A nationwide survey to measure practice variation of catheterisation management in patients undergoing vaginal prolapse surgery

Urinary catheterisation following vaginal prolapse surgery causes inconvenience for patients, risk of urinary tract infections and potentially longer hospitalisation. Possibly, practice variation exists concerning diagnosis and management of abnormal postvoid residual (PVR) volume implying suboptimal treatment for certain subgroups. Nationwide questionnaire-based survey. Post-operatively, 77% performed transurethral indwelling catheterisation, 12% suprapubic catheterisation and 11% intermittent catheterisation. Catheterisation was applied 3 days (1-7 days) following anterior repair and 1 day (1-3 days) following all other procedures. The median cut-off point for abnormal PVR was 150 mL (range 50-250 mL). Treatment of abnormal PVR consisted mostly of prolonging transurethral indwelling catheterisation for 2 days (range 1-5 days; 57%), 29% by intermittent and 12% by suprapubic catheterisation. Antibiotics were administered by 21% either routinely or based on symptoms only. Due to insufficient evidence and suboptimal implementation of available evidence, practice variation in catheterisation regimens is hig

Performance of Polymerase Chain Reaction Techniques Detecting Perforin in the Diagnosis of Acute Renal Rejection: A Meta-Analysis

BACKGROUND: Studies in the past have shown that perforin expression is up-regulated during acute renal rejection, which provided hopes for a non-invasive and reliable diagnostic method to identify acute rejection. However, a systematic assessment of the value of perforin as a diagnostic marker of acute renal rejection has not been performed. We conducted this meta-analysis to document the diagnostic performance of perforin mRNA detection and to identify potential variables that may affect the performance. METHODOLOGY/PRINCIPAL FINDINGS: Relevant materials that reported the diagnostic performance of perforin mRNA detection in acute renal rejection patients were extracted from electronic databases. After careful evaluation of the studies included in this analysis, the numbers of true positive, true negative, false positive and false negative cases of acute renal rejection identified by perforin mRNA detection were gathered from each data set. The publication year, sample origin, mRNA quantification method and housekeeping gene were also extracted as potential confounding variables. Fourteen studies with a total of 501 renal transplant subjects were included in this meta-analysis. The overall performance of perforin mRNA detection was: pooled sensitivity, 0.83 (95% confidence interval: 0.78 to 0.88); pooled specificity, 0.86 (95% confidence interval: 0.82 to 0.90); diagnostic odds ratio, 28.79 (95% confidence interval: 16.26 to 50.97); and area under the summary receiver operating characteristic curves value, 0.9107±0.0174. The univariate analysis of potential variables showed some changes in the diagnostic performance, but none of the differences reached statistical significance. CONCLUSIONS/SIGNIFICANCE: Despite inter-study variability, the test performance of perforin mRNA detected by polymerase chain reaction was consistent under circumstances of methodological changes and demonstrated both sensitivity and specificity in detecting acute renal rejection. These results suggest a great diagnostic potential for perforin mRNA detection as a reliable marker of acute rejection in renal allograft recipients

Accuracy of clinical pallor in the diagnosis of anaemia in children: a meta-analysis

BACKGROUND: Anaemia is highly prevalent in children of developing countries. It is associated with impaired physical growth and mental development. Palmar pallor is recommended at primary level for diagnosing it, on the basis of few studies. The objective of the study was to systematically assess the accuracy of clinical signs in the diagnosis of anaemia in children. METHODS: A systematic review on the accuracy of clinical signs of anaemia in children. We performed an Internet search in various databases and an additional reference tracking. Studies had to be on performance of clinical signs in the diagnosis of anaemia, using haemoglobin as the gold standard. We calculated pooled diagnostic likelihood ratios (LR's) and odds ratios (DOR's) for each clinical sign at different haemoglobin thresholds. RESULTS: Eleven articles met the inclusion criteria. Most studies were performed in Africa, in children underfive. Chi-square test for proportions and Cochran Q for DOR's and for LR's showed heterogeneity. Type of observer and haemoglobin technique influenced the results. Pooling was done using the random effects model. Pooled DOR at haemoglobin <11 g/dL was 4.3 (95% CI 2.6–7.2) for palmar pallor, 3.7 (2.3–5.9) for conjunctival pallor, and 3.4 (1.8–6.3) for nailbed pallor. DOR's and LR's were slightly better for nailbed pallor at all other haemoglobin thresholds. The accuracy did not vary substantially after excluding outliers. CONCLUSION: This meta-analysis did not document a highly accurate clinical sign of anaemia. In view of poor performance of clinical signs, universal iron supplementation may be an adequate control strategy in high prevalence areas. Further well-designed studies are needed in settings other than Africa. They should assess inter-observer variation, performance of combined clinical signs, phenotypic differences, and different degrees of anaemia

Meta-analysis of the diagnostic performance of stress perfusion cardiovascular magnetic resonance for detection of coronary artery disease

<p>Abstract</p> <p>Aim</p> <p>Evaluation of the diagnostic accuracy of stress perfusion cardiovascular magnetic resonance for the diagnosis of significant obstructive coronary artery disease (CAD) through meta-analysis of the available data.</p> <p>Methodology</p> <p>Original articles in any language published before July 2009 were selected from available databases (MEDLINE, Cochrane Library and BioMedCentral) using the combined search terms of magnetic resonance, perfusion, and coronary angiography; with the exploded term coronary artery disease. Statistical analysis was only performed on studies that: (1) used a [greater than or equal to] 1.5 Tesla MR scanner; (2) employed invasive coronary angiography as the reference standard for diagnosing significant obstructive CAD, defined as a [greater than or equal to] 50% diameter stenosis; and (3) provided sufficient data to permit analysis.</p> <p>Results</p> <p>From the 263 citations identified, 55 relevant original articles were selected. Only 35 fulfilled all of the inclusion criteria, and of these 26 presented data on patient-based analysis. The overall patient-based analysis demonstrated a sensitivity of 89% (95% CI: 88-91%), and a specificity of 80% (95% CI: 78-83%). Adenosine stress perfusion CMR had better sensitivity than with dipyridamole (90% (88-92%) versus 86% (80-90%), P = 0.022), and a tendency to a better specificity (81% (78-84%) versus 77% (71-82%), P = 0.065).</p> <p>Conclusion</p> <p>Stress perfusion CMR is highly sensitive for detection of CAD but its specificity remains moderate.</p

Detecting neuroimaging biomarkers for schizophrenia:a meta-analysis of multivariate pattern recognition studies

Multivariate pattern recognition approaches have recently facilitated the search for reliable neuroimaging-based biomarkers in psychiatric disorders such as schizophrenia. By taking into account the multivariate nature of brain functional and structural changes as well as their distributed localization across the whole brain, they overcome drawbacks of traditional univariate approaches. To evaluate the overall reliability of neuroimaging-based biomarkers, we conducted a comprehensive literature search to identify all studies that used multivariate pattern recognition to identify patterns of brain alterations that differentiate patients with schizophrenia from healthy controls. A bivariate random-effects meta-analytic model was implemented to investigate the sensitivity and specificity across studies as well as to assess the robustness to potentially confounding variables. In the total sample of n=38 studies (1602 patients and 1637 healthy controls), patients were differentiated from controls with a sensitivity of 80.3% (95% CI: 76.7–83.5%) and a specificity of 80.3% (95% CI: 76.9–83.3%). Analysis of neuroimaging modality indicated higher sensitivity (84.46%, 95% CI: 79.9–88.2%) and similar specificity (76.9%, 95% CI: 71.3–81.6%) of rsfMRI studies as compared with structural MRI studies (sensitivity: 76.4%, 95% CI: 71.9–80.4%, specificity of 79.0%, 95% CI: 74.6–82.8%). Moderator analysis identified significant effects of age (p=0.029), imaging modality (p=0.019), and disease stage (p=0.025) on sensitivity as well as of positive-to-negative symptom ratio (p=0.022) and antipsychotic medication (p=0.016) on specificity. Our results underline the utility of multivariate pattern recognition approaches for the identification of reliable neuroimaging-based biomarkers. Despite the clinical heterogeneity of the schizophrenia phenotype, brain functional and structural alterations differentiate schizophrenic patients from healthy controls with 80% sensitivity and specificity

Development and validation of filters for the retrieval of studies of clinical examination from medline

Background: Efficiently finding clinical examination studies-studies that quantify the value of symptoms and signs in the diagnosis of disease-is becoming increasingly difficult. Filters developed to retrieve studies of diagnosis from Medline lack specificity because they also retrieve large numbers of studies on the diagnostic value of imaging and laboratory tests. Objective: The objective was to develop filters for retrieving clinical examination studies from Medline. Methods: We developed filters in a training dataset and validated them in a testing database. We created the training database by hand searching 161 journals (n = 52,636 studies). We evaluated the recall and precision of 65 candidate single-term filters in identifying studies that reported the sensitivity and specificity of symptoms or signs in the training database. To identify best combinations of these search terms, we used recursive partitioning. The best-performing filters in the training database as well as 13 previously developed filters were evaluated in a testing database (n = 431,120 studies). We also examined the impact of examining reference lists of included articles on recall. Results: In the training database, the single-term filters with the highest recall (95%) and the highest precision (8.4%) were diagnosis[subheading] and "medical history taking"[MeSH], respectively. The multiple-term filter developed using recursive partitioning (the RP filter) had a recall of 100% and a precision of 89% in the training database. In the testing database, the Haynes-2004-Sensitive filter (recall 98%, precision 0.13%) and the RP filter (recall 89%, precision 0.52%) showed the best performance. The recall of these two filters increased to 99% and 94% respectively with review of the reference lists of the included articles. Conclusions: Recursive partitioning appears to be a useful method of developing search filters. The empirical search filters proposed here can assist in the retrieval of clinical examination studies from Medline; however, because of the low precision of the search strategies, retrieving relevant studies remains challenging. Improving precision may require systematic changes in the tagging of articles by the National Library of Medicine. © Nader Shaikh, Robert G. Badgett, Mina Pi, Nancy L. Wilczynski, K. Ann McKibbon, Andrea M. Ketchum, R. Brian Haynes