Explore the vast range of titles available.

Background Delirium affects > 15% of hospitalised patients but is grossly underdetected, contributing to poor care. The 4 ‘A’s Test (4AT, www.the4AT.com ) is a short delirium assessment tool designed for routine use without special training. The primary objective was to assess the accuracy of the 4AT for delirium detection. The secondary objective was to compare the 4AT with another commonly used delirium assessment tool, the Confusion Assessment Method (CAM). Methods This was a prospective diagnostic test accuracy study set in emergency departments or acute medical wards involving acute medical patients aged ≥ 70. All those without acutely life-threatening illness or coma were eligible. Patients underwent (1) reference standard delirium assessment based on DSM-IV criteria and (2) were randomised to either the index test (4AT, scores 0–12; prespecified score of > 3 considered positive) or the comparator (CAM; scored positive or negative), in a random order, using computer-generated pseudo-random numbers, stratified by study site, with block allocation. Reference standard and 4AT or CAM assessments were performed by pairs of independent raters blinded to the results of the other assessment. Results Eight hundred forty-three individuals were randomised: 21 withdrew, 3 lost contact, 32 indeterminate diagnosis, 2 missing outcome, and 785 were included in the analysis. Mean age was 81.4 (SD 6.4) years. 12.1% (95/785) had delirium by reference standard assessment, 14.3% (56/392) by 4AT, and 4.7% (18/384) by CAM. The 4AT had an area under the receiver operating characteristic curve of 0.90 (95% CI 0.84–0.96). The 4AT had a sensitivity of 76% (95% CI 61–87%) and a specificity of 94% (95% CI 92–97%). The CAM had a sensitivity of 40% (95% CI 26–57%) and a specificity of 100% (95% CI 98–100%). Conclusions The 4AT is a short, pragmatic tool which can help improving detection rates of delirium in routine clinical care. Trial registration International standard randomised controlled trial number (ISRCTN) 53388093 . Date applied 30/05/2014; date assigned 02/06/2014.

The aim of diagnostic point-of-care testing is to minimise the time to obtain a test result, thereby allowing clinicians and patients to make a quick clinical decision. Because point-of-care tests are used in resource-limited settings, the benefits need to outweigh the costs. To optimise point-of-care testing in resource-limited settings, diagnostic tests need rigorous assessments focused on relevant clinical outcomes and operational costs, which differ from assessments of conventional diagnostic tests. We reviewed published studies on point-of-care testing in resource-limited settings, and found no clearly defined metric for the clinical usefulness of point-of-care testing. Therefore, we propose a framework for the assessment of point-of-care tests, and suggest and define the term test efficacy to describe the ability of a diagnostic test to support a clinical decision within its operational context. We also propose revised criteria for an ideal diagnostic point-of-care test in resource-limited settings. Through systematic assessments, comparisons between centralised testing and novel point-of-care technologies can be more formalised, and health officials can better establish which point-of-care technologies represent valuable additions to their clinical programmes.

Background Spillover of effect, whether positive or negative, from intervention to control group patients invalidates the Stable Unit Treatment Variable Assumption (SUTVA). SUTVA is critical to valid causal inference from randomized concurrent controlled trials (RCCT). Spillover of infection prevention is an important population level effect mediating herd immunity. This herd effect, being additional to any individual level effect, is subsumed within the overall effect size (ES) estimate derived by contrast-based techniques from RCCT’s. This herd effect would manifest only as increased dispersion among the control group infection incidence rates above background. Methods and results The objective here is to explore aspects of spillover and how this might be visualized and diagnosed. I use, for illustration, data from 190 RCCT’s abstracted in 13 Cochrane reviews of various antimicrobial versus non-antimicrobial based interventions to prevent pneumonia in ICU patients. Spillover has long been postulated in this context. Arm-based techniques enable three approaches to identify increased dispersion, not available from contrast-based techniques, which enable the diagnosis of spillover within antimicrobial versus non-antimicrobial based infection prevention RCCT’s. These three approaches are benchmarking the pneumonia incidence rates versus a clinically relevant range, comparing the dispersion in pneumonia incidence among the control versus the intervention groups and thirdly, visualizing the incidence dispersion within summary receiver operator characteristic (SROC) plots. By these criteria there is harmful spillover effects to concurrent control group patients. Conclusions Arm-based versus contrast-based techniques lead to contrary inferences from the aggregated RCCT’s of antimicrobial based interventions despite similar summary ES estimates. Moreover, the inferred relationship between underlying control group risk and ES is ‘flipped’.

Financial incentives and audit/feedback are widely used in primary care to influence clinician behaviour and increase quality of care. While observational data suggest a decline in quality when these interventions are stopped, their removal has not been evaluated in a randomised controlled trial (RCT), to our knowledge. This trial aimed to determine whether chlamydia testing in general practice is sustained when financial incentives and/or audit/feedback are removed. We undertook a 2 × 2 factorial cluster RCT in 60 general practices in 4 Australian states targeting 49,525 patients aged 16-29 years for annual chlamydia testing. Clinics were recruited between July 2014 and September 2015 and were followed for up to 2 years or until 31 December 2016. Clinics were eligible if they were in the intervention group of a previous cluster RCT where general practitioners (GPs) received financial incentives (AU$5-AU$8) for each chlamydia test and quarterly audit/feedback reports of their chlamydia testing rates. Clinics were randomised into 1 of 4 groups: incentives removed but audit/feedback retained (group A), audit/feedback removed but incentives retained (group B), both removed (group C), or both retained (group D). The primary outcome was the annual chlamydia testing rate among 16- to 29-year-old patients, where the numerator was the number who had at least 1 chlamydia test within 12 months and the denominator was the number who had at least 1 consultation during the same 12 months. We undertook a factorial analysis in which we investigated the effects of removal versus retention of incentives (groups A + C versus groups B + D) and the effects of removal versus retention of audit/feedback (group B + C versus groups A + D) separately. Of 60 clinics, 59 were randomised and 55 (91.7%) provided data (group A: 15 clinics, 11,196 patients; group B: 14, 11,944; group C: 13, 11,566; group D: 13, 14,819). Annual testing decreased from 20.2% to 11.7% (difference -8.8%; 95% CI -10.5% to -7.0%) in clinics with incentives removed and decreased from 20.6% to 14.3% (difference -7.1%; 95% CI -9.6% to -4.7%) where incentives were retained. The adjusted absolute difference in treatment effect was -0.9% (95% CI -3.5% to 1.7%; p = 0.2267). Annual testing decreased from 21.0% to 11.6% (difference -9.5%; 95% CI -11.7% to -7.4%) in clinics where audit/feedback was removed and decreased from 19.9% to 14.5% (difference -6.4%; 95% CI -8.6% to -4.2%) where audit/feedback was retained. The adjusted absolute difference in treatment effect was -2.6% (95% CI -5.4% to -0.1%; p = 0.0336). Study limitations included an unexpected reduction in testing across all groups impacting statistical power, loss of 4 clinics after randomisation, and inclusion of rural clinics only. Audit/feedback is more effective than financial incentives of AU$5-AU$8 per chlamydia test at sustaining GP chlamydia testing practices over time in Australian general practice. Australian New Zealand Clinical Trials Registry ACTRN12614000595617.

The promise of point-of-care medical diagnostics — tests that can be carried out at the site of patient care — is enormous, bringing the benefits of fast and reliable testing and allowing rapid decisions on the course of treatment to be made. To this end, much innovation is occurring in technologies for use in biodiagnostic tests. Assays based on nanomaterials, for example, are now beginning to make the transition from the laboratory to the clinic. But the potential for such assays to become part of routine medical testing depends on many scientific factors, including sensitivity, selectivity and versatility, as well as technological, financial and policy factors.

Abstract Purpose The diagnosis of adult GH deficiency (AGHD) is challenging and often requires confirmation with a GH stimulation test (GHST). The insulin tolerance test (ITT) is considered the reference standard GHST but is labor intensive, can cause severe hypoglycemia, and is contraindicated for certain patients. Macimorelin, an orally active GH secretagogue, could be used to diagnose AGHD by measuring stimulated GH levels after an oral dose. Materials and Methods The present multicenter, open-label, randomized, two-way crossover trial was designed to validate the efficacy and safety of single-dose oral macimorelin for AGHD diagnosis compared with the ITT. Subjects with high (n = 38), intermediate (n = 37), and low (n = 39) likelihood for AGHD and healthy, matched controls (n = 25) were included in the efficacy analysis. Results After the first test, 99% of macimorelin tests and 82% of ITTs were evaluable. Using GH cutoff levels of 2.8 ng/mL for macimorelin and 5.1 ng/mL for ITTs, the negative agreement was 95.38% (95% CI, 87% to 99%), the positive agreement was 74.32% (95% CI, 63% to 84%), sensitivity was 87%, and specificity was 96%. On retesting, the reproducibility was 97% for macimorelin (n = 33). In post hoc analyses, a GH cutoff of 5.1 ng/mL for both tests resulted in 94% (95% CI, 85% to 98%) negative agreement, 82% (95% CI, 72% to 90%) positive agreement, 92% sensitivity, and 96% specificity. No serious adverse events were reported for macimorelin. Conclusions Oral macimorelin is a simple, well-tolerated, reproducible, and safe diagnostic test for AGHD with accuracy comparable to that of the ITT. A GH cutoff of 5.1 ng/mL for the macimorelin test provides an excellent balance between sensitivity and specificity. The present multicenter, open-label, randomized, two-way crossover trial of macimorelin vs the ITT showed that macimorelin is a simple, well-tolerated, reproducible, and safe diagnostic test for AGHD.

Early diagnosis and prompt, effective treatment of uncomplicated malaria is critical to prevent severe disease, death and malaria transmission. We assessed the impact of rapid malaria diagnostic tests (RDTs) by community health workers (CHWs) on provision of artemisinin-based combination therapy (ACT) and health outcome in fever patients. Twenty-two CHWs from five villages in Kibaha District, a high-malaria transmission area in Coast Region, Tanzania, were trained to manage uncomplicated malaria using RDT aided diagnosis or clinical diagnosis (CD) only. Each CHW was randomly assigned to use either RDT or CD the first week and thereafter alternating weekly. Primary outcome was provision of ACT and main secondary outcomes were referral rates and health status by days 3 and 7. The CHWs enrolled 2930 fever patients during five months of whom 1988 (67.8%) presented within 24 hours of fever onset. ACT was provided to 775 of 1457 (53.2%) patients during RDT weeks and to 1422 of 1473 (96.5%) patients during CD weeks (Odds Ratio (OR) 0.039, 95% CI 0.029-0.053). The CHWs adhered to the RDT results in 1411 of 1457 (96.8%, 95% CI 95.8-97.6) patients. More patients were referred on inclusion day during RDT weeks (10.0%) compared to CD weeks (1.6%). Referral during days 1-7 and perceived non-recovery on days 3 and 7 were also more common after RDT aided diagnosis. However, no fatal or severe malaria occurred among 682 patients in the RDT group who were not treated with ACT, supporting the safety of withholding ACT to RDT negative patients. RDTs in the hands of CHWs may safely improve early and well-targeted ACT treatment in malaria patients at community level in Africa. ClinicalTrials.gov NCT00301015.

Liquid chromatography–tandem mass spectrometry (LC–MS/MS) has been increasingly used in routine clinical laboratories during the last two decades. The high specificity, sensitivity, and multi-analyte potential make it an ideal alternative to immunoassays or conventional high-performance liquid chromatography (HPLC). It also provides higher throughput than gas chromatography–mass spectrometry (GC–MS). LC–MS/MS also offers higher flexibility than immunoassays because LC–MS/MS assays are typically developed in-house. In addition, abundant information can be obtained from a single LC–MS/MS run which can produce a large amount of quantitative or qualitative data. In this review, typical LC–MS/MS clinical applications are presented, personal experiences are shared, and strengths and weakness are discussed. It is foreseeable that LC–MS/MS will become a key instrument in routine clinical laboratories.

ABSTRACT BACKGROUND The probability of a disease following a diagnostic test depends on the sensitivity and specificity of the test, but also on the prevalence of the disease in the population of interest (or pre-test probability). How physicians use this information is not well known. OBJECTIVE To assess whether physicians correctly estimate post-test probability according to various levels of prevalence and explore this skill across respondent groups. DESIGN Randomized trial. PARTICIPANTS Population-based sample of 1,361 physicians of all clinical specialties. INTERVENTION We described a scenario of a highly accurate screening test (sensitivity 99% and specificity 99%) in which we randomly manipulated the prevalence of the disease (1%, 2%, 10%, 25%, 95%, or no information). MAIN MEASURES We asked physicians to estimate the probability of disease following a positive test (categorized as <60%, 60–79%, 80–94%, 95–99.9%, and >99.9%). Each answer was correct for a different version of the scenario, and no answer was possible in the “no information” scenario. We estimated the proportion of physicians proficient in assessing post-test probability as the proportion of correct answers beyond the distribution of answers attributable to guessing. KEY RESULTS Most respondents in each of the six groups (67%–82%) selected a post-test probability of 95–99.9%, regardless of the prevalence of disease and even when no information on prevalence was provided. This answer was correct only for a prevalence of 25%. We estimated that 9.1% (95% CI 6.0–14.0) of respondents knew how to assess correctly the post-test probability. This proportion did not vary with clinical experience or practice setting. CONCLUSIONS Most physicians do not take into account the prevalence of disease when interpreting a positive test result. This may cause unnecessary testing and diagnostic errors.