22 research outputs found
Imaging tests for the detection of osteomyelitis : a systematic review
BACKGROUND: Osteomyelitis is an infection of the bone. Medical imaging tests, such as radiography, ultrasound, magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT) and positron emission tomography (PET), are often used to diagnose osteomyelitis. OBJECTIVES: To systematically review the evidence on the diagnostic accuracy, inter-rater reliability and implementation of imaging tests to diagnose osteomyelitis. DATA SOURCES: We conducted a systematic review of imaging tests to diagnose osteomyelitis. We searched MEDLINE and other databases from inception to July 2018. REVIEW METHODS: Risk of bias was assessed with QUADAS-2 [quality assessment of diagnostic accuracy studies (version 2)]. Diagnostic accuracy was assessed using bivariate regression models. Imaging tests were compared. Subgroup analyses were performed based on the location and nature of the suspected osteomyelitis. Studies of children, inter-rater reliability and implementation outcomes were synthesised narratively. RESULTS: Eighty-one studies were included (diagnostic accuracy: 77 studies; inter-rater reliability: 11 studies; implementation: one study; some studies were included in two reviews). One-quarter of diagnostic accuracy studies were rated as being at a high risk of bias. In adults, MRI had high diagnostic accuracy [95.6% sensitivity, 95% confidence interval (CI) 92.4% to 97.5%; 80.7% specificity, 95% CI 70.8% to 87.8%]. PET also had high accuracy (85.1% sensitivity, 95% CI 71.5% to 92.9%; 92.8% specificity, 95% CI 83.0% to 97.1%), as did SPECT (95.1% sensitivity, 95% CI 87.8% to 98.1%; 82.0% specificity, 95% CI 61.5% to 92.8%). There was similar diagnostic performance with MRI, PET and SPECT. Scintigraphy (83.6% sensitivity, 95% CI 71.8% to 91.1%; 70.6% specificity, 57.7% to 80.8%), computed tomography (69.7% sensitivity, 95% CI 40.1% to 88.7%; 90.2% specificity, 95% CI 57.6% to 98.4%) and radiography (70.4% sensitivity, 95% CI 61.6% to 77.8%; 81.5% specificity, 95% CI 69.6% to 89.5%) all had generally inferior diagnostic accuracy. Technetium-99m hexamethylpropyleneamine oxime white blood cell scintigraphy (87.3% sensitivity, 95% CI 75.1% to 94.0%; 94.7% specificity, 95% CI 84.9% to 98.3%) had higher diagnostic accuracy, similar to that of PET or MRI. There was no evidence that diagnostic accuracy varied by scan location or cause of osteomyelitis, although data on many scan locations were limited. Diagnostic accuracy in diabetic foot patients was similar to the overall results. Only three studies in children were identified; results were too limited to draw any conclusions. Eleven studies evaluated inter-rater reliability. MRI had acceptable inter-rater reliability. We found only one study on test implementation and no evidence on patient preferences or cost-effectiveness of imaging tests for osteomyelitis. LIMITATIONS: Most studies included < 50 participants and were poorly reported. There was limited evidence for children, ultrasonography and on clinical factors other than diagnostic accuracy. CONCLUSIONS: Osteomyelitis is reliably diagnosed by MRI, PET and SPECT. No clear reason to prefer one test over the other in terms of diagnostic accuracy was identified. The wider availability of MRI machines, and the fact that MRI does not expose patients to harmful ionising radiation, may mean that MRI is preferable in most cases. Diagnostic accuracy does not appear to vary with the potential cause of osteomyelitis or with the body part scanned. Considerable uncertainty remains over the diagnostic accuracy of imaging tests in children. Studies of diagnostic accuracy in children, particularly using MRI and ultrasound, are needed. STUDY REGISTRATION: This study is registered as PROSPERO CRD42017068511. FUNDING: This project was funded by the National Institute for Health Research Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 23, No. 61. See the NIHR Journals Library website for further project information
Introduction of a novel magnetic resonance imaging-based scoring system for assessing disease activity in children with juvenile dermatomyositis
Objectives: We aimed to develop and assess the reliability of a novel MRI-based scoring system for reporting the severity of MRI findings in children with suspected JDM. Methods: Nine consultant paediatric radiologists independently assessed and scored 40 axial and 30 coronal thigh MR images of children with suspected JDM on two occasions using the juvenile dermatomyositis magnetic resonance Imaging Score (JIS). JIS was calculated for both reads for each plane and each limb, with possible scores ranging from 0 (normal) to 100 (severe). Inter- and intraobserver agreement was calculated using the intraclass correlation coefficient (ICC) and two- and one-way random effects models, respectively. Bland-Altman plots of the difference in JIS against the average JIS were also produced for each rater. Results: Overall, the interobserver reliability and agreement was good-for axial images, JIS ranged from 46.8 to 61.0 [ICC = 0.88 (95% CI: 0.82, 0.92)] for the left limb and 47.9-61.4 [ICC = 0.87 (95% CI: 0.81, 0.92)] for the right limb. For coronal images, JIS ranged from 56.7 to 65.1 [ICC = 0.90 (95% CI: 0.85, 0.95)] for the left limb and 55.7 to 66.8 [ICC = 0.90 (95% CI: 0.84, 0.94)] for the right limb. The intraobserver reliability and agreement was good, with ICC ranging from 0.90 to 0.94. Conclusion: JIS is a semi-objective scoring system with potential to serve as a reliable biomarker of disease severity and response to therapeutic interventions in children with JDM
Bowing fracture of the inferior angle of the scapula, a difficult diagnosis
A 4-year-old boy presented with swelling over the inferior tip of the scapula and an unclear history. Initial radiographic findings were concerning for an aggressive lesion. This case highlights how a multimodality imaging approach was used to relieve uncertainty by diagnosing a paediatric bowing type fracture of the scapular tip
Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.
Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction
Imaging for detection of osteomyelitis in people with diabetic foot ulcers : A systematic review and meta-analysis
BACKGROUND: Osteomyelitis is an infection of the bone which can occur in people with diabetic foot ulcers. It can be diagnosed using X-rays, ultrasound, scintigraphy, magnetic resonance imaging (MRI), single photon emission computed tomography (SPECT) and positron emission tomography (PET). OBJECTIVES: To review the evidence on the diagnostic accuracy of imaging tests to diagnose osteomyelitis in people with diabetic foot ulcers. METHODS: We conducted a systematic review and meta-analysis. MEDLINE, EMBASE and other databases were searched to July 2018. Risk of bias was evaluated. Diagnostic accuracy was estimated using bivariate meta-analyses. RESULTS: Thirty-six studies were included in the meta-analysis. Eight studies were at high risk of bias MRI had high diagnostic accuracy (22 studies: 96.4 % sensitivity (95 % CI 90.7-98.7); 83.8 % specificity (76.0-89.5)). PET scans also had high accuracy (6 studies: 84.3 % sensitivity (52.8-96.3); 92.8 % specificity (75.7-98.2)), and possibly also SPECT, but with few studies (3 studies: 95.6 % sensitivity (76.0-99.3); 55.1 % specificity (19.3-86.3)). Scintigraphy (17 studies: 84.2 % sensitivity (76.8-89.6); 67.7 % specificity (56.2-77.4)), and X-rays (16 studies: 61.9 % sensitivity (50.5-72.1); 78.3 % specificity (62.9-88.5)) had generally inferior diagnostic accuracy. CONCLUSIONS: MRI and PET both reliably diagnose osteomyelitis in diabetic foot ulcer patients. SPECT may also have good diagnostic accuracy, although evidence is limited. This review confirms most current guidelines, showing that MRI may be the preferable test in most cases, given its wider availability and the lack of potentially harmful ionising radiation
Allele-specific targeting of mutant ataxin-3 by antisense oligonucleotides in SCA3-iPSC-derived neurons
Spinocerebellar ataxia type 3 (SCA3) is caused by an expanded polyglutamine stretch in ataxin-3. While wild-type ataxin-3 has important functions, e.g., as a deubiquitinase, downregulation of mutant ataxin-3 is likely to slow down the course of this fatal disease. We established a screening platform with human neurons of patients and controls derived from induced pluripotent stem cells to test antisense oligonucleotides (ASOs) for their effects on ataxin-3 expression. We identified an ASO that suppressed mutant and wild-type ataxin-3 levels by >90% after a singular treatment. Next, we screened pairs of ASOs designed to selectively target the mutant or the wild-type allele by taking advantage of a SNP (c.987G > C) in ATXN3 that is present in most SCA3 patients. We found ASOmut4 to reduce levels of mutant ataxin-3 by 80% after 10 days while leaving expression of wild-type ataxin-3 largely unaffected. In a long-term study we proved this effect to last for about 4 weeks after a single treatment without signs of neurotoxicity. This study provides proof of principle that allele-specific lowering of poly(Q)-expanded ataxin-3 by selective ASOs is feasible and long lasting, with sparing of wild-type ataxin-3 expression in a human cell culture model that is genetically identical to SCA3 patients
Predictive accuracy of the Post-Stroke Depression Prediction Scale : A prospective binational observational study✰
BACKGROUND: Depression after a stroke is a common complication that negatively influences stroke rehabilitation. Early identification, followed by adequate treatment of depression, improves recovery from stroke. To support early identification, the Post-stroke Depression Prediction Scale (DePreS) was developed to predict in the first week after stroke, the risk of depression in the second month. In this study we investigate the predictive accuracy of the DePreS in stroke patients. METHODS: In this prospective multicenter observational study, hospitalized stroke patients were included from three stroke units in the Netherlands and Germany using consecutive sampling. In the first week after stroke, the predicted risk for depression was estimated with the DePreS. Two months after stroke, major depressive disorder was determined with the Composite International Diagnostic Interview. RESULTS: Of the 93 included patients, 17 (18.3%) showed symptoms of major depressive disorder. With a cut-off value of ≥ 0, DePreS performed optimally with a sensitivity of 0.65 (95% CI 0.42-0.87), specificity of 0.74 (95% CI 0.64-0.84), positive predictive value of 0.35 (95% CI 0.19-0.52), and negative predictive value of 0.90 (95% CI 0.80-1.00). The AUC was 0.71 (95% CI 0.56-0.86). LIMITATIONS: The generalizability of the study findings is limited to patients able to communicate adequately. CONCLUSIONS: This study demonstrates that the DePreS is an adequate instrument for early and reliable identification of stroke patients who are not at risk of MDD in the second months after stroke. This limits the need for structural diagnostic follow-up to patients with a high risk
Predictive accuracy of the Post-Stroke Depression Prediction Scale : A prospective binational observational study✰
BACKGROUND: Depression after a stroke is a common complication that negatively influences stroke rehabilitation. Early identification, followed by adequate treatment of depression, improves recovery from stroke. To support early identification, the Post-stroke Depression Prediction Scale (DePreS) was developed to predict in the first week after stroke, the risk of depression in the second month. In this study we investigate the predictive accuracy of the DePreS in stroke patients. METHODS: In this prospective multicenter observational study, hospitalized stroke patients were included from three stroke units in the Netherlands and Germany using consecutive sampling. In the first week after stroke, the predicted risk for depression was estimated with the DePreS. Two months after stroke, major depressive disorder was determined with the Composite International Diagnostic Interview. RESULTS: Of the 93 included patients, 17 (18.3%) showed symptoms of major depressive disorder. With a cut-off value of ≥ 0, DePreS performed optimally with a sensitivity of 0.65 (95% CI 0.42-0.87), specificity of 0.74 (95% CI 0.64-0.84), positive predictive value of 0.35 (95% CI 0.19-0.52), and negative predictive value of 0.90 (95% CI 0.80-1.00). The AUC was 0.71 (95% CI 0.56-0.86). LIMITATIONS: The generalizability of the study findings is limited to patients able to communicate adequately. CONCLUSIONS: This study demonstrates that the DePreS is an adequate instrument for early and reliable identification of stroke patients who are not at risk of MDD in the second months after stroke. This limits the need for structural diagnostic follow-up to patients with a high risk