Use, Impact, Weaknesses, and Advanced Features of Search Functions for Clinical Use in Electronic Health Records: A Scoping Review

Objective: Although vast amounts of patient information are captured in electronic health records (EHRs), effective clinical use of this information is challenging due to inadequate and inefficient access to it at the point of care. The purpose of this study was to conduct a scoping review of the literature on the use of EHR search functions within a single patient's record in clinical settings to characterize the current state of research on the topic and identify areas for future study. Methods: We conducted a literature search of four databases to identify articles on within-EHR search functions or the use of EHR search function in the context of clinical tasks. After reviewing titles and abstracts and performing a full-text review of selected articles, we included 17 articles in the analysis. We qualitatively identified themes in those articles and synthesized the literature for each theme. Results: Based on the 17 articles analyzed, we delineated four themes: (1) how clinicians use search functions, (2) impact of search functions on clinical workflow, (3) weaknesses of current search functions, and (4) advanced search features. Our review found that search functions generally facilitate patient information retrieval by clinicians and are positively received by users. However, existing search functions have weaknesses, such as yielding false negatives and false positives, which can decrease trust in the results, and requiring a high cognitive load to perform an inclusive search of a patient's record. Conclusion: Despite the widespread adoption of EHRs, only a limited number of articles describe the use of EHR search functions in a clinical setting, despite evidence that they benefit clinician workflow and productivity. Some of the weaknesses of current search functions may be addressed by enhancing EHR search functions with collaborative filtering

Murein and pseudomurein cell wall binding domains of bacteria and archaea—a comparative view

The cell wall, a major barrier protecting cells from their environment, is an essential compartment of both bacteria and archaea. It protects the organism from internal turgor pressure and gives a defined shape to the cell. The cell wall serves also as an anchoring surface for various proteins and acts as an adhesion platform for bacteriophages. The walls of bacteria and archaea are mostly composed of murein and pseudomurein, respectively. Cell wall binding domains play a crucial role in the non-covalent attachment of proteins to cell walls. Here, we give an overview of the similarities and differences in the biochemical and functional properties of the two major murein and pseudomurein cell wall binding domains, i.e., the Lysin Motif (LysM) domain (Pfam PF01476) and the pseudomurein binding (PMB) domain (Pfam PF09373) of bacteria and archaea, respectively

Wnt antagonist secreted frizzled-related protein 4 upregulates adipogenic differentiation in human adipose tissue-derived mesenchymal stem cells

With more than 1.4 billion overweight or obese adults worldwide, obesity and progression of the metabolic syndrome are major health and economic challenges. To address mechanisms of obesity, adipose tissue-derived mesenchymal stem cells (ADSCs) are being studied to detail the molecular mechanisms involved in adipogenic differentiation. Activation of the Wnt signalling pathway has inhibited adipogenesis from precursor cells. In our study, we examined this anti-adipogenic effect in further detail stimulating Wnt with lithium chloride (LiCl) and 6-bromo indirubin 3'oxime (BIO). We also examined the effect of Wnt inhibition using secreted frizzled-related protein 4 (sFRP4), which we have previously shown to be pro-apoptotic, anti-angiogenic, and anti-tumorigenic. Wnt stimulation in LiCl and BIOtreated ADSCs resulted in a significant reduction (2.7-fold and 12-fold respectively) in lipid accumulation as measured by Oil red O staining while Wnt inhibition with sFRP4 induced a 1.5-fold increase in lipid accumulation. Furthermore, there was significant 1.2-fold increase in peroxisome proliferator-activated receptor gamma (PPAR ?) and CCAAT/enhancer binding protein alpha (C/EBPa), and 1.3-fold increase in acetyl CoA carboxylase protein levels. In contrast, the expression of adipogenic proteins (PPAR?, C/EBPa, and acetyl CoA carboxylase) were decreased significantly with LiCl (by 1.6, 2.6, and 1.9-fold respectively) and BIO (by 7, 17, and 5.6-fold respectively) treatments. These investigations demonstrate interplay between Wnt antagonism and Wnt activation during adipogenesis and indicate pathways for therapeutic intervention to control this process

Learning genetic epistasis using Bayesian network scoring criteria

<p>Abstract</p> <p>Background</p> <p>Gene-gene epistatic interactions likely play an important role in the genetic basis of many common diseases. Recently, machine-learning and data mining methods have been developed for learning epistatic relationships from data. A well-known combinatorial method that has been successfully applied for detecting epistasis is <it>Multifactor Dimensionality Reduction </it>(MDR). Jiang et al. created a combinatorial epistasis learning method called <it>BNMBL </it>to learn Bayesian network (BN) epistatic models. They compared BNMBL to MDR using simulated data sets. Each of these data sets was generated from a model that associates two SNPs with a disease and includes 18 unrelated SNPs. For each data set, BNMBL and MDR were used to score all 2-SNP models, and BNMBL learned significantly more correct models. In real data sets, we ordinarily do not know the number of SNPs that influence phenotype. BNMBL may not perform as well if we also scored models containing more than two SNPs. Furthermore, a number of other BN scoring criteria have been developed. They may detect epistatic interactions even better than BNMBL.</p> <p>Although BNs are a promising tool for learning epistatic relationships from data, we cannot confidently use them in this domain until we determine which scoring criteria work best or even well when we try learning the correct model without knowledge of the number of SNPs in that model.</p> <p>Results</p> <p>We evaluated the performance of 22 BN scoring criteria using 28,000 simulated data sets and a real Alzheimer's GWAS data set. Our results were surprising in that the Bayesian scoring criterion with large values of a hyperparameter called α performed best. This score performed better than other BN scoring criteria and MDR at <it>recall </it>using simulated data sets, at detecting the hardest-to-detect models using simulated data sets, and at substantiating previous results using the real Alzheimer's data set.</p> <p>Conclusions</p> <p>We conclude that representing epistatic interactions using BN models and scoring them using a BN scoring criterion holds promise for identifying epistatic genetic variants in data. In particular, the Bayesian scoring criterion with large values of a hyperparameter α appears more promising than a number of alternatives.</p

Multinational characterization of neurological phenotypes in patients hospitalized with COVID-19

Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents (January–September 2020) for a cross-sectional analysis. We assessed the frequency of International Classification of Disease code of neurological conditions by countries, healthcare systems, time before and after admission for COVID-19 and COVID-19 severity. Among 35,177 hospitalized patients with SARS-CoV-2 infection, there was an increase in the proportion with disorders of consciousness (5.8%, 95% confidence interval [CI] 3.7–7.8%, pFDR < 0.001) and unspecified disorders of the brain (8.1%, 5.7–10.5%, pFDR < 0.001) when compared to the pre-admission proportion. During hospitalization, the relative risk of disorders of consciousness (22%, 19–25%), cerebrovascular diseases (24%, 13–35%), nontraumatic intracranial hemorrhage (34%, 20–50%), encephalitis and/or myelitis (37%, 17–60%) and myopathy (72%, 67–77%) were higher for patients with severe COVID-19 when compared to those who never experienced severe COVID-19. Leveraging a multinational network to capture standardized EHR data, we highlighted the increased prevalence of central and peripheral neurological phenotypes in patients hospitalized with COVID-19, particularly among those with severe disease

Metabolism before, during and after anaesthesia in colic and healthy horses

<p>Abstract</p> <p>Background</p> <p>Many colic horses are compromised due to the disease state and from hours of starvation and sometimes long trailer rides. This could influence their muscle energy reserves and affect the horses' ability to recover. The principal aim was to follow metabolic parameter before, during, and up to 7 days after anaesthesia in healthy horses and in horses undergoing abdominal surgery due to colic.</p> <p>Methods</p> <p>20 healthy horses given anaesthesia alone and 20 colic horses subjected to emergency abdominal surgery were anaesthetised for a mean of 228 minutes and 183 minutes respectively. Blood for analysis of haematology, electrolytes, cortisol, creatine kinase (CK), free fatty acids (FFA), glycerol, glucose and lactate was sampled before, during, and up to 7 days after anaesthesia. Arterial and venous blood gases were obtained before, during and up to 8 hours after recovery. Gluteal muscle biopsy specimens for biochemical analysis of muscle metabolites were obtained at start and end of anaesthesia and 1 h and 1 day after recovery.</p> <p>Results</p> <p>Plasma cortisol, FFA, glycerol, glucose, lactate and CK were elevated and serum phosphate and potassium were lower in colic horses before anaesthesia. Muscle adenosine triphosphate (ATP) content was low in several colic horses. Anaesthesia and surgery resulted in a decrease in plasma FFA and glycerol in colic horses whereas levels increased in healthy horses. During anaesthesia muscle and plasma lactate and plasma phosphate increased in both groups. In the colic horses plasma lactate increased further after recovery. Plasma FFA and glycerol increased 8 h after standing in the colic horses. In both groups, plasma concentrations of CK increased and serum phosphate decreased post-anaesthesia. On Day 7 most parameters were not different between groups. Colic horses lost on average 8% of their initial weight. Eleven colic horses completed the study.</p> <p>Conclusion</p> <p>Colic horses entered anaesthesia with altered metabolism and in a negative oxygen balance. Muscle oxygenation was insufficient during anaesthesia in both groups, although to a lesser extent in the healthy horses. The post-anaesthetic period was associated with increased lipolysis and weight loss in the colic horses, indicating a negative energy balance during the first week post-operatively.</p

Rhabdomyolysis in Community Acquired Bacterial Sepsis – A Retrospective Cohort Study

BACKGROUND AND OBJECTIVES:Rhabdomyolysis is often associated with sepsis and gram positive bacterial pathogens are reported to be the most frequent cause of sepsis induced rhabdomyolysis. We report the pattern of infecting bacterial pathogens and associated causal factors in a South-Indian cohort. DESIGN, SETTING, PARTICIPANTS #ENTITYSTARTX00026; MEASUREMENTS:Retrospective cohort study of adult patients with community acquired bacterial sepsis complicated by rhabdomyolysis from March 2003--August 2008. Rhabdomyolysis was defined as serum creatine kinase >2000 IU/L. The study population was divided into group-I (sepsis with gram positive pathogens), group-II (sepsis with gram negative pathogens) and group-III (culture negative sepsis). RESULTS:103 patients (group I -15, group II- 34 and group III- 54) formed the study cohort. Mean age was 55 years and two-third had diabetes. Mean creatine kinase was 7114 IU/L and mean serum creatinine on admission was 2.4 mg/dl. Causative pathogen of sepsis was identified in 47.5%. Gram negative pathogens were more frequently (33%) associated with rhabdomyolysis than gram positive pathogens (14.5%). Lung was the commonest foci of sepsis (38.8%). 78.6% of the study population had one or more additional causal factor for rhabdomyolysis like statin intake, chronic alcoholism, hypokalemia, hypernatremia and hypophosphatemia. Mortality was 59%. CONCLUSIONS:Gram negative bacterial pathogens were more frequently associated with rhabdomyolysis than gram positive pathogens. Rhabdomyolysis in patients with sepsis is multifactorial and is associated with high mortality

Assessing machine learning for diagnostic classification of hypertension types identified by ambulatory blood pressure monitoring

Background: Inaccurate blood pressure classification results in inappropriate treatment. We tested if machine learning (ML), using routine clinical data, can serve as a reliable alternative to Ambulatory Blood Pressure Monitoring (ABPM) in classifying blood pressure status. Methods: This study employed a multi-centre approach involving three derivation cohorts from Glasgow, Gdańsk, and Birmingham, and a fourth independent evaluation cohort. ML models were trained using office BP, ABPM, and clinical, laboratory, and demographic data, collected from patients referred for hypertension assessment. Seven ML algorithms were trained to classify patients into five groups: Normal/Target, Hypertension-Masked, Normal/Target-White-Coat, Hypertension-White-Coat, and Hypertension. The 10-year cardiovascular outcomes and 27-year all-cause mortality risks were calculated for the ML-derived groups using the Cox proportional hazards model. Results: Overall XGBoost showed the highest AUROC of 0.85-0.88 across derivation cohorts, Glasgow (n=923; 43% females; age 50.7±16.3 years), Gdańsk (n=709; 46% females; age 54.4±13 years), and Birmingham (n=1,222; 56% females; age 55.7±14 years). But accuracy (0·57-0·72) and F1 scores (0·57-0·69) were low across the three patient cohorts. The evaluation cohort (n=6213, 51% females; age 51.2±10.8 years) indicated elevated 10-year risks of composite cardiovascular events in the Normal/Target-White-Coat and Hypertension-White-Coat groups, with heightened 27-year all-cause mortality observed in all groups except Hypertension-Masked, compared to the Normal/Target group. Conclusions: Machine learning has limited potential in accurate blood pressure classification when ABPM is unavailable. Larger studies including diverse patient groups and different resource settings are warranted

Reflexivity as a ground-clearing activity within the context of early years' pedagogy

The article concerns itself with the struggles that are prompted by the question, “What is my position as a teacher who whilst wanting to pursue emancipatory practices nevertheless is fearful of finding herself supporting and perpetuating normalizing structures?” An extract drawn from a journal entry serves as a base on which a series of reflexive readings are rehearsed. These have spanned over a period of time (2000-2009) and, as a consequence, convey the theoretical vantage points that have been used to create conceptual openings where there are possibilities for thinking “differently.” Both practices of deconstruction (Derrida) and anthropological work on purification rites (Douglas and Kristeva) are used to shift the means with which the author makes sense. Overall, the article depicts an individual’s attempts at creating a becoming space, where thinking and doing may be a little less bounded