Use of Hy's law and a new composite algorithm to predict acute liver failure in patients with drug-induced liver injury.

BACKGROUND & AIMS Hy's Law, which states that hepatocellular drug-induced liver injury (DILI) with jaundice indicates a serious reaction, is used widely to determine risk for acute liver failure (ALF). We aimed to optimize the definition of Hy's Law and to develop a model for predicting ALF in patients with DILI. METHODS We collected data from 771 patients with DILI (805 episodes) from the Spanish DILI registry, from April 1994 through August 2012. We analyzed data collected at DILI recognition and at the time of peak levels of alanine aminotransferase (ALT) and total bilirubin (TBL). RESULTS Of the 771 patients with DILI, 32 developed ALF. Hepatocellular injury, female sex, high levels of TBL, and a high ratio of aspartate aminotransferase (AST):ALT were independent risk factors for ALF. We compared 3 ways to use Hy's Law to predict which patients would develop ALF; all included TBL greater than 2-fold the upper limit of normal (×ULN) and either ALT level greater than 3 × ULN, a ratio (R) value (ALT × ULN/alkaline phosphatase × ULN) of 5 or greater, or a new ratio (nR) value (ALT or AST, whichever produced the highest ×ULN/ alkaline phosphatase × ULN value) of 5 or greater. At recognition of DILI, the R- and nR-based models identified patients who developed ALF with 67% and 63% specificity, respectively, whereas use of only ALT level identified them with 44% specificity. However, the level of ALT and the nR model each identified patients who developed ALF with 90% sensitivity, whereas the R criteria identified them with 83% sensitivity. An equal number of patients who did and did not develop ALF had alkaline phosphatase levels greater than 2 × ULN. An algorithm based on AST level greater than 17.3 × ULN, TBL greater than 6.6 × ULN, and AST:ALT greater than 1.5 identified patients who developed ALF with 82% specificity and 80% sensitivity. CONCLUSIONS When applied at DILI recognition, the nR criteria for Hy's Law provides the best balance of sensitivity and specificity whereas our new composite algorithm provides additional specificity in predicting the ultimate development of ALF.

A validated clinical approach for the management of aspergillosis in critically ill patients: ready, steady, go!

The clinical relevance of recovering Aspergillus species in intensive care unit patients is unknown. Diagnosis of invasive pulmonary aspergillosis is extremely difficult because there are no specific tests sensitive enough to detect it. The rapidly fatal prognosis of this infection without treatment justifies early antifungal therapy. A clinical algorithm may aid clinicians to manage critically ill patients from whose respiratory specimens Aspergillus spp. have been isolated. This new tool needs to be validated in a large cohort of patients before it can be recommended.

Laboratory detection of respiratory viruses by automated techniques.

Advances in clinical virology for detecting respiratory viruses have been focused on nucleic acids amplification techniques, which have converted in the reference method for the diagnosis of acute respiratory infections of viral aetiology. Improvements of current commercial molecular assays to reduce hands-on-time rely on two strategies, a stepwise automation (semi-automation) and the complete automation of the whole procedure. Contributions to the former strategy have been the use of automated nucleic acids extractors, multiplex PCR, real-time PCR and/or DNA arrays for detection of amplicons. Commercial fully-automated molecular systems are now available for the detection of respiratory viruses. Some of them could convert in point-of-care methods substituting antigen tests for detection of respiratory syncytial virus and influenza A and B viruses. This article describes laboratory methods for detection of respiratory viruses. A cost-effective and rational diagnostic algorithm is proposed, considering technical aspects of the available assays, infrastructure possibilities of each laboratory and clinic-epidemiologic factors of the infection.

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Expectations, experiences and attitudes of patients and primary care health professionals regarding online psychotherapeutic interventions for depression: protocol for a qualitative study.

BACKGROUND In the year 2020, depression will cause the second highest amount of disability worldwide. One quarter of the population will suffer from depression symptoms at some point in their lives. Mental health services in Western countries are overburdened. Therefore, cost-effective interventions that do not involve mental health services, such as online psychotherapy programs, have been proposed. These programs demonstrate satisfactory outcomes, but the completion rate for patients is low. Health professionals' attitudes towards this type of psychotherapy are more negative than the attitudes of depressed patients themselves. The aim of this study is to describe the profile of depressed patients who would benefit most from online psychotherapy and to identify expectations, experiences, and attitudes about online psychotherapy among both patients and health professionals that can facilitate or hinder its effects. METHODS A parallel qualitative design will be used in a randomised controlled trial on the efficiency of online psychotherapeutic treatment for depression. Through interviews and focus groups, the experiences of treated patients, their reasons for abandoning the program, the expectations of untreated patients, and the attitudes of health professionals will be examined. Questions will be asked about training in new technologies, opinions of online psychotherapy, adjustment to therapy within the daily routine, the virtual and anonymous relationship with the therapist, the process of online communication, information necessary to make progress in therapy, process of working with the program, motivations and attitudes about treatment, expected consequences, normalisation of this type of therapy in primary care, changes in the physician-patient relationship, and resources and risks. A thematic content analysis from the grounded theory for interviews and an analysis of the discursive positions of participants based on the sociological model for focus groups will be performed. DISCUSSION Knowledge of the expectations, experiences, and attitudes of both patients and medical personnel regarding online interventions for depression can facilitate the implementation of this new psychotherapeutic tool. This qualitative investigation will provide thorough knowledge of the perceptions, beliefs, and values of patients and clinicians, which will be very useful for understanding how to implement this intervention method for depression.

Algoritmo para el diagnóstico precoz de la deficiencia de vitamina b12 en ancianos

BACKGROUND: The elderly population is particularly at risk for developing vitamin B12-deficiency. Serum cobalamin does not necessarily reflect a normal B12 status. The determination of methylmalonic acid is not available in all laboratories. Issues of sensitivity for holotranscobalamin and the low specificity of total homocysteine limit their utility. The aim of the present study is to establish a diagnostic algorithm by using a combination of these markers in place of a single measurement. METHODS: We compared the diagnostic efficiency of these markers for detection of vitamin B12 deficiency in a population (n = 218) of institutionalized elderly (median age 80 years). Biochemical, haematological and morphological data were used to categorize people with or without vitamin B12 deficiency. RESULTS: In receiver operating curves characteristics for detection on vitamin B12 deficiency using single measurements, serum folate has the greatest area under the curve (0.87) and homocysteine the lowest (0.67). The best specificity was observed for erythrocyte folate and methylmalonic acid (100% for both) but their sensitivity was very low (17% and 53%, respectively). The highest sensitivity was observed for homocysteine (81%) and serum folate (74%). When we combined these markers, starting with serum and erythrocyte folate, followed by holotranscobalamin and ending by methylmalonic acid measurements, the overall sensitivity and specificity of the algorithm were 100% and 90%, respectively. CONCLUSION: The proposed algorithm, which combines erythrocyte folate, serum folate, holotranscobalamin and methylmalonic acid, but eliminate B12 and tHcy measurements, is a useful alternative for vitamin B12 deficiency screening in an elderly institutionalized cohort.

New insights to occult gastrointestinal bleeding: From pathophysiology to therapeutics.

Obscure gastrointestinal bleeding is still a clinical challenge for gastroenterologists. The recent development of novel technologies for the diagnosis and treatment of different bleeding causes has allowed a better management of patients, but it also determines the need of a deeper comprehension of pathophysiology and the analysis of local expertise in order to develop a rational management algorithm. Obscure gastrointestinal bleeding can be divided in occult, when a positive occult blood fecal test is the main manifestation, and overt, when external sings of bleeding are visible. In this paper we are going to focus on overt gastrointestinal bleeding, describing the physiopathology of the most usual causes, analyzing the diagnostic procedures available, from the most classical to the novel ones, and establishing a standard algorithm which can be adapted depending on the local expertise or availability. Finally, we will review the main therapeutic options for this complex and not so uncommon clinical problem.