians and researchers. The approach will proceed in a stepwise fashion, moving to the next outcome in the hierarchy, until a decision has been reached for every pair. The win ratio will then be calculated as the proportion of “winners” (the participant in the beta-blocker arm had a better outcome) divided by the proportion of “losers” (the participant in the placebo arm had a better outcome). To complete the interpretation, we will also compute the win odds and net benefit.
Each component of the primary composite outcome will also be analysed separately, both using a win ratio approach and a survival analysis approach. Additionally, annual rate of AECOPD will be analysed by Poisson regression with an over-dispersion correction applied if necessary. Continuous variables, such as the CAT scores, SGRQ and FEV1 will be compared by t-tests and mixed linear models to account for repeated measurements and to examine patterns of change with time.
4. Economic Evaluation
There are not sufficient numbers recruited within Australia for an Australian-specific cost effectiveness analysis. We are currently investigating alternate options for an economic evaluation but may need to shelve this analysis if deemed futile.
We have updated ClinTrials.gov to reflect these changes in our protocol. We will also be publishing our Statistical Analysis Plan prior to database lock.
We thank Dr. Rodriguez for his interest in our article. Dr. Rodriguez raises some questions which were carefully considered by the authors during the development and implementation of this quality improvement initiative. Some of these issues have, in fact, been mentioned in the original manuscript, while others were intentionally not included because the authors felt that they were outside the scope of the paper.
First, we would like to clarify that our use of the adjective “low-value” refers to the definition of Sorenson et al (1), who describe low-value care as “those medical services that provide little or no clinical benefit or may even cause harm to patients” (not, as Dr. Rodriguez seems to have understood, as services provided for patients with arguably trivial presenting complaints). In line with this definition, our quality improvement initiative has proven to reduce low-value appointments by eliminating unnecessary first appointments. It is obvious that such appointments do not provide clinical benefit to patients and may even potentially cause harm through prolonged diagnostic workup, unnecessary disruptions to patients’ schedules, and avoidable travel. Our initiative was implemented in four hospitals which provide tertiary-level services to a population of over 1 million inhabitants in the Madrid area, thus ensuring that the data-driven selection of test order sets was based on a representative sample of the overall population. Given...
We thank Dr. Rodriguez for his interest in our article. Dr. Rodriguez raises some questions which were carefully considered by the authors during the development and implementation of this quality improvement initiative. Some of these issues have, in fact, been mentioned in the original manuscript, while others were intentionally not included because the authors felt that they were outside the scope of the paper.
First, we would like to clarify that our use of the adjective “low-value” refers to the definition of Sorenson et al (1), who describe low-value care as “those medical services that provide little or no clinical benefit or may even cause harm to patients” (not, as Dr. Rodriguez seems to have understood, as services provided for patients with arguably trivial presenting complaints). In line with this definition, our quality improvement initiative has proven to reduce low-value appointments by eliminating unnecessary first appointments. It is obvious that such appointments do not provide clinical benefit to patients and may even potentially cause harm through prolonged diagnostic workup, unnecessary disruptions to patients’ schedules, and avoidable travel. Our initiative was implemented in four hospitals which provide tertiary-level services to a population of over 1 million inhabitants in the Madrid area, thus ensuring that the data-driven selection of test order sets was based on a representative sample of the overall population. Given the complexity of the problem of low-value appointments, we wholeheartedly agree with Dr. Rodriguez that other actions are necessary in order to improve the workflow between primary and specialist care, such as initiatives geared towards improving the quality of referrals from general practitioners to specialist physicians.
As Dr. Rodriguez points out in his rapid response, our article does not present information on the accuracy of diagnosis and treatment, healthcare professional experience, and patient experience. This is indeed true, as the authors felt that these endpoints – although important – were outside the scope of the original manuscript. As we state in the paper, “our study opens the door to several areas for future research, including the effect of the algorithm on the earlier diagnosis of serious conditions such as cancer, and the way that healthcare professionals and patients perceive this new form of delivering healthcare. Further studies are being planned to answer these questions.” (2) We can, in fact, provide the following positive data regarding patient experience (demonstrated to correlate closely with improved clinical results (3)). Independently collected official patient experience scores for specialist outpatient care in the Madrid Healthcare Service consistently position participating hospitals as first for each corresponding district, while internally collected patient experience scores (NPS) (4) have improved from 59.49-65.71 to 64.35-70.51 since the implementation of the initiative.
Regarding the concerns expressed by Dr. Rodriguez about potentially increased backlogs for follow-up appointments, our mean backlog for follow-up appointments has decreased over the last five years, and both our mean backlog for first appointments and for follow-up appointments are lower than the mean for other public hospitals in the same area of Spain (Communidad Autónoma de Madrid). Backlogs for tests have also decreased over the last five years, including MRI and CT scans. However, as we are conscious that these improvements in backlogs are due to multiple factors (and not only to this initiative), we considered that it would be methodologically incorrect to include them as primary outcomes of our analysis.
Dr. Rodriguez expresses certain reservations regarding the ethical aspects of implementing this quality improvement project in the private sector. We beg to differ. The initiative respects the four principles of healthcare ethics (nonmaleficence, beneficence, autonomy, and justice (5)), as it aims to reduce low-value actions while ensuring a standardized approach to diagnostic workup according to current clinical guidelines through the implementation of automatized protocols.
Dr. Rodriguez comments that “it is not clear if the strategy really provides an improvement for public patients in specialized healthcare or is limited to reducing backlog number for first appointments”. To respond to this point, the authors refer to the definition of quality in healthcare proposed by the Institute of Medicine (6). According to this definition, our project demonstrates a clear improvement in at least three of the six domains of quality in healthcare: effectiveness, equity, and timeliness. Effectiveness in healthcare implies avoiding under and overuse of healthcare resources; our initiative reduces the number of follow-up appointments without increasing overall test order rates. Equity in healthcare means ensuring equal access to care; process standardization and the development of test order protocols means that a patient will receive the same diagnostic approach regardless of the level of expertise of the attending physician. Timeliness implies reducing waits and sometimes harmful delays for both those who receive and give care; our project potentially reduces diagnostic delays by improving times to test results. We eagerly await further research which will allow us to evaluate our initiative’s impact on other domains of quality in healthcare: patient-centeredness, effectiveness, and safety.
1. Sorenson C, Japinga M, Crook H, Mcclellan M. Building A Better Health Care System Post-Covid-19: Steps for Reducing Low-Value and Wasteful Care. NEJM Catal. 2020;1;4. doi:10.1056/CAT.20.0368
2. Álvaro de la Parra JA, Del Olmo Rodríguez M, Caramés Sánchez C, et al. Effect of an algorithm for automatic placing of standardised test order sets on low-value appointments and attendance rates at four Spanish teaching hospitals: an interrupted time series analysis. BMJ Open. 2024;14;1:e081158. doi:10.1136/BMJOPEN-2023-081158
3. Doyle C, Lennox L, Bell D. A systematic review of evidence on the links between patient experience and clinical safety and effectiveness. BMJ Open. 2013;3;1:e001570. doi:10.1136/BMJOPEN-2012-001570
4. Nadanyiova M, Gajanova L, Baquero A. Net Promoter Score (NPS) and Customer Satisfaction: Relationship and Efficient Management. Sustainability 2022, Vol 14, Page 2011. 2022;14;4:2011. doi:10.3390/SU14042011
5. Gillon R. Medical ethics: four principles plus attention to scope. BMJ. 1994;309;6948:184. doi:10.1136/BMJ.309.6948.184
6. Institute of Medicine (US) Committee on Quality of Health Care in America. Crossing the Quality Chasm: A New Health System for the 21st Century. National Academies Press; 2001. doi:10.17226/10027
Dr Littorin has published a response to our paper entitled ‘Distribution of intra-nasal naloxone to potential opioid overdose bystanders – effects on overdose mortality in a full region-wide study’. We thank Dr Littorin for his interest in our paper, and we note that he appreciates the fact that we acknowledged a number of limitations in our paper. Our paper described mortality rates in drug overdose after the introduction of a region-wide, large-scale naloxone distribution program aiming to prevent overdose deaths. Our paper reported that the number of fatal overdose cases, calculated per 100,000 inhabitants, was significantly lower during the years following the start of the intervention, compared to a historic time period when the intervention was not available (and both in the whole population and within the narrower group of patients with registered substance use disorder diagnoses). The significant decrease in number of fatal overdoses was seen in men, but not in women. In the absence of randomized controlled trials, which for example are challenging to conduct from an ethical standpoint, the present study lends supports to one previous observational study design where positive findings were seen when regions with higher or lower penetration of the intervention were compared (1).
Dr Littorin argues that the overall decrease in overdoses in 2019-2021, compared to 2013-2017, is likely not associated with the introduction of naloxone, but ins...
Dr Littorin has published a response to our paper entitled ‘Distribution of intra-nasal naloxone to potential opioid overdose bystanders – effects on overdose mortality in a full region-wide study’. We thank Dr Littorin for his interest in our paper, and we note that he appreciates the fact that we acknowledged a number of limitations in our paper. Our paper described mortality rates in drug overdose after the introduction of a region-wide, large-scale naloxone distribution program aiming to prevent overdose deaths. Our paper reported that the number of fatal overdose cases, calculated per 100,000 inhabitants, was significantly lower during the years following the start of the intervention, compared to a historic time period when the intervention was not available (and both in the whole population and within the narrower group of patients with registered substance use disorder diagnoses). The significant decrease in number of fatal overdoses was seen in men, but not in women. In the absence of randomized controlled trials, which for example are challenging to conduct from an ethical standpoint, the present study lends supports to one previous observational study design where positive findings were seen when regions with higher or lower penetration of the intervention were compared (1).
Dr Littorin argues that the overall decrease in overdoses in 2019-2021, compared to 2013-2017, is likely not associated with the introduction of naloxone, but instead may be the result from an overall decreasing trend in the rest of the country. Dr Littorin refers, for example, to a legal ruling suspected to have affected the overall Swedish situation in 2018.
In response to Dr Littorin’s comment, we would like to state that overdose death rates over time in one region may not follow exactly the same trend as in a full country, as seen in another recent paper reporting overdose deaths in the present region (2). Indeed, in that paper, the region assessed in our study (the Skåne region) appeared to display a lower number of overdose deaths than in the rest of Sweden during the years 2015-2017. Thus, it can be concluded that overdose rates in our region thereafter may not change from such a high level as Dr Littorin points out and which may be the case for remaining parts of Sweden (2). Thus, in our region, it is unlikely that a decrease in deaths may only be due to a natural decrease from a peak level.
In addition, in our paper, contrary to Dr Littorin’s statement, we made significant attempts to rule out that decreasing death rates would be due to clinical observations of a decreasing overall opioid use in the region. One limitation of this study, and other observational studies of this type, is that we cannot know the number of opioid users, nor the number of individuals with an opioid use disorder in the region. Therefore, these sensitivity analyses were carried out, and both when we studied social services treatment occasions involving opioids, and when we studied health care occasions related to opioids, there were no signs of a decreasing opioid problem in the region. As part of this, in fact, the number of non-fatal drug overdoses seen by emergency units in the region did not decrease and even appeared to increase from the control period to the intervention period. Thus, our attempts to control for possible community trends in opioids, failed to point out that such a trend would explain the decrease in deaths. Thus, we believe these sensitivity analyses rather lend support to the reporting of decreasing overdose rates in men, although causality can never be concluded from any observational study.
Still, needless to say, large challenges remain in this area. Overdose rates clearly remain very high. Humbly, we acknowledge that numbers of overdoses are subject to changes from one year to another, likely based on a large number of suspected or unknown mediating factors. Thus, although our current findings appeared promising, longer follow-up periods are needed, and further longitudinal assessments are included in our study plan for the present project (3), along with a number of other parameters describing fatal and non-fatal outcomes of opioid use.
References
1. Walley AY, Xuan Z, Hackman HH, et al. Opioid overdose rates and implementation of overdose education and nasal naloxone distribution in Massachusetts: interrupted time series analysis. BMJ 2013;346:f174.
2. Håkansson A, Janfada-Baloo S, Berge J. No obvious effect on mortality from a patient choice reform expanding access to opioid disorder treatment – results from a natural experiment of policy change in Sweden. Subst Abuse Treat Prev Pol 2023;18:64.
3. Troberg K, Isendahl P, Alanko Blomé M, Dahlman D, Håkansson A. Protocol for a multi-site study of the effects of overdose prevention education with naloxone distribution program in Skåne County, Sweden. BMC Psychiatry 2020;20:49.
We are grateful to Niall Keenan, Matthew Knight, Domenique Auger, Martin Hawkings, and Andrew Barlow for their careful consideration of our article.
However, we firmly reject the characterisation of our article as a 'misleading economic analysis’.
Although virtual ward occupancy information is not included in the abstract, it was originally reported in the Discussion. This stated that, ‘This means that for a hospital with 100% occupancy (therefore providing 365 hospital bed days per bed) and 40 virtual ward beds at the capacity found in this study (24%), the virtual ward effect is an increase in the hospital capacity of 3.08 hospital beds per day (1123.62/365).’
Furthermore, in the same section of the article, we explicitly mentioned that ‘increasing the capacity to use the 40 virtual ward beds and reducing the time from hospital admission to virtual ward admission can reduce the cost of a freed-day hospital bed’.
We encourage readers not to solely rely on the abstract but to peruse the full article for a comprehensive understanding of the findings, recommendations, and limitations.
This study shows nicely the problems of digitalized healthcare and related data interpretation. The study has great strength analyzing data of patient referral for a first appointment (FA) in four medium-sized hospitals in Madrid, applying algorithms for test orders prior to the appointment with a specialist in many different pathologies. But these quantitative parameters should be interpreted with caution, as the study fails to give any qualitative measurements that could shed light on the most important question, i.e. if patient care meets the same quality standards in this digitalized setting of reducing backlogs for FA in outpatient care.
The authors claim that the algorithms are applied to “low-value appointments” citing Sorensen et al., 2020 [1] (p. 1), but this article uses the given definition for complaints other than those used for test order algorithms here. The authors define many potentially important symptoms as of “low-value”, instead of targeting the referring physician as modifiable variable to reduce low-value appointments in specialized care, as in fact does one of the cited studies. [2]
Both the primary and the secondary endpoints of the study try to show efficiency and efficacy of the implemented algorithms, but do not give any information about the accuracy of diagnosis and treatment in this patient group, nor does it reveal patients or healthcare professionals satisfaction, need of repetition of ill-suited tests or a second referral from...
This study shows nicely the problems of digitalized healthcare and related data interpretation. The study has great strength analyzing data of patient referral for a first appointment (FA) in four medium-sized hospitals in Madrid, applying algorithms for test orders prior to the appointment with a specialist in many different pathologies. But these quantitative parameters should be interpreted with caution, as the study fails to give any qualitative measurements that could shed light on the most important question, i.e. if patient care meets the same quality standards in this digitalized setting of reducing backlogs for FA in outpatient care.
The authors claim that the algorithms are applied to “low-value appointments” citing Sorensen et al., 2020 [1] (p. 1), but this article uses the given definition for complaints other than those used for test order algorithms here. The authors define many potentially important symptoms as of “low-value”, instead of targeting the referring physician as modifiable variable to reduce low-value appointments in specialized care, as in fact does one of the cited studies. [2]
Both the primary and the secondary endpoints of the study try to show efficiency and efficacy of the implemented algorithms, but do not give any information about the accuracy of diagnosis and treatment in this patient group, nor does it reveal patients or healthcare professionals satisfaction, need of repetition of ill-suited tests or a second referral from primary care of the same patient and complaints. These are largely discussed issues in many publications concerning digitalization in public healthcare. [3]
The authors do not mention if the implementation of their algorithm had a negative effect on backlogs for follow-up by a healthcare specialist of the chronic diseases included in their protocols. It is also to expect that the reduction of backlogs for FA would have a negative impact on backlogs for complementary tests for outpatients other than the studied patient group, especially for complex imaging tests, that were ordered more often than ordered after the patient’s clinical evaluation by a healthcare specialist (see table 1). It is not clear if the strategy really provides an improvement for public patients in specialized healthcare, or is limited to reducing backlog numbers for the FA.
The authors claim “the fact that less than 1% of the patients declined to participate in the new care model points to high patient acceptance” (p. 7). Taking into account that Spain has a universal public healthcare system and that in the Community of Madrid patients are appointed to a unique hospital for specialized care (as are the four hospitals participating in this study), as well as the important backlogs for FA and complementary tests in specialized public healthcare, a standard patient without medical knowledge referred by his primary care physician does not really perceive the possibility to decline this new way of choosing complementary tests before clinical evaluation by a specialist.
The authors mention implementing the public healthcare algorithms in 43 private hospitals belonging to their hospital group (p. 8). Being the public healthcare system universal, private medical insurance is used mainly seeking quicker access to specialized care and testing, as well as second opinions in already diagnosed patients. The implementation of the FA algorithms raises important ethical concerns, because there is no primary healthcare physician referring the patient to a specialist after a first medical exam, and the selection of complementary tests depends entirely on the patients accuracy to complete a digital form asking for their complaints.
In my opinion, the published study presents an interesting proposal to reduce backlogs for a FA in public specialized care, but fail to answer important questions regarding quality assessment in this setting. Digitalization of modern medicine should not loose a critical view of ordering and performing complementary tests, i.e. complementary to a proper clinical orientation of patients.
References
1 Sorenson C, Japinga M, Crook H, et al. Building A better health care system post-COVID-19: steps for reducing low-value and wasteful care. NEJM Catal 2020;1.
2 Doyle J, Abraham S, Feeney L, et al. Clinical decision support for high-cost imaging: a randomized clinical trial. PLoS One 2019;14:e0213373.
3 Iyamu I, Gómez-Ramírez O, Xu AX, Chang HJ, Watt S, Mckee G, Gilbert M. Challenges in the development of digital public health interventions and mapped solutions: Findings from a scoping review. Digit Health 2022; 8:20552076221102255
We read with interest this assessment of the virtual ward at Wrightington, Wigan and Leigh (WWL) Hospitals by Jalilian et al. While we welcome the development of the literature on virtual ward and hospital at home models of care, we do not agree with the economic analysis in the paper which as presented in the abstract has the potential to be highly misleading.
The authors say that they spent £1.051 million for 40 virtual ward beds in 2022. They then calculate that because they had looked after 366 patients and the mean reduction in length of stay was 3.07 days that the cost per bed day saved was £935 (=£1 051 150/ (3.07 days×366 patients)). However they go on to state: “… £935 is calculated based on the WWL’s capacity to use the virtual beds, which was 24% of the potential 14 600 (24-hour) beds per year provided by 40 virtual ward beds… reference to 3508 total days spent by virtual ward patients).”
What this actually means is that they spent £1,051,000 to staff and run 40 virtual beds for a year, only used 10 of them, and then found that this was not cost effective. This is hardly surprising; however because this detail is not given in the abstract it runs the risk of making the paper seriously misleading – as some of the coverage in the medical press has demonstrated. “Virtual ward costs twice that of inpatient care, study finds” Lawrence L, HSJ 25 January 2024.. ...
We read with interest this assessment of the virtual ward at Wrightington, Wigan and Leigh (WWL) Hospitals by Jalilian et al. While we welcome the development of the literature on virtual ward and hospital at home models of care, we do not agree with the economic analysis in the paper which as presented in the abstract has the potential to be highly misleading.
The authors say that they spent £1.051 million for 40 virtual ward beds in 2022. They then calculate that because they had looked after 366 patients and the mean reduction in length of stay was 3.07 days that the cost per bed day saved was £935 (=£1 051 150/ (3.07 days×366 patients)). However they go on to state: “… £935 is calculated based on the WWL’s capacity to use the virtual beds, which was 24% of the potential 14 600 (24-hour) beds per year provided by 40 virtual ward beds… reference to 3508 total days spent by virtual ward patients).”
What this actually means is that they spent £1,051,000 to staff and run 40 virtual beds for a year, only used 10 of them, and then found that this was not cost effective. This is hardly surprising; however because this detail is not given in the abstract it runs the risk of making the paper seriously misleading – as some of the coverage in the medical press has demonstrated. “Virtual ward costs twice that of inpatient care, study finds” Lawrence L, HSJ 25 January 2024.. https://www.hsj.co.uk/finance-and-efficiency/virtual-ward-costs-twice-th...
The authors could just as easily have concluded that if the team at WWL had only opened 10 virtual beds, or had filled all 40 virtual beds then their costs would be £935 x 0.24 = £224 per bed day saved which would then be highly cost effective. This is without touching on other financial benefits such as less use of surge capacity enabling more elective work to be performed, and of course the benefit to patients of receiving care at home.
The real conclusion of this study is that a. it can be difficult to accurately model and then fill virtual ward capacity, and that b. underutilisation is a major bar to cost effectiveness.
Dear editor,
I have read with great interest Al-Wardat et al.'s recent systematic review entitled “Prevalence of attention-deficit hyperactivity disorder in children, adolescents, and adults in the Middle East and North Africa region: a systematic review and meta-analysis." 1. Well-conducted systematic reviews of prevalence and incidence data are generally considered to provide the best evidence for health care planning and resource allocation 2 3.
I have following concerns about methodology of the aforementioned systematic review:
1- In systematic reviews of prevalence and incidence data, the inclusion of gray literature (through specialized databases such as ProQuest), ranging from clinical registries to government reports, census data, and national administrative datasets, is recommended 2. Furthermore, to improve the comprehensiveness of literature searches, additional significant databases, such as PsycINFO and CINAHL, and all related keywords (e.g., attention deficit disorder, ADD, attention-deficit/hyperactivity disorder, etc.), should be considered.
2- The majority of nations in the Middle East and North Africa (MENA) region have official languages other than English, and many scholarly works originating from these regions are published in their respective native languages 4. Restricting inclusion criteria solely to studies in the English language may have inadvertently overlooked a significant portion of relevant literature (i.e....
Dear editor,
I have read with great interest Al-Wardat et al.'s recent systematic review entitled “Prevalence of attention-deficit hyperactivity disorder in children, adolescents, and adults in the Middle East and North Africa region: a systematic review and meta-analysis." 1. Well-conducted systematic reviews of prevalence and incidence data are generally considered to provide the best evidence for health care planning and resource allocation 2 3.
I have following concerns about methodology of the aforementioned systematic review:
1- In systematic reviews of prevalence and incidence data, the inclusion of gray literature (through specialized databases such as ProQuest), ranging from clinical registries to government reports, census data, and national administrative datasets, is recommended 2. Furthermore, to improve the comprehensiveness of literature searches, additional significant databases, such as PsycINFO and CINAHL, and all related keywords (e.g., attention deficit disorder, ADD, attention-deficit/hyperactivity disorder, etc.), should be considered.
2- The majority of nations in the Middle East and North Africa (MENA) region have official languages other than English, and many scholarly works originating from these regions are published in their respective native languages 4. Restricting inclusion criteria solely to studies in the English language may have inadvertently overlooked a significant portion of relevant literature (i.e., 22% of all articles) 1.
3- The exclusion of 180 studies due to retrieval failures raises concerns for publication bias.
4- The authors indicated that the Middle East and North Africa (MENA) region consists of 20 countries with an estimated population of around 355 million. However, it's noteworthy that, based on the World Bank's definition, the MENA region encompasses 21 countries and a population of 493,279,469 people.
5- The use of the Newcastle Ottawa Scale, originally designed for cohort and case-control studies, may not be suitable for the critical appraisal of prevalence studies. For studies focusing on prevalence and incidence, it is advisable to employ the Joanna Briggs Institute (JBI) critical appraisal tool, which is specifically tailored to assess the quality and methodological rigor of prevalence and incident studies 5.
6- There was high heterogeneity between studies included in this systematic review. Exploration of heterogeneity through subgroup analyses (for example, method and criteria of diagnosis) or meta-regression (for instance based on the year of study), allowing for a more nuanced understanding of the factors contributing to the observed heterogeneity in study results 6.
7- The authors used I2 statistics as an indication of statistical heterogeneity amongst studies. In systematic reviews of prevalence data, where studies contribute large datasets with precise confidence intervals, the reliance solely on I2 may be misleading 2.
References
1. Al-Wardat M, Etoom M, Almhdawi KA, et al. Prevalence of attention-deficit hyperactivity disorder in children, adolescents and adults in the Middle East and North Africa region: a systematic review and meta-analysis. BMJ Open 2024;14(1):e078849. doi: 10.1136/bmjopen-2023-078849 [published Online First: 2024/01/19]
2. Borges Migliavaca C, Stein C, Colpani V, et al. How are systematic reviews of prevalence conducted? A methodological study. BMC Medical Research Methodology 2020;20(1):96. doi: 10.1186/s12874-020-00975-3
3. Munn Z, Moola S, Lisy K, et al. Systematic reviews of prevalence and incidence. Joanna Briggs Institute reviewer’s manual Adelaide, South Australia: The Joanna Briggs Institute 2017:5.1-5.5.
4. Habibzadeh F. A snapshot of medical journals from the Middle East. Lancet 2006;367(9515):978. doi: 10.1016/S0140-6736(06)68411-0 [published Online First: 2006/03/29]
5. Munn Z, Moola S, Riitano D, et al. The Development of a Critical Appraisal Tool for Use in Systematic Reviews: Addressing Questions of Prevalence. International Journal of Health Policy and Management 2014;3(3):123-28. doi: 10.15171/ijhpm.2014.71
6. Deeks JJ HJ, Altman DG (editors). Chapter 10: Analysing data and undertaking meta-analyses. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.4 (updated August 2023). Cochrane, 2023. Available from www.training.cochrane.org/handbook.
The hypothesized mechanisms for reduction of cardiovascular risk by sodium-glucose cotransporter-2 (SGLT2) inhibitors are multifactorial. Among these mechanisms, Professor Tomoyuki Kawada made a comment on the relative contribution of two clinically important markers, serum uric acid and kidney function, to SGLT2 inhibitors-driven risk reduction of cardiovascular disease.
Inzucchi et al. explored the potential underlying mechanisms behind the empagliflozin on cardiovascular benefit by conducting post hoc mediation analysis of data from the EMPA-REG OUTCOME trial. 1 The authors demonstrated that changes in plasma volume status (hematocrit or hemoglobin) had the largest impact (mediated around 50% of the treatment effect) on the cardiovascular death with empagliflozin versus placebo. In line with Professor Tomoyuki Kawada’s point of view, the authors reported that changes in uric acid had a greater mediation effect on the treatment effect of empagliflozin on cardiovascular risk reduction, whereas changes in kidney function had no or negligible effects (percentage mediation was 24.6% for uric acid, 11.1% for logUACR, and 5.3% for eGFR). The uricosuric effect of the SGLT2 inhibitors is linked to urinary glucose excretion and caused by blockage of renal tubular uric acid transporters. 2
The relationship between changes in albuminuria and reduction in cardiovascular risk with SGLT2 inhibitors therapy depends on baseline albuminuria status. Waijer el al. assessed whet...
The hypothesized mechanisms for reduction of cardiovascular risk by sodium-glucose cotransporter-2 (SGLT2) inhibitors are multifactorial. Among these mechanisms, Professor Tomoyuki Kawada made a comment on the relative contribution of two clinically important markers, serum uric acid and kidney function, to SGLT2 inhibitors-driven risk reduction of cardiovascular disease.
Inzucchi et al. explored the potential underlying mechanisms behind the empagliflozin on cardiovascular benefit by conducting post hoc mediation analysis of data from the EMPA-REG OUTCOME trial. 1 The authors demonstrated that changes in plasma volume status (hematocrit or hemoglobin) had the largest impact (mediated around 50% of the treatment effect) on the cardiovascular death with empagliflozin versus placebo. In line with Professor Tomoyuki Kawada’s point of view, the authors reported that changes in uric acid had a greater mediation effect on the treatment effect of empagliflozin on cardiovascular risk reduction, whereas changes in kidney function had no or negligible effects (percentage mediation was 24.6% for uric acid, 11.1% for logUACR, and 5.3% for eGFR). The uricosuric effect of the SGLT2 inhibitors is linked to urinary glucose excretion and caused by blockage of renal tubular uric acid transporters. 2
The relationship between changes in albuminuria and reduction in cardiovascular risk with SGLT2 inhibitors therapy depends on baseline albuminuria status. Waijer el al. assessed whether albuminuria is a mediator for effects of empagliflozin on cardiovascular and renal outcomes in the EMPA-REG OUTCOME trial. 3 For patients with micro- or macroalbuminuria, albuminuria mediated a larger effect on cardiovascular event, whereas there was a smaller mediated effect in those with normoalbuminuria (mediated proportion was 58.2% for UACR level ≥30 mg/g vs 7.9% for UACR level <30 mg/g on major adverse cardiovascular event). The reduction in albuminuria might serve as a mediating factor, possibly linked to decreased intraglomerular pressure, which in turn could result from the restoration of tubuloglomerular feedback. 4
The precise contributions of individual putative mechanism to the reduction in cardiovascular risk with SGLT2 inhibitors remain to be elucidated and further mechanistic studies are required in the future.
References
1. Inzucchi SE, Zinman B, Fitchett D, et al. How Does Empagliflozin Reduce Cardiovascular Mortality? Insights From a Mediation Analysis of the EMPA-REG OUTCOME Trial. Diabetes Care 2018;41(2):356-63. doi: 10.2337/dc17-1096 [published Online First: 20171204]
2. Suijk DLS, van Baar MJB, van Bommel EJM, et al. SGLT2 Inhibition and Uric Acid Excretion in Patients with Type 2 Diabetes and Normal Kidney Function. Clin J Am Soc Nephrol 2022;17(5):663-71. doi: 10.2215/cjn.11480821 [published Online First: 20220323]
3. Waijer SW, Xie D, Inzucchi SE, et al. Short-Term Changes in Albuminuria and Risk of Cardiovascular and Renal Outcomes in Type 2 Diabetes Mellitus: A Post Hoc Analysis of the EMPA-REG OUTCOME Trial. J Am Heart Assoc 2020;9(18):e016976. doi: 10.1161/jaha.120.016976 [published Online First: 20200906]
4. Cherney DZ, Perkins BA, Soleymanlou N, et al. Renal hemodynamic effect of sodium-glucose cotransporter 2 inhibition in patients with type 1 diabetes mellitus. Circulation 2014;129(5):587-97. doi: 10.1161/circulationaha.113.005081 [published Online First: 20131213]
Tsai et al. conducted a meta-analysis to evaluate the cardiovascular and renal efficacy and safety of sodium-glucose cotransporter-2 (SGLT2) inhibitors in patients without diabetes (1). Risk ratios (RRs) (95% confidence intervals [CIs]) of SGLT2 inhibitors for the composite cardiovascular outcome, cardiovascular death, hospitalization for heart failure, and the composite renal outcome were 0.79 (0.71 to 0.87), 0.85 (0.74 to 0.99), 0.72 (0.62 to 0.82), and 0.64 (0.48 to 0.85), respectively. The authors clarified that SGLT2 inhibitors had cardiorenal benefits and increased risk for urinary tract and genital infection in patients without diabetes. I present comments with special reference to the level of serum uric acid and kidney function.
Zhao et al. conducted a meta-analysis to evaluate the effects of SGLT2 inhibitors on serum uric acid (SUA) in patients with type 2 diabetes mellitus (T2DM) (2). Any of the SGLT2 inhibitors significantly decreased SUA levels against controls, and empagliflozin presented a predominant reduction in SUA. Increase of the urinary excretion of uric acid by SGLT2 inhibitor is not simply caused by the increased urinary volume, but the inhibition of uric acid reabsorption by SGLT2 inhibitor would be made at the collecting duct in the renal tubule (3). I suspect that the urinary excretion rate of uric acid would be increased by SGLT2 inhibitor-induced glycosuria plus active uric acid reabsorption mechanism via insulin resistance.
Tsai et al. conducted a meta-analysis to evaluate the cardiovascular and renal efficacy and safety of sodium-glucose cotransporter-2 (SGLT2) inhibitors in patients without diabetes (1). Risk ratios (RRs) (95% confidence intervals [CIs]) of SGLT2 inhibitors for the composite cardiovascular outcome, cardiovascular death, hospitalization for heart failure, and the composite renal outcome were 0.79 (0.71 to 0.87), 0.85 (0.74 to 0.99), 0.72 (0.62 to 0.82), and 0.64 (0.48 to 0.85), respectively. The authors clarified that SGLT2 inhibitors had cardiorenal benefits and increased risk for urinary tract and genital infection in patients without diabetes. I present comments with special reference to the level of serum uric acid and kidney function.
Zhao et al. conducted a meta-analysis to evaluate the effects of SGLT2 inhibitors on serum uric acid (SUA) in patients with type 2 diabetes mellitus (T2DM) (2). Any of the SGLT2 inhibitors significantly decreased SUA levels against controls, and empagliflozin presented a predominant reduction in SUA. Increase of the urinary excretion of uric acid by SGLT2 inhibitor is not simply caused by the increased urinary volume, but the inhibition of uric acid reabsorption by SGLT2 inhibitor would be made at the collecting duct in the renal tubule (3). I suspect that the urinary excretion rate of uric acid would be increased by SGLT2 inhibitor-induced glycosuria plus active uric acid reabsorption mechanism via insulin resistance.
Tang et al. reported that there were advantages for major adverse cardiovascular events, cardiovascular death/hospitalization, or composite renal outcomes with use of SGLT2 inhibitors (4). Wanner et al. reported the prognostic effect of empagliflozin in patients with T2DM, and the level of glomerular filtration rate and urine albumin-creatinine ratio did not modify the effect of empagliflozin on clinical outcomes (5). Taken together, the risk reduction of cardiovascular disease by sodium-SGLT2 inhibitors may partly be caused by the mechanism of reducing SUA, not caused by increased level of kidney function.
References
1. Tsai WC, Hsu SP, Chiu YL, Yet al. Cardiovascular and renal efficacy and safety of sodium-glucose cotransporter-2 inhibitors in patients without diabetes: a systematic review and meta-analysis of randomised placebo-controlled trials. BMJ Open 2022;12(10):e060655.
2. Zhao Y, Xu L, Tian D, et al. Effects of sodium-glucose co-transporter 2 (SGLT2) inhibitors on serum uric acid level: A meta-analysis of randomized controlled trials. Diabetes Obes Metab 2018;2082):458-462.
3. Ahmadieh H, Azar S. Effects of sodium glucose cotransporter-2 inhibitors on serum uric acid in type 2 diabetes mellitus. Diabetes Technol Ther 2017;19(9):507-512.
4. Tang H, Kimmel SE, Smith SM, et al. Comparable cardiorenal benefits of SGLT2 inhibitors and GLP-1RAs in Asian and White populations: An updated meta-analysis of results from randomized outcome trials. Diabetes Care 2022;45(4):1007-1012.
5. Wanner C, Lachin JM, Inzucchi SE, et al. Empagliflozin and clinical outcomes in patients with type 2 diabetes mellitus, established cardiovascular disease, and chronic kidney disease. Circulation 2018;137(2):119-129.
A press-released article generated media headlines about kimchi and obesity (Ref 1). Obesity was defined in the study as BMI ≥ 25, in accordance with Korean guidelines (Ref 2). That’s overweight in world health definitions (Ref 3). I’ll proceed using the word obesity, although that’s not what was studied.
Show MoreAssociation does not mean causation although the press release inferred this “kimchi, may lower men’s overall risk of obesity.”
The healthy person confounder was (unusually) inverse in this study. The highest kimchi intake group was the least healthy in numerous characteristics. At baseline, those who consumed more kimchi were more likely to be obese and more likely to have abdominal obesity.
The claims had no consistency or rationale.
1) For total kimchi, it was claimed that, compared to < 1 serving of kimchi a day, 1-2 and 2-3 servings per day were associated with lower obesity in men only.
No claims were made for men beyond 3 servings a day.
No claims were made for men and abdominal obesity at any intake of kimchi.
No claims were made for women for obesity or abdominal obesity at any intake of kimchi.
This needed to be explained and it wasn’t. The researchers tried to argue that “Lactobacillus brevis and L. plantarum isolated from kimchi had an anti-obesity effect.” Why in men not women? Why at up to 3 servings but not higher? Why for obesity occasionally and not abdominal obesity ever?
The researchers also tr...
Due to low recruitment into our trial, we have amended the primary endpoint of our study. The sections affected are summarised below:
1. Primary and secondary outcomes
The primary outcome is no longer the “time” to composite outcome but will now be a composite outcome of the following that will be categorised into a hierarchy according to clinical importance, to be used in the Win ratio analysis below:
• Death - any cause of death
• Severe COPD exacerbation -hospitalised and treated with OCS/Abx or both
• MACE (defined as non-fatal MI, nonfatal stroke and cardiovascular death)
• Hospitalisation with a primary cardiac cause - ischemia, arrythmia, or heart failure
• Moderate COPD exacerbation - not hospitalised but treated with OCS /Abx or both
• Cardiac Hospitalisation - hospitalisation for a cardiac cause other than ischemia, arrythmia or heart failure
• Respiratory Hospitalisation - hospitalisation for a respiratory cause other than COPD exacerbation
• Decrease in FEV1 or greatest FEV1 % drop - largest decrease in FEV1 from post-bronchodilator spirometry at baseline
• Mild COPD exacerbation - treated with increased inhalers / inhaler technique / addition of theophylline
• Higher SGRQ score at 12m and 24m (clinically important change > 4)
• Higher CAT score at 12m and 24m (clinically important change >2)
The secondary outcomes will remain the same, but...
Show MoreDear Editor,
We thank Dr. Rodriguez for his interest in our article. Dr. Rodriguez raises some questions which were carefully considered by the authors during the development and implementation of this quality improvement initiative. Some of these issues have, in fact, been mentioned in the original manuscript, while others were intentionally not included because the authors felt that they were outside the scope of the paper.
First, we would like to clarify that our use of the adjective “low-value” refers to the definition of Sorenson et al (1), who describe low-value care as “those medical services that provide little or no clinical benefit or may even cause harm to patients” (not, as Dr. Rodriguez seems to have understood, as services provided for patients with arguably trivial presenting complaints). In line with this definition, our quality improvement initiative has proven to reduce low-value appointments by eliminating unnecessary first appointments. It is obvious that such appointments do not provide clinical benefit to patients and may even potentially cause harm through prolonged diagnostic workup, unnecessary disruptions to patients’ schedules, and avoidable travel. Our initiative was implemented in four hospitals which provide tertiary-level services to a population of over 1 million inhabitants in the Madrid area, thus ensuring that the data-driven selection of test order sets was based on a representative sample of the overall population. Given...
Show MoreDear Editor,
Dr Littorin has published a response to our paper entitled ‘Distribution of intra-nasal naloxone to potential opioid overdose bystanders – effects on overdose mortality in a full region-wide study’. We thank Dr Littorin for his interest in our paper, and we note that he appreciates the fact that we acknowledged a number of limitations in our paper. Our paper described mortality rates in drug overdose after the introduction of a region-wide, large-scale naloxone distribution program aiming to prevent overdose deaths. Our paper reported that the number of fatal overdose cases, calculated per 100,000 inhabitants, was significantly lower during the years following the start of the intervention, compared to a historic time period when the intervention was not available (and both in the whole population and within the narrower group of patients with registered substance use disorder diagnoses). The significant decrease in number of fatal overdoses was seen in men, but not in women. In the absence of randomized controlled trials, which for example are challenging to conduct from an ethical standpoint, the present study lends supports to one previous observational study design where positive findings were seen when regions with higher or lower penetration of the intervention were compared (1).
Dr Littorin argues that the overall decrease in overdoses in 2019-2021, compared to 2013-2017, is likely not associated with the introduction of naloxone, but ins...
Show MoreWe are grateful to Niall Keenan, Matthew Knight, Domenique Auger, Martin Hawkings, and Andrew Barlow for their careful consideration of our article.
However, we firmly reject the characterisation of our article as a 'misleading economic analysis’.
Although virtual ward occupancy information is not included in the abstract, it was originally reported in the Discussion. This stated that, ‘This means that for a hospital with 100% occupancy (therefore providing 365 hospital bed days per bed) and 40 virtual ward beds at the capacity found in this study (24%), the virtual ward effect is an increase in the hospital capacity of 3.08 hospital beds per day (1123.62/365).’
Furthermore, in the same section of the article, we explicitly mentioned that ‘increasing the capacity to use the 40 virtual ward beds and reducing the time from hospital admission to virtual ward admission can reduce the cost of a freed-day hospital bed’.
We encourage readers not to solely rely on the abstract but to peruse the full article for a comprehensive understanding of the findings, recommendations, and limitations.
This study shows nicely the problems of digitalized healthcare and related data interpretation. The study has great strength analyzing data of patient referral for a first appointment (FA) in four medium-sized hospitals in Madrid, applying algorithms for test orders prior to the appointment with a specialist in many different pathologies. But these quantitative parameters should be interpreted with caution, as the study fails to give any qualitative measurements that could shed light on the most important question, i.e. if patient care meets the same quality standards in this digitalized setting of reducing backlogs for FA in outpatient care.
Show MoreThe authors claim that the algorithms are applied to “low-value appointments” citing Sorensen et al., 2020 [1] (p. 1), but this article uses the given definition for complaints other than those used for test order algorithms here. The authors define many potentially important symptoms as of “low-value”, instead of targeting the referring physician as modifiable variable to reduce low-value appointments in specialized care, as in fact does one of the cited studies. [2]
Both the primary and the secondary endpoints of the study try to show efficiency and efficacy of the implemented algorithms, but do not give any information about the accuracy of diagnosis and treatment in this patient group, nor does it reveal patients or healthcare professionals satisfaction, need of repetition of ill-suited tests or a second referral from...
We read with interest this assessment of the virtual ward at Wrightington, Wigan and Leigh (WWL) Hospitals by Jalilian et al. While we welcome the development of the literature on virtual ward and hospital at home models of care, we do not agree with the economic analysis in the paper which as presented in the abstract has the potential to be highly misleading.
The authors say that they spent £1.051 million for 40 virtual ward beds in 2022. They then calculate that because they had looked after 366 patients and the mean reduction in length of stay was 3.07 days that the cost per bed day saved was £935 (=£1 051 150/ (3.07 days×366 patients)). However they go on to state: “… £935 is calculated based on the WWL’s capacity to use the virtual beds, which was 24% of the potential 14 600 (24-hour) beds per year provided by 40 virtual ward beds… reference to 3508 total days spent by virtual ward patients).”
Show MoreWhat this actually means is that they spent £1,051,000 to staff and run 40 virtual beds for a year, only used 10 of them, and then found that this was not cost effective. This is hardly surprising; however because this detail is not given in the abstract it runs the risk of making the paper seriously misleading – as some of the coverage in the medical press has demonstrated. “Virtual ward costs twice that of inpatient care, study finds” Lawrence L, HSJ 25 January 2024..
...
Dear editor,
Show MoreI have read with great interest Al-Wardat et al.'s recent systematic review entitled “Prevalence of attention-deficit hyperactivity disorder in children, adolescents, and adults in the Middle East and North Africa region: a systematic review and meta-analysis." 1. Well-conducted systematic reviews of prevalence and incidence data are generally considered to provide the best evidence for health care planning and resource allocation 2 3.
I have following concerns about methodology of the aforementioned systematic review:
1- In systematic reviews of prevalence and incidence data, the inclusion of gray literature (through specialized databases such as ProQuest), ranging from clinical registries to government reports, census data, and national administrative datasets, is recommended 2. Furthermore, to improve the comprehensiveness of literature searches, additional significant databases, such as PsycINFO and CINAHL, and all related keywords (e.g., attention deficit disorder, ADD, attention-deficit/hyperactivity disorder, etc.), should be considered.
2- The majority of nations in the Middle East and North Africa (MENA) region have official languages other than English, and many scholarly works originating from these regions are published in their respective native languages 4. Restricting inclusion criteria solely to studies in the English language may have inadvertently overlooked a significant portion of relevant literature (i.e....
The hypothesized mechanisms for reduction of cardiovascular risk by sodium-glucose cotransporter-2 (SGLT2) inhibitors are multifactorial. Among these mechanisms, Professor Tomoyuki Kawada made a comment on the relative contribution of two clinically important markers, serum uric acid and kidney function, to SGLT2 inhibitors-driven risk reduction of cardiovascular disease.
Show MoreInzucchi et al. explored the potential underlying mechanisms behind the empagliflozin on cardiovascular benefit by conducting post hoc mediation analysis of data from the EMPA-REG OUTCOME trial. 1 The authors demonstrated that changes in plasma volume status (hematocrit or hemoglobin) had the largest impact (mediated around 50% of the treatment effect) on the cardiovascular death with empagliflozin versus placebo. In line with Professor Tomoyuki Kawada’s point of view, the authors reported that changes in uric acid had a greater mediation effect on the treatment effect of empagliflozin on cardiovascular risk reduction, whereas changes in kidney function had no or negligible effects (percentage mediation was 24.6% for uric acid, 11.1% for logUACR, and 5.3% for eGFR). The uricosuric effect of the SGLT2 inhibitors is linked to urinary glucose excretion and caused by blockage of renal tubular uric acid transporters. 2
The relationship between changes in albuminuria and reduction in cardiovascular risk with SGLT2 inhibitors therapy depends on baseline albuminuria status. Waijer el al. assessed whet...
Tsai et al. conducted a meta-analysis to evaluate the cardiovascular and renal efficacy and safety of sodium-glucose cotransporter-2 (SGLT2) inhibitors in patients without diabetes (1). Risk ratios (RRs) (95% confidence intervals [CIs]) of SGLT2 inhibitors for the composite cardiovascular outcome, cardiovascular death, hospitalization for heart failure, and the composite renal outcome were 0.79 (0.71 to 0.87), 0.85 (0.74 to 0.99), 0.72 (0.62 to 0.82), and 0.64 (0.48 to 0.85), respectively. The authors clarified that SGLT2 inhibitors had cardiorenal benefits and increased risk for urinary tract and genital infection in patients without diabetes. I present comments with special reference to the level of serum uric acid and kidney function.
Zhao et al. conducted a meta-analysis to evaluate the effects of SGLT2 inhibitors on serum uric acid (SUA) in patients with type 2 diabetes mellitus (T2DM) (2). Any of the SGLT2 inhibitors significantly decreased SUA levels against controls, and empagliflozin presented a predominant reduction in SUA. Increase of the urinary excretion of uric acid by SGLT2 inhibitor is not simply caused by the increased urinary volume, but the inhibition of uric acid reabsorption by SGLT2 inhibitor would be made at the collecting duct in the renal tubule (3). I suspect that the urinary excretion rate of uric acid would be increased by SGLT2 inhibitor-induced glycosuria plus active uric acid reabsorption mechanism via insulin resistance.
Tang e...
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