Reduced Mortality Rates Following Elective Percutaneous Liver Biopsies
ABSTRACT Estimates of complication rates following elective percutaneous liver biopsy vary and might not accurately reflect current practice. We studied mortality and complication rates, by indication, in patients after they underwent liver biopsies.
We performed a study using hospital episode statistics collected by the National Health Service in England from 1998 to 2005 of elective percutaneous liver biopsies; data were linked with those from the Office for National Statistics to determine mortality rates. Using data from 61,187 people who underwent liver biopsies, all-cause mortality at 7 and 30 days after biopsy, 7-day mortality directly related to liver biopsy, and episodes of bleeding up to 7 days after biopsy were determined.
Overall all-cause mortality by 7 days after biopsy was 2 per 1000 biopsies (95% confidence interval, 1.8-2.5); this rate varied markedly by indication for biopsy, with rates as high as 12 per 1000 for patients investigated for cancer. Death within 7 days directly related to liver biopsy occurred, at most, every 1 in 10,000 biopsies in patients investigated for liver disease or abnormal liver function test results. Overall, 6 episodes of major bleeding occurred per 1000 biopsies.
All-cause mortality risk following elective percutaneous liver biopsy is approximately 0.2%, with a higher risk of major bleeding. Deaths directly related to liver biopsy occur approximately 1 in every 10,000 biopsies. This risk is substantially lower than that of previous reports, indicating that the safety of this procedure has improved.
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ABSTRACT: OBJECTIVE: To evaluate the overall accuracy of real-time tissue elastography (RTE) for the staging of liver fibrosis. METHODS: We systematically reviewed 15 studies (1,626 subjects) in which sensitivity and specificity of RTE for liver fibrosis are available. For each cut-off stage of fibrosis, i.e., F ≥ 1, F ≥ 2, F ≥ 3, and F ≥ 4, summary sensitivity and specificity were estimated using a bivariate random-effects model. Publication bias was assessed using funnel plots and Egger's test. RESULTS: Summary sensitivity and specificity were 0.79 and 0.76 for F ≥ 2, 0.82 and 0.81 for F ≥ 3, and 0.74 and 0.84 for F ≥ 4, respectively. Meta-regressions revealed scoring methods of RTE and liver diseases in the samples might not influence sensitivity and specificity of RTE. However, the estimated accuracy of RTE might be overestimated due to publication bias (p = 0.004 for F ≥ 2, p < 0.001 for F ≥ 3, and p = 0.002 for F ≥ 4). CONCLUSIONS: RTE is not highly accurate for any cut-off stage of fibrosis. Compared with findings of meta-analyses on Transient Elastography and Acoustic Radiation Force Impulse imaging, the overall accuracy of RTE seems to be nearly identical for the evaluation of significant liver fibrosis, but less accurate for the evaluation of cirrhosis.European Radiology 08/2014; DOI:10.1007/s00330-014-3364-x · 4.34 Impact Factor
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ABSTRACT: Several authors have developed and applied methods to routine data sets to identify the nature and rate of complications following interventional procedures. But, to date, there has been no systematic search for such methods. The objective of this article was to find, classify and appraise published methods, based on analysis of clinical codes, which used routine healthcare databases in a United Kingdom setting to identify complications resulting from interventional procedures. A literature search strategy was developed to identify published studies that referred, in the title or abstract, to the name or acronym of a known routine healthcare database and to complications from procedures or devices. The following data sources were searched in February and March 2013: Cochrane Methods Register, Conference Proceedings Citation Index - Science, Econlit, EMBASE, Health Management Information Consortium, Health Technology Assessment database, MathSciNet, MEDLINE, MEDLINE in-process, OAIster, OpenGrey, Science Citation Index Expanded and ScienceDirect. Of the eligible papers, those which reported methods using clinical coding were classified and summarised in tabular form using the following headings: routine healthcare database; medical speciality; method for identifying complications; length of follow-up; method of recording comorbidity. The benefits and limitations of each approach were assessed. From 3688 papers identified from the literature search, 44 reported the use of clinical codes to identify complications, from which four distinct methods were identified: 1) searching the index admission for specified clinical codes, 2) searching a sequence of admissions for specified clinical codes, 3) searching for specified clinical codes for complications from procedures and devices within the International Classification of Diseases 10th revision (ICD-10) coding scheme which is the methodology recommended by NHS Classification Service, and 4) conducting manual clinical review of diagnostic and procedure codes. The four distinct methods identifying complication from codified data offer great potential in generating new evidence on the quality and safety of new procedures using routine data. However the most robust method, using the methodology recommended by the NHS Classification Service, was the least frequently used, highlighting that much valuable observational data is being ignored.BMC Medical Research Methodology 11/2014; 14(1):126. DOI:10.1186/1471-2288-14-126 · 2.17 Impact Factor
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ABSTRACT: To assess the feasibility of texture analysis for classifying fibrosis stage and necroinflammatory activity grade in patients with chronic hepatitis C on T2-weighted (T2W), T1-weighted (T1W) and Gd-EOB-DTPA-enhanced hepatocyte-phase (EOB-HP) imaging. From April 2008 to June 2012, MR images from 123 patients with pathologically proven chronic hepatitis C were retrospectively analyzed. Texture parameters derived from histogram, gradient, run-length matrix, co-occurrence matrix, autoregressive model and wavelet transform methods were estimated with imaging software. Fisher, probability of classification error and average correlation, and mutual information coefficients were used to extract subsets of optimized texture features. Linear discriminant analysis in combination with 1-nearest neighbor classifier (LDA/1-NN) was used for lesion classification. In compliance with the software requirement, classification was performed based on datasets from all patients, the patient group with necroinflammatory activity grade 1, and that with fibrosis stage 4, respectively. Based on all patient dataset, LDA/1-NN produced misclassification rates of 28.46%, 35.77% and 20.33% for fibrosis staging and 34.15%, 25.20% and 28.46% for necroinflammatory activity grading in T2W, T1W and EOB-HP images. In the patient group with necroinflammatory activity grade 1, LDA/1-NN yielded misclassification rates of 5.00%, 0% and 12.50% for fibrosis staging in T2W, T1W and EOB-HP images respectively. In the patient group with fibrosis stage 4, LDA/1-NN yielded misclassification rates of 5.88%, 12.94% and 11.76% for necroinflammatory activity grading in T2W, T1W and EOB-HP images respectively. Texture quantitative parameters of MR images facilitate classification of the fibrosis stage as well as necroinflammatory activity grade in chronic hepatitis C, especially after categorizing the input dataset according to the activity or fibrosis degree in order to remove the interference between the fibrosis stage and necroinflammatory activity grade on texture features.PLoS ONE 03/2015; 10(3):e0118297. DOI:10.1371/journal.pone.0118297 · 3.53 Impact Factor