Systematic review and metaanalysis comparing the bias and accuracy of the modification of diet in renal disease and chronic kidney disease epidemiology collaboration equations in community-based population

BACKGROUND The majority of patients with chronic kidney disease are diagnosed and monitored in primary care. Glomerular filtration rate (GFR) is a key marker of renal function, but direct measurement is invasive; in routine practice, equations are used for estimated GFR (eGFR) from serum creatinine. We systematically assessed bias and accuracy of commonly used eGFR equations in populations relevant to primary care. CONTENT MEDLINE, EMBASE, and the Cochrane Library were searched for studies comparing measured GFR (mGFR) with eGFR in adult populations comparable to primary care and reporting both the Modification of Diet in Renal Disease (MDRD) and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations based on standardized creatinine measurements. We pooled data on mean bias (difference between eGFR and mGFR) and on mean accuracy (proportion of eGFR within 30% of mGFR) using a random-effects inverse-variance weighted metaanalysis. We included 48 studies of 26875 patients that reported data on bias and/or accuracy. Metaanalysis of within-study comparisons in which both formulae were tested on the same patient cohorts using isotope dilution-mass spectrometry-traceable creatinine showed a lower mean bias in eGFR using CKD-EPI of 2.2 mL/min/1.73 m2 (95% CI, 1.1–3.2; 30 studies; I2 = 74.4%) and a higher mean accuracy of CKD-EPI of 2.7% (1.6–3.8; 47 studies; I2 = 55.5%). Metaregression showed that in both equations bias and accuracy favored the CKD-EPI equation at higher mGFR values. SUMMARY Both equations underestimated mGFR, but CKD-EPI gave more accurate estimates of GFR

Restricted access to the NHS during the COVID-19 pandemic : is it time to move away from the rationed clinical response?

Recently a Lancet Commission examined the future prospects of the NHS in the wake of COVID-19. The report cites poor healthcare capacity and chronic staff shortages as key contributing factors to the UK’s inadequate pandemic response. Notable strengths included universal access, the goodwill of staff, and the ability to generate innovative solutions - qualities that are likely to have averted an even deeper national crisis [1]. The prosperity of the NHS is intrinsically connected to the prosperity of the nation. Access to healthcare influences morbidity, mortality, economic activity, and whether or not social restrictions are necessary [2,3]. Public health measures such as timely implementation of social distancing are also important to limit mortality, but going forward it is the capacity to respond in a clinically effective and decisive manner that is vital to diminish the threat associated with the virus [4]. The importance of examining the national clinical response to SARS-CoV-2 cannot be overstated. Arguably the greatest mistake of this pandemic would be failing to prepare for the next. There are also the looming unknowns of SARS-CoV-2 variants [5], the higher rates of Long COVID following more severe disease [6], and the increased healthcare demands associated with delayed presentation of COVID-19 pneumonia [7-11]. Improving the tolerance of society to background levels of SARS-CoV-2 will require an improved clinical response. With this in mind, we examine one aspect of the UK’s clinical response that remains in place today: restricted access to healthcare

Measuring the Quality of Observational Study Data in an International HIV Research Network

Observational studies of health conditions and outcomes often combine clinical care data from many sites without explicitly assessing the accuracy and completeness of these data. In order to improve the quality of data in an international multi-site observational cohort of HIV-infected patients, the authors conducted on-site, Good Clinical Practice-based audits of the clinical care datasets submitted by participating HIV clinics. Discrepancies between data submitted for research and data in the clinical records were categorized using the audit codes published by the European Organization for the Research and Treatment of Cancer. Five of seven sites had error rates >10% in key study variables, notably laboratory data, weight measurements, and antiretroviral medications. All sites had significant discrepancies in medication start and stop dates. Clinical care data, particularly antiretroviral regimens and associated dates, are prone to substantial error. Verifying data against source documents through audits will improve the quality of databases and research and can be a technique for retraining staff responsible for clinical data collection. The authors recommend that all participants in observational cohorts use data audits to assess and improve the quality of data and to guide future data collection and abstraction efforts at the point of care

Statistical Analysis of Choice Experiments and Surveys

Measures of households' past behavior, their expectations with respect to future events and contingencies, and their intentions with respect to future behavior are frequently collected using household surveys. These questions are conceptually difficult. Answering them requires elaborate cognitive and social processes, and often respondents report only their “best” guesses and/or estimates, using more or less sophisticated heuristics. A large body of literature in psychology and survey research shows that as a result, responses to such questions may be severely biased. In this paper, (1) we describe some of the problems that are typically encountered, (2) provide some empirical illustrations of these biases, and (3) develop a framework for conceptualizing survey response behavior and for integrating structural models of response behavior into the statistical analysis of the underlying economic behavior.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47001/1/11002_2005_Article_5884.pd