Assessment of the comparative agreement between chest radiographs and CT scans in intensive care units.

PURPOSE: Chest radiographs in critically ill patients can be difficult to interpret due to technical and clinical factors. We sought to determine the agreement of chest radiographs and CT scans, and the inter-observer variation of chest radiograph interpretation, in intensive care units (ICUs). METHODS: Chest radiographs and corresponding thoracic computerised tomography (CT) scans (as reference standard) were collected from 45 ICU patients. All radiographs were analysed by 20 doctors (radiology consultants, radiology trainees, ICU consultants, ICU trainees) from 4 different centres, blinded to CT results. Specificity/sensitivity were determined for pleural effusion, lobar collapse and consolidation/atelectasis. Separately, Fleiss' kappa for multiple raters was used to determine inter-observer variation for chest radiographs. RESULTS: The median sensitivity and specificity of chest radiographs for detecting abnormalities seen on CTs scans were 43.2% and 85.9% respectively. Diagnostic sensitivity for pleural effusion was significantly higher among radiology consultants but no specialty/experience distinctions were observed for specificity. Median inter-observer kappa coefficient among assessors was 0.295 ("fair"). CONCLUSIONS: Chest radiographs commonly miss important radiological features in critically ill patients. Inter-observer agreement in chest radiograph interpretation is only "fair". Consultant radiologists are least likely to miss thoracic radiological abnormalities. The consequences of misdiagnosis by chest radiographs remain to be determined.

SATCHMO-JS: a webserver for simultaneous protein multiple sequence alignment and phylogenetic tree construction.

We present the jump-start simultaneous alignment and tree construction using hidden Markov models (SATCHMO-JS) web server for simultaneous estimation of protein multiple sequence alignments (MSAs) and phylogenetic trees. The server takes as input a set of sequences in FASTA format, and outputs a phylogenetic tree and MSA; these can be viewed online or downloaded from the website. SATCHMO-JS is an extension of the SATCHMO algorithm, and employs a divide-and-conquer strategy to jump-start SATCHMO at a higher point in the phylogenetic tree, reducing the computational complexity of the progressive all-versus-all HMM-HMM scoring and alignment. Results on a benchmark dataset of 983 structurally aligned pairs from the PREFAB benchmark dataset show that SATCHMO-JS provides a statistically significant improvement in alignment accuracy over MUSCLE, Multiple Alignment using Fast Fourier Transform (MAFFT), ClustalW and the original SATCHMO algorithm. The SATCHMO-JS webserver is available at http://phylogenomics.berkeley.edu/satchmo-js. The datasets used in these experiments are available for download at http://phylogenomics.berkeley.edu/satchmo-js/supplementary/.

Do you understand your risk? Liability and third-party evaluations in civil litigation.

Many psychiatrists believe that there is little or no liability associated with conducting examinations at the request of a third party or with providing testimony in civil litigation. Case law has demonstrated otherwise. Psychiatrists conducting independent medical examinations (IMEs) may be vulnerable to tort lawsuits by either the evaluee or the third party who commissions the IME. In addition, breaches of legal or ethical conduct can lead to disciplinary action by state medical boards and professional organizations. Although immunity for certain types of forensic activities is available, such immunity is qualified and may not be applicable to evaluations and related testimony conducted for third parties. Understanding the liability associated with third-party evaluations will assist psychiatrists in minimizing their exposure.