The gameChange trial primary outcome was avoidance and distress in real-life situations measured using a behavioural assessment task (Oxford-Behavioural Assessment Task, O-BAT). The O-BAT is administered with a trial research assistant and the patient is asked to go into a (personalised) hierarchy of five real world situations that they find anxiety-provoking (e.g. go into a local café or shop). The assessment records how many of the five steps the individual completed (avoidance score) and their level of anxiety (distress score).
Why the measure had to be changed
Due to the COVID-19 lockdown measures implemented in March 2020, we were not allowed to administer the O-BAT. It would involve face-to-face contact, which was prohibited by the NHS trusts. It was also the case that many locations (e.g. cafes, shops) used in the O-BAT were closed. All patient recruitment into the trial was suspended for six months but remote assessments continued for those who had already entered into the trial.
The replacement primary outcome
We had already developed a self-report version of the O-BAT, which was a secondary outcome measure. In the published protocol this is called the ‘self-report O-BAT’. We now call the measure the Oxford Agoraphobic Avoidance Scale (O-AS) (Lambe et al, submitted). We have made this self-report version of the O-BAT the primary outcome variable. As in the original O-BAT, the O-AS gives an avoidance...
The gameChange trial primary outcome was avoidance and distress in real-life situations measured using a behavioural assessment task (Oxford-Behavioural Assessment Task, O-BAT). The O-BAT is administered with a trial research assistant and the patient is asked to go into a (personalised) hierarchy of five real world situations that they find anxiety-provoking (e.g. go into a local café or shop). The assessment records how many of the five steps the individual completed (avoidance score) and their level of anxiety (distress score).
Why the measure had to be changed
Due to the COVID-19 lockdown measures implemented in March 2020, we were not allowed to administer the O-BAT. It would involve face-to-face contact, which was prohibited by the NHS trusts. It was also the case that many locations (e.g. cafes, shops) used in the O-BAT were closed. All patient recruitment into the trial was suspended for six months but remote assessments continued for those who had already entered into the trial.
The replacement primary outcome
We had already developed a self-report version of the O-BAT, which was a secondary outcome measure. In the published protocol this is called the ‘self-report O-BAT’. We now call the measure the Oxford Agoraphobic Avoidance Scale (O-AS) (Lambe et al, submitted). We have made this self-report version of the O-BAT the primary outcome variable. As in the original O-BAT, the O-AS gives an avoidance and distress score, which means it can be used to answer the original main trial question. We therefore had a ready-made assessment to replace the original outcome scale. As the O-AS is self-report it has been possible to administer remotely to trial participants throughout the pandemic and therefore maintain follow-up rates.
The amendment to replace the O-BAT with the O-AS was agreed by the trial Data Monitoring and Ethics Committee (DMEC) and the trial sponsor. The amendment to the protocol was approved by the NHS South Central – Oxford B Research Ethics Committee on 24th August 2020 (REC reference: 19/SC/0075) and the Health Research Authority on 3rd September 2020 (IRAS ID: 256895). This amendment was made before any inspection of trial outcome data. The original O-BAT will be a secondary outcome for those who completed it before the pandemic.
Daniel Freeman (chief investigator), Ariane Petit (trial coordinator), Ly-Mee Yu (lead statistician)
Dear Ms. Manning,
thank you very much for your response and helpful comments to our study protocol.
You point out that we might have missed to report on two important reviews conducted in the field of stroke survivors' needs. This might be due to our focus on stroke-related aphasia and the accordingly constructed search algorithm. Since the focus of our work will be the comparison of the results of two synthesis methods, we aimed to rule out that QES exist that duplicate our research question. Either way, thank you for pointing us to these important reviews. We will review those studies and use them to refine and inform our research algorithm if neccessary.
We also want to apologize for not having reproduced the results of your study in an appropriate way. We will keep your critique in mind while conducting our QES using two different approaches.
Park et al. identified risk factors for in-hospital mortality within 56 days in patients with severe infection of COVID-19 (1). The adjusted hazard ratios (95% confidence interval [CI]) of fibrosis-4 index (FIB-4), lymphocyte count, diabetes, and systemic inflammatory response syndrome in patients with COVID-19 receiving respiratory support for mortality were 2.784 (1.691 to 4.585), 0.480 (0.271 to 0.852), 1.917 (1.181 to 3.111), and 1.714 (1.048 to 2.802), respectively. A number of risk factors were also inversely related to survival in a dose-response manner. I present information regarding FIB-4 index and mortality in patients with COVID-19.
First, Li et al. assessed the association of FIB-4 with biomarkers and clinical outcome in hospitalized patients with COVID-19 (2). Among the 202 participants, 22 died. The median values of FIB-4 in participants who survived and died were 1.91 and 3.98, respectively. The adjusted odds ratio (OR) (95% CI) of patients with each one-unit increment in FIB-4 for mortality was 1.79 (1.36 to 2.35). Although the number of events was small, FIB-4 was selected as a simple and inexpensive approach for the risk assessment in patients with COVID-19.
Second, Lopez-Mendez et al. evaluated the association of liver steatosis and fibrosis with clinical outcomes.in patients with COVID-19 (3). ORs (95% CIs) of patients with liver fibrosis by FIB-4 for ICU admission and mortality were 1.74 (1.74 to 2.68) and 6.45 (2.01 to 20.83), but signi...
Park et al. identified risk factors for in-hospital mortality within 56 days in patients with severe infection of COVID-19 (1). The adjusted hazard ratios (95% confidence interval [CI]) of fibrosis-4 index (FIB-4), lymphocyte count, diabetes, and systemic inflammatory response syndrome in patients with COVID-19 receiving respiratory support for mortality were 2.784 (1.691 to 4.585), 0.480 (0.271 to 0.852), 1.917 (1.181 to 3.111), and 1.714 (1.048 to 2.802), respectively. A number of risk factors were also inversely related to survival in a dose-response manner. I present information regarding FIB-4 index and mortality in patients with COVID-19.
First, Li et al. assessed the association of FIB-4 with biomarkers and clinical outcome in hospitalized patients with COVID-19 (2). Among the 202 participants, 22 died. The median values of FIB-4 in participants who survived and died were 1.91 and 3.98, respectively. The adjusted odds ratio (OR) (95% CI) of patients with each one-unit increment in FIB-4 for mortality was 1.79 (1.36 to 2.35). Although the number of events was small, FIB-4 was selected as a simple and inexpensive approach for the risk assessment in patients with COVID-19.
Second, Lopez-Mendez et al. evaluated the association of liver steatosis and fibrosis with clinical outcomes.in patients with COVID-19 (3). ORs (95% CIs) of patients with liver fibrosis by FIB-4 for ICU admission and mortality were 1.74 (1.74 to 2.68) and 6.45 (2.01 to 20.83), but significance disappeared by the adjustment. In any case, stable risk estimation by FIB-4 for health outcomes should be conducted by further studies.
Reference
1. Park JG, Kang MK, Lee YR, et al. Fibrosis-4 index as a predictor for mortality in hospitalised patients with COVID-19: a retrospective multicentre cohort study. BMJ Open 2020;10(11):e041989.
2. Li Y, Regan J, Fajnzylber J, et al. Liver Fibrosis Index FIB-4 Is Associated With Mortality in COVID-19. Hepatol Commun 2020;5(3):434–45.
3. Lopez-Mendez I, Aquino-Matus J, Gall SM, et al. Association of liver steatosis and fibrosis with clinical outcomes in patients with SARS-CoV-2 infection (COVID-19). Ann Hepatol 2021;20:100271.
Medisauskaite and Kamau conducted a randomized controlled trial to investigate the association between occupational distress and the risk of health problems among UK doctors (1). Occupational distress and job factors increased the odds of doctors using substances, having sleep problems, presenting with frequent symptoms of ill health and binge-eating. Especially, burnout increased the risk of all types of sleep problems, including difficulty falling/staying asleep, insomnia. I suppose that association might be caused from occupational distress to the risk of health problems in an intervention study. I have a general concern on the inter-relationship among health problems, and discussed the relationship between alcohol use and sleep problem as an example.
First, Hu et al. conducted a meta-analysis to examine the relationship of alcohol consumption with incidence of sleep disorder (2). Pooled odds ratios (ORs) (95% confidence intervals [CIs]) of mild/moderate and heavy alcohol consumptions for the incidence of sleep disorder were 1.37 (1.22, 1.54) and 1.22 (0.94, 1.60). They selected sleepiness and insomnia as sleep problems, and obstructive sleep apnea was not selected in spite of the frequent sleep disorders in drinkers (3). In addition, there is a space of evaluating dose-response relationship.
Second, Britton et al. evaluated the association between alcohol consumption and sleep disorders among older people (4). For men, OR (95% CI) of drinking more than 21...
Medisauskaite and Kamau conducted a randomized controlled trial to investigate the association between occupational distress and the risk of health problems among UK doctors (1). Occupational distress and job factors increased the odds of doctors using substances, having sleep problems, presenting with frequent symptoms of ill health and binge-eating. Especially, burnout increased the risk of all types of sleep problems, including difficulty falling/staying asleep, insomnia. I suppose that association might be caused from occupational distress to the risk of health problems in an intervention study. I have a general concern on the inter-relationship among health problems, and discussed the relationship between alcohol use and sleep problem as an example.
First, Hu et al. conducted a meta-analysis to examine the relationship of alcohol consumption with incidence of sleep disorder (2). Pooled odds ratios (ORs) (95% confidence intervals [CIs]) of mild/moderate and heavy alcohol consumptions for the incidence of sleep disorder were 1.37 (1.22, 1.54) and 1.22 (0.94, 1.60). They selected sleepiness and insomnia as sleep problems, and obstructive sleep apnea was not selected in spite of the frequent sleep disorders in drinkers (3). In addition, there is a space of evaluating dose-response relationship.
Second, Britton et al. evaluated the association between alcohol consumption and sleep disorders among older people (4). For men, OR (95% CI) of drinking more than 21 units (approximately 168 grams) of alcohol per week for waking several times a night was 1.30 (1.02, 1.66). In contrast, there was no significant increase of OR for women. The criteria of increased amount of drinking were different from those by Hu et al. (2), and stratified analysis by sex was based on the same criteria of increased alcohol consumption. In addition, comorbidities including mental disorders might be affected by aging. As many contributing variables on the association might be existed in epidemiological studies, selecting prospective studies for a meta-analysis would be difficult to conduct.
Finally, Zheng et al. assessed the association between alcohol intake and sleep quality (5). The adjusted OR (95% CI) of heavy alcohol intake for short sleep duration and snoring were 1.31 (1.09, 1.57) and 1.38 (1.22, 1.57), respectively. Among several types of alcohol beverage, hard liquor was significantly associated with poor sleep quality. Comprehensive studies including lifestyle information might contribute to the risk of alcohol consumption on the incidence of sleep disorder.
Stress management is important to reduce health problems among doctors, especially in era of COVID-19 infection. Initiation of occupational distress would accelerate each health problem, and health problems make interactions each other. To solve the health problems, effective stress-lowering interventions should be conducted.
References
1. Medisauskaite A, Kamau C. Does occupational distress raise the risk of alcohol use, binge-eating, ill health and sleep problems among medical doctors? A UK cross-sectional study. BMJ Open 2019;9(5):e027362.
2. Hu N, Ma Y, He J, et al. Alcohol consumption and incidence of sleep disorder: A systematic review and meta-analysis of cohort studies. Drug Alcohol Depend 2020;217:108259.
3. Kolla BP, Foroughi M, Saeidifard F, et al. The impact of alcohol on breathing parameters during sleep: A systematic review and meta-analysis. Sleep Med Rev 2018;42:59-67.
4. Britton A, Fat LN, Neligan A. The association between alcohol consumption and sleep disorders among older people in the general population. Sci Rep 2020;10(1):5275.
5. Zheng D, Yuan X, Ma C, et al. Alcohol consumption and sleep quality: a community-based study. Public Health Nutr 2020 Nov 13. doi: 10.1017/S1368980020004553. [Online ahead of print]
In their meta-analysis of the impact of air pollution on renal outcomes,1 the authors should include exposure to organic solvents. Almost fifty years ago Zimmerman et al. published a case–control study of patients with terminal renal failure and just as many controls without renal disease and found that almost all patients with glomerulonephritis (GN) had been exposed to toxic substances, mainly hydrocarbons, but only a few of the controls.2 Since then, at least a dozen similar studies have confirmed their findings.3 There is also much evidence that renal function improves if the exposure is discontinued.4-6 Furthermore, 29 experiments on rats, mice and guinea pigs have shown that many types of hydrocarbons are able to produce almost all types of GN with renal failure.7 Yaqoob et al. have even shown that exposure to organic solvents may be the cause of diabetic nephropathy.8
In spite of these findings, there has been little attention to this issue. One of the reasons may be a nationwide, population-based case–control study published seventeen years ago. It included almost 1000 patients with renal failure and just as many healthy control subjects. In that study, no difference was found as regards degree of renal failure between those who had been exposed to organic solvents and those who had not. The study had several biases, however. Many people are unaware about such exposure and should therefore be interviewed by an occupational hygienist, but such interviews were...
In their meta-analysis of the impact of air pollution on renal outcomes,1 the authors should include exposure to organic solvents. Almost fifty years ago Zimmerman et al. published a case–control study of patients with terminal renal failure and just as many controls without renal disease and found that almost all patients with glomerulonephritis (GN) had been exposed to toxic substances, mainly hydrocarbons, but only a few of the controls.2 Since then, at least a dozen similar studies have confirmed their findings.3 There is also much evidence that renal function improves if the exposure is discontinued.4-6 Furthermore, 29 experiments on rats, mice and guinea pigs have shown that many types of hydrocarbons are able to produce almost all types of GN with renal failure.7 Yaqoob et al. have even shown that exposure to organic solvents may be the cause of diabetic nephropathy.8
In spite of these findings, there has been little attention to this issue. One of the reasons may be a nationwide, population-based case–control study published seventeen years ago. It included almost 1000 patients with renal failure and just as many healthy control subjects. In that study, no difference was found as regards degree of renal failure between those who had been exposed to organic solvents and those who had not. The study had several biases, however. Many people are unaware about such exposure and should therefore be interviewed by an occupational hygienist, but such interviews were only performed if the patient had reported about such exposure him- or herself. Furthermore, patients who had died before the interview, patients who were too ill to be interviewed and patients who had received a kidney transplant, were excluded. This is a serious error because all other studies have shown that exposure to organic solvents is most common and most pronounced in patients with renal failure.
Therefore, the planned study by Hamroun et al. is highly important, because many urologists seem to be unaware of the role played by exposure to nephrotoxic chemicals. For instance, hundreds of reports about kidney graft failure due to various types of GN have been reported, but apparently, none of the authors have investigated whether the patients have been exposed to nephrotoxic chemicals.
References
1. Hamroun A, Camier A, Bigna JJ, et al. Impact of air pollution on renal outcomes: a systematic review and meta- analysis protocol. BMJ Open 2021;11:e041088. doi:10.1136/ bmjopen-2020-041088
2. Zimmerman SW, Groehler K, Beirne GJ. Hydrocarbon exposure and chronic glomerulonephritis. Lancet 1975;2:199–201.
3. Ravnskov U. Hydrocarbons may worsen renal function in glomerulonephritis: a meta-analysis of the case–control studies. Am J Ind Med 2000;37:599– 600.
4. Bell GM, Doig A, Thomson D, et al. End-stage renal failure associated with occupational exposure to organic solvents. Proc EDTA-ER 1985;22:725–9.
5. Yaqoob M, Stevenson A, Mason H, Bell GM. Hydrocarbon exposure and tubular damage: additional factors in the progression of renal failure in primary glomerulonephritis. QJM 1993;86:661-7.
6. Ravnskov U. Influence of hydrocarbon exposure on the course of glomerulonephritis. Nephron 1986;42:156–60.
7. Ravnskov U. Experimental glomerulonephritis induced by hydrocarbon exposure: a systematic review. BMC Nephrol 2005;6:15
8. Yaqoob M, Patrick AW, McClelland P, Stevenson A, Mason H, Percy DF, et al. Occupational hydrocarbon exposure and diabetic nephropathy. Diabet Med. 1994;11:789–93.
9. Fored CM, Nise G, Ejerblad E et al. Absence of association between organic solvent exposure and risk of chronic renal failure: a nationwide population-based case-control study. J Am Soc Nephrol 2004;15:180-6.
Incorporating two parallel approaches, meta-ethnography and thematic synthesis, this protocol aims to contribute to the methodological discussion around qualitative evidence synthesis (QES) and will examinethe healthcare needs / preferences of older people with post-stroke aphasia. This is an important topic to address due to the general exclusion of this cohort in stroke studies, however the authors should review the existing QES relating to this topic to better discern the unique contribution that this review will bring.
First, I am concerned by the omission of a number of related QES in the Introduction (e.g., (1) WRAY, F. & CLARKE, D. 2017. Longer-term needs of stroke survivors with communication difficulties living in the community: a systematic review and thematic synthesis of qualitative studies. BMJ Open, 7; (2) GALLACHER, K., MORRISON, D., JANI, B., MACDONALD, S., MAY, C. R., MONTORI, V. M., ERWIN, P. J., BATTY, G. D., ETON, D. T., LANGHORNE, P. & MAIR, F. S. 2013. Uncovering treatment burden as a key concept for stroke care: a systematic review of qualitative research. PLoS Med, 10, e1001473.) Considering broader concepts around treatment burden and self-management support is essential when examining healthcare needs.
Second, I am concerned by an apparent lack of engagement with the focus and findings of previous QES cited. For example, the authors write that Manning et al. (2019) "did not focus on healthcare needs or healthcare experi...
Incorporating two parallel approaches, meta-ethnography and thematic synthesis, this protocol aims to contribute to the methodological discussion around qualitative evidence synthesis (QES) and will examinethe healthcare needs / preferences of older people with post-stroke aphasia. This is an important topic to address due to the general exclusion of this cohort in stroke studies, however the authors should review the existing QES relating to this topic to better discern the unique contribution that this review will bring.
First, I am concerned by the omission of a number of related QES in the Introduction (e.g., (1) WRAY, F. & CLARKE, D. 2017. Longer-term needs of stroke survivors with communication difficulties living in the community: a systematic review and thematic synthesis of qualitative studies. BMJ Open, 7; (2) GALLACHER, K., MORRISON, D., JANI, B., MACDONALD, S., MAY, C. R., MONTORI, V. M., ERWIN, P. J., BATTY, G. D., ETON, D. T., LANGHORNE, P. & MAIR, F. S. 2013. Uncovering treatment burden as a key concept for stroke care: a systematic review of qualitative research. PLoS Med, 10, e1001473.) Considering broader concepts around treatment burden and self-management support is essential when examining healthcare needs.
Second, I am concerned by an apparent lack of engagement with the focus and findings of previous QES cited. For example, the authors write that Manning et al. (2019) "did not focus on healthcare needs or healthcare experiences, but were interested more generally in factors contributing to personal recovery and living successfully with aphasia". This is not a comprehensive or accurate summary of this thematic synthesis (not thematic analysis) of 31 papers reporting qualitative research with >350 people with post-stroke aphasia (PWA).
The purpose of the Manning et al (2019) included advancing conceptual understanding of how best to support PWA to 'live well'. In doing so, the QES comprehensively and systematically searched and synthesised prior qualitative literature around healthcare needs and experiences, and integrated these with issues of quality, access, equity and inclusion - i.e. with wider consideration to structural barriers to being able to access relevant support services.
The findings included analytical themes which explicitly refer to healthcare needs - e.g., the need for long-term, responsive access to a wide range of health / community support services and information, and for healthcare workers to be competent and trained in supporting communication with people with aphasia. The analysis integrates these healthcare needs within a broader conceptual understanding of living well with aphasia, that is aligned with the personal recovery model used in the mental health literature.
In summary, while the protocol is novel in contributing to methodological insights more generally, I would urge the authors to engage with prior QES on this topic to explicate the new knowledge it will generate around healthcare needs of people with aphasia.
You may wish to use the output area classification (OAC) to further investigate the role of social group on Covid-19 mortality. The OAC is based on the output area (OA) which is the smallest unit at which census data is aggregated. I have found that it gives unique insight into patterns of admission/diagnosis in Critical Care and admission to hospital via the emergency department.
In the PATCH trial protocol, Mitra and colleagues misrepresent the CRASH-2 trial.1 They say that almost all of the patients included in the CRASH-2 trial were “from low- and middle-income countries were where prehospital care was limited, blood components were uncommonly used and injury mortality was high.” The CRASH-2 trial did not describe pre-hospital care and it is inappropriately judgemental to assume that it was limited.2 It is also wrong to state that blood components were uncommonly used when more than half of the CRASH-2 trial patients were transfused.2 In defence of their questionable assertion that the effects of tranexamic acid might be different in “regions with advanced trauma care systems,” whatever advanced might mean, they claim that “subgroup analyses have not addressed this limitation.” However, in 2012, we published subgroup analysis of the effect of tranexamic acid on death due to bleeding by geographical region which found no evidence of heterogeneity.3 Indeed, we shared these data with the chief investigator of the PATCH trial (Russel Gruen) when he requested them. The subgroup of patients from “Europe, North America, and Australasia” included 1960 patients – more patients than are in the PATCH trial. They go on to suggest that because the risk of death due to bleeding may be lower in regions with “advanced trauma care systems” that the balance of risks and benefits will be different. They ignore our 2012 BMJ paper that specifically examined “whethe...
In the PATCH trial protocol, Mitra and colleagues misrepresent the CRASH-2 trial.1 They say that almost all of the patients included in the CRASH-2 trial were “from low- and middle-income countries were where prehospital care was limited, blood components were uncommonly used and injury mortality was high.” The CRASH-2 trial did not describe pre-hospital care and it is inappropriately judgemental to assume that it was limited.2 It is also wrong to state that blood components were uncommonly used when more than half of the CRASH-2 trial patients were transfused.2 In defence of their questionable assertion that the effects of tranexamic acid might be different in “regions with advanced trauma care systems,” whatever advanced might mean, they claim that “subgroup analyses have not addressed this limitation.” However, in 2012, we published subgroup analysis of the effect of tranexamic acid on death due to bleeding by geographical region which found no evidence of heterogeneity.3 Indeed, we shared these data with the chief investigator of the PATCH trial (Russel Gruen) when he requested them. The subgroup of patients from “Europe, North America, and Australasia” included 1960 patients – more patients than are in the PATCH trial. They go on to suggest that because the risk of death due to bleeding may be lower in regions with “advanced trauma care systems” that the balance of risks and benefits will be different. They ignore our 2012 BMJ paper that specifically examined “whether the effect of tranexamic acid on the risk of death and thrombotic events in patients with traumatic bleeding varies according to baseline risk of death.”4 This paper found no evidence that the balance of risks and benefits varies by baseline risk. As noted in the Australian Medical Journal, they misrepresent the data on the safety of tranexamic acid in trauma patients by citing results from small observational studies that were most probably confounded by severity of injury.5 At the same time, they overlook the CRASH-3 randomised trial results with 12,737 trauma patients that found no evidence of increased risk.6 On the timing of intervention, they point out that whilst there was strong evidence of mortality benefit with early treatment, the interpretation of the effects of TXA is complicated by an apparent increase in the risk of death due to bleeding if TXA was administered 3 hours or more after injury. If the benefits of early treatment are not in doubt, what uncertainty is being evaluated in this trial? Why should the effect of early TXA treatment depend on location?7 They claim that the mechanism of mortality benefit in the CRASH-2 trial is unclear. They ignore our paper on this issue which showed that early administration of tranexamic acid reduced mortality by preventing exsanguination on the day of the injury.8 The PATCH trial will make a modest contribution to the evidence on the safety and effectiveness of tranexamic acid in trauma patients and will need to be presented and interpreted in the light of this body of evidence. To ignore or disparage this evidence is inappropriate and unethical.
References
1. Mitra B, Bernard S, Gantner D, et al. Protocol for a multicentre prehospital randomised controlled trial investigating tranexamic acid in severe trauma: the PATCH-Trauma trial. BMJ Open 2021;11:e046522. doi:10.1136/bmjopen-2020-046522
2. The CRASH-2 trial collaborators. Effects of tranexamic acid on death, vascular occlusive events, and blood transfusion in trauma patients with significant haemorrhage (CRASH-2): a randomised, placebo-controlled trial. The Lancet. 2010;376:23-32.
3. Ker K, Kiriya J, Perel P, Edwards P, Shakur H, Roberts I. Avoidable mortality from giving tranexamic acid to bleeding trauma patients: an estimation based on WHO mortality data, a systematic literature review and data from the CRASH-2 trial. BMC Emerg Med. 2012;12:3. Epub 2012/03/03.
4. Roberts I, Perel P, Prieto-Merino D, Shakur H, Coats T, Hunt BJ, Lecky F, Brohi K, Willett K; CRASH-2 Collaborators. Effect of tranexamic acid on mortality in patients with traumatic bleeding: prespecified analysis of data from randomised controlled trial. BMJ 2012;345:e5839. doi: 10.1136/bmj.e5839.
5. Jarman J, Brier A. Tranexamic acid and trauma. MJA 2014; 200: 254.
6. The CRASH-3 trial collaborators. Effects of tranexamic acid on death, disability, vascular occlusive events and other morbidities in patients with acute traumatic brain injury (CRASH-3): a randomised, placebo-controlled trial. Lancet 2019;394:1713-1723.
7. Roberts I, Prieto D. Applying results from clinical trials: tranexamic acid in trauma patients. Journal of Intensive Care 2014, 2:56
8. Roberts I, Prieto-Merino D, Manno D. Mechanism of action of tranexamic acid in bleeding trauma patients: an exploratory analysis of data from the CRASH-2 trial. Critical Care 2014, 18:685 http://ccforum.com/content/18/6/685
We would like to thank Professor Adami for his comments regarding the possible differing pathogenic processes driving T2DM at low versus higher BMIs and the importance of accounting for this when assessing the predictive capacity of a co-variate such as diabetes duration. We certainly agree that T2DM is a heterogenous disease [1]. However, Taylor and Holman describe a convincing body of evidence that questions whether those who are non-obese have a greater defect in β cell function and insulin deficiency compared to those with higher BMI [2], suggesting that the relationship of BMI to β cell reserve may not be simple.
We agree that it would indeed be interesting to understand if there is an interaction between T2DM duration and BMI. To investigate the hypothesis, therefore, would require a study that recruited people with diabetes and a wide range of BMI (e.g. ≥25 kg/m2). In the UK, commissioning of bariatric surgery is restricted to people with a BMI ≥35 kg/m2 in most cases, and always ≥30 kg/m2. Hence, unfortunately, our study will not test Professor Adami’s most interesting hypothesis.
1. Ahlqvist, E., et al., Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. The Lancet Diabetes & Endocrinology, 2018. 6(5): p. 361-369.
2. Taylor, R. and Rury R. Holman, Normal weight individuals who develop Type 2 diabetes: the personal fat threshold. Clinical Science, 2014. 128(7): p. 40...
We would like to thank Professor Adami for his comments regarding the possible differing pathogenic processes driving T2DM at low versus higher BMIs and the importance of accounting for this when assessing the predictive capacity of a co-variate such as diabetes duration. We certainly agree that T2DM is a heterogenous disease [1]. However, Taylor and Holman describe a convincing body of evidence that questions whether those who are non-obese have a greater defect in β cell function and insulin deficiency compared to those with higher BMI [2], suggesting that the relationship of BMI to β cell reserve may not be simple.
We agree that it would indeed be interesting to understand if there is an interaction between T2DM duration and BMI. To investigate the hypothesis, therefore, would require a study that recruited people with diabetes and a wide range of BMI (e.g. ≥25 kg/m2). In the UK, commissioning of bariatric surgery is restricted to people with a BMI ≥35 kg/m2 in most cases, and always ≥30 kg/m2. Hence, unfortunately, our study will not test Professor Adami’s most interesting hypothesis.
1. Ahlqvist, E., et al., Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. The Lancet Diabetes & Endocrinology, 2018. 6(5): p. 361-369.
2. Taylor, R. and Rury R. Holman, Normal weight individuals who develop Type 2 diabetes: the personal fat threshold. Clinical Science, 2014. 128(7): p. 405-410.
As in many other studies of urinary tract infection, Holm et al. found that many women with dysuria do not have bacteriuria.1 The reason is most likely the use of soap. In a study of 50 women with frequent uncomplicated urinary tract infections, dysuria without bacteriuria, or asymptomatic bacteriuria, 27 of 31 among those with dysuria washed their sexual organs with soap every day, but only one among 19 with asymptomatic bacteriuria. Furthermore, dysuria disappeared in almost all of those who stopped using soap.2 Obviously, women with dysuria should be warned against using soap because dysuria occurring after previous treatments of cystitis may be interpreted as a sign of recurrence of the infection and result in unnecessary treatment.
References
1. Holm A, Siersma V, Cordoba GC. Diagnosis of urinary tract infection based on symptoms: how are likelihood ratios affected by age? a diagnostic accuracy study. BMJ Open 2021;11:e039871. doi:10.1136/ bmjopen-2020-039871
2. Ravnskov U. Soap is the major cause of dysuria. Lancet 1984;1(8384):1027-8. doi: 10.1016/s0140-6736(84)92381-x.
The original primary outcome
The gameChange trial primary outcome was avoidance and distress in real-life situations measured using a behavioural assessment task (Oxford-Behavioural Assessment Task, O-BAT). The O-BAT is administered with a trial research assistant and the patient is asked to go into a (personalised) hierarchy of five real world situations that they find anxiety-provoking (e.g. go into a local café or shop). The assessment records how many of the five steps the individual completed (avoidance score) and their level of anxiety (distress score).
Why the measure had to be changed
Due to the COVID-19 lockdown measures implemented in March 2020, we were not allowed to administer the O-BAT. It would involve face-to-face contact, which was prohibited by the NHS trusts. It was also the case that many locations (e.g. cafes, shops) used in the O-BAT were closed. All patient recruitment into the trial was suspended for six months but remote assessments continued for those who had already entered into the trial.
The replacement primary outcome
We had already developed a self-report version of the O-BAT, which was a secondary outcome measure. In the published protocol this is called the ‘self-report O-BAT’. We now call the measure the Oxford Agoraphobic Avoidance Scale (O-AS) (Lambe et al, submitted). We have made this self-report version of the O-BAT the primary outcome variable. As in the original O-BAT, the O-AS gives an avoidance...
Show MoreDear Ms. Manning,
thank you very much for your response and helpful comments to our study protocol.
You point out that we might have missed to report on two important reviews conducted in the field of stroke survivors' needs. This might be due to our focus on stroke-related aphasia and the accordingly constructed search algorithm. Since the focus of our work will be the comparison of the results of two synthesis methods, we aimed to rule out that QES exist that duplicate our research question. Either way, thank you for pointing us to these important reviews. We will review those studies and use them to refine and inform our research algorithm if neccessary.
We also want to apologize for not having reproduced the results of your study in an appropriate way. We will keep your critique in mind while conducting our QES using two different approaches.
Best regards,
the authors
Park et al. identified risk factors for in-hospital mortality within 56 days in patients with severe infection of COVID-19 (1). The adjusted hazard ratios (95% confidence interval [CI]) of fibrosis-4 index (FIB-4), lymphocyte count, diabetes, and systemic inflammatory response syndrome in patients with COVID-19 receiving respiratory support for mortality were 2.784 (1.691 to 4.585), 0.480 (0.271 to 0.852), 1.917 (1.181 to 3.111), and 1.714 (1.048 to 2.802), respectively. A number of risk factors were also inversely related to survival in a dose-response manner. I present information regarding FIB-4 index and mortality in patients with COVID-19.
First, Li et al. assessed the association of FIB-4 with biomarkers and clinical outcome in hospitalized patients with COVID-19 (2). Among the 202 participants, 22 died. The median values of FIB-4 in participants who survived and died were 1.91 and 3.98, respectively. The adjusted odds ratio (OR) (95% CI) of patients with each one-unit increment in FIB-4 for mortality was 1.79 (1.36 to 2.35). Although the number of events was small, FIB-4 was selected as a simple and inexpensive approach for the risk assessment in patients with COVID-19.
Second, Lopez-Mendez et al. evaluated the association of liver steatosis and fibrosis with clinical outcomes.in patients with COVID-19 (3). ORs (95% CIs) of patients with liver fibrosis by FIB-4 for ICU admission and mortality were 1.74 (1.74 to 2.68) and 6.45 (2.01 to 20.83), but signi...
Show MoreMedisauskaite and Kamau conducted a randomized controlled trial to investigate the association between occupational distress and the risk of health problems among UK doctors (1). Occupational distress and job factors increased the odds of doctors using substances, having sleep problems, presenting with frequent symptoms of ill health and binge-eating. Especially, burnout increased the risk of all types of sleep problems, including difficulty falling/staying asleep, insomnia. I suppose that association might be caused from occupational distress to the risk of health problems in an intervention study. I have a general concern on the inter-relationship among health problems, and discussed the relationship between alcohol use and sleep problem as an example.
First, Hu et al. conducted a meta-analysis to examine the relationship of alcohol consumption with incidence of sleep disorder (2). Pooled odds ratios (ORs) (95% confidence intervals [CIs]) of mild/moderate and heavy alcohol consumptions for the incidence of sleep disorder were 1.37 (1.22, 1.54) and 1.22 (0.94, 1.60). They selected sleepiness and insomnia as sleep problems, and obstructive sleep apnea was not selected in spite of the frequent sleep disorders in drinkers (3). In addition, there is a space of evaluating dose-response relationship.
Second, Britton et al. evaluated the association between alcohol consumption and sleep disorders among older people (4). For men, OR (95% CI) of drinking more than 21...
Show MoreIn their meta-analysis of the impact of air pollution on renal outcomes,1 the authors should include exposure to organic solvents. Almost fifty years ago Zimmerman et al. published a case–control study of patients with terminal renal failure and just as many controls without renal disease and found that almost all patients with glomerulonephritis (GN) had been exposed to toxic substances, mainly hydrocarbons, but only a few of the controls.2 Since then, at least a dozen similar studies have confirmed their findings.3 There is also much evidence that renal function improves if the exposure is discontinued.4-6 Furthermore, 29 experiments on rats, mice and guinea pigs have shown that many types of hydrocarbons are able to produce almost all types of GN with renal failure.7 Yaqoob et al. have even shown that exposure to organic solvents may be the cause of diabetic nephropathy.8
In spite of these findings, there has been little attention to this issue. One of the reasons may be a nationwide, population-based case–control study published seventeen years ago. It included almost 1000 patients with renal failure and just as many healthy control subjects. In that study, no difference was found as regards degree of renal failure between those who had been exposed to organic solvents and those who had not. The study had several biases, however. Many people are unaware about such exposure and should therefore be interviewed by an occupational hygienist, but such interviews were...
Show MoreIncorporating two parallel approaches, meta-ethnography and thematic synthesis, this protocol aims to contribute to the methodological discussion around qualitative evidence synthesis (QES) and will examinethe healthcare needs / preferences of older people with post-stroke aphasia. This is an important topic to address due to the general exclusion of this cohort in stroke studies, however the authors should review the existing QES relating to this topic to better discern the unique contribution that this review will bring.
First, I am concerned by the omission of a number of related QES in the Introduction (e.g., (1) WRAY, F. & CLARKE, D. 2017. Longer-term needs of stroke survivors with communication difficulties living in the community: a systematic review and thematic synthesis of qualitative studies. BMJ Open, 7; (2) GALLACHER, K., MORRISON, D., JANI, B., MACDONALD, S., MAY, C. R., MONTORI, V. M., ERWIN, P. J., BATTY, G. D., ETON, D. T., LANGHORNE, P. & MAIR, F. S. 2013. Uncovering treatment burden as a key concept for stroke care: a systematic review of qualitative research. PLoS Med, 10, e1001473.) Considering broader concepts around treatment burden and self-management support is essential when examining healthcare needs.
Second, I am concerned by an apparent lack of engagement with the focus and findings of previous QES cited. For example, the authors write that Manning et al. (2019) "did not focus on healthcare needs or healthcare experi...
Show MoreYou may wish to use the output area classification (OAC) to further investigate the role of social group on Covid-19 mortality. The OAC is based on the output area (OA) which is the smallest unit at which census data is aggregated. I have found that it gives unique insight into patterns of admission/diagnosis in Critical Care and admission to hospital via the emergency department.
In the PATCH trial protocol, Mitra and colleagues misrepresent the CRASH-2 trial.1 They say that almost all of the patients included in the CRASH-2 trial were “from low- and middle-income countries were where prehospital care was limited, blood components were uncommonly used and injury mortality was high.” The CRASH-2 trial did not describe pre-hospital care and it is inappropriately judgemental to assume that it was limited.2 It is also wrong to state that blood components were uncommonly used when more than half of the CRASH-2 trial patients were transfused.2 In defence of their questionable assertion that the effects of tranexamic acid might be different in “regions with advanced trauma care systems,” whatever advanced might mean, they claim that “subgroup analyses have not addressed this limitation.” However, in 2012, we published subgroup analysis of the effect of tranexamic acid on death due to bleeding by geographical region which found no evidence of heterogeneity.3 Indeed, we shared these data with the chief investigator of the PATCH trial (Russel Gruen) when he requested them. The subgroup of patients from “Europe, North America, and Australasia” included 1960 patients – more patients than are in the PATCH trial. They go on to suggest that because the risk of death due to bleeding may be lower in regions with “advanced trauma care systems” that the balance of risks and benefits will be different. They ignore our 2012 BMJ paper that specifically examined “whethe...
Show MoreWe would like to thank Professor Adami for his comments regarding the possible differing pathogenic processes driving T2DM at low versus higher BMIs and the importance of accounting for this when assessing the predictive capacity of a co-variate such as diabetes duration. We certainly agree that T2DM is a heterogenous disease [1]. However, Taylor and Holman describe a convincing body of evidence that questions whether those who are non-obese have a greater defect in β cell function and insulin deficiency compared to those with higher BMI [2], suggesting that the relationship of BMI to β cell reserve may not be simple.
We agree that it would indeed be interesting to understand if there is an interaction between T2DM duration and BMI. To investigate the hypothesis, therefore, would require a study that recruited people with diabetes and a wide range of BMI (e.g. ≥25 kg/m2). In the UK, commissioning of bariatric surgery is restricted to people with a BMI ≥35 kg/m2 in most cases, and always ≥30 kg/m2. Hence, unfortunately, our study will not test Professor Adami’s most interesting hypothesis.
1. Ahlqvist, E., et al., Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. The Lancet Diabetes & Endocrinology, 2018. 6(5): p. 361-369.
Show More2. Taylor, R. and Rury R. Holman, Normal weight individuals who develop Type 2 diabetes: the personal fat threshold. Clinical Science, 2014. 128(7): p. 40...
As in many other studies of urinary tract infection, Holm et al. found that many women with dysuria do not have bacteriuria.1 The reason is most likely the use of soap. In a study of 50 women with frequent uncomplicated urinary tract infections, dysuria without bacteriuria, or asymptomatic bacteriuria, 27 of 31 among those with dysuria washed their sexual organs with soap every day, but only one among 19 with asymptomatic bacteriuria. Furthermore, dysuria disappeared in almost all of those who stopped using soap.2 Obviously, women with dysuria should be warned against using soap because dysuria occurring after previous treatments of cystitis may be interpreted as a sign of recurrence of the infection and result in unnecessary treatment.
References
1. Holm A, Siersma V, Cordoba GC. Diagnosis of urinary tract infection based on symptoms: how are likelihood ratios affected by age? a diagnostic accuracy study. BMJ Open 2021;11:e039871. doi:10.1136/ bmjopen-2020-039871
2. Ravnskov U. Soap is the major cause of dysuria. Lancet 1984;1(8384):1027-8. doi: 10.1016/s0140-6736(84)92381-x.
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