The complexity and heterogeneity of patients with multimorbidity and polypharmacy renders traditional disease‐oriented guidelines often inadequate and complicates clinical decision making. To address ...this challenge, guidelines have been developed on multimorbidity or polypharmacy. To systematically analyse their recommendations, we conducted a systematic guideline review using the Ariadne principles for managing multimorbidity as analytical framework. The information synthesis included a multistep consensus process involving 18 multidisciplinary experts from seven countries. We included eight guidelines (four each on multimorbidity and polypharmacy) and extracted about 250 recommendations. The guideline addressed (i) the identification of the target population (risk factors); (ii) the assessment of interacting conditions and treatments: medical history, clinical and psychosocial assessment including physiological status and frailty, reviews of medication and encounters with healthcare providers highlighting informational continuity; (iii) the need to incorporate patient preferences and goal setting: eliciting preferences and expectations, the process of shared decision making in relation to treatment options and the level of involvement of patients and carers; (iv) individualized management: guiding principles on optimization of treatment benefits over possible harms, treatment communication and the information content of medication/care plans; (v) monitoring and follow‐up: strategies in care planning, self‐management and medication‐related aspects, communication with patients including safety instructions and adherence, coordination of care regarding referral and discharge management, medication appropriateness and safety concerns. The spectrum of clinical and self‐management issues varied from guiding principles to specific recommendations and tools providing actionable support. The limited availability of reliable risk prediction models, feasible interventions of proven effectiveness and decision aids, and limited consensus on appropriate outcomes of care highlight major research deficits. An integrated approach to both multimorbidity and polypharmacy should be considered in future guidelines.
Content List – Read more articles from the symposium: “Multimorbidity research at the cross‐roads: developing the evidence for clinical practice and health policy”.
Antimicrobial resistance has emerged as a major concern in developing countries. The present study sought to define the pattern of antimicrobial resistance in ICU patients with ventilator-associated ...pneumonia.
Between November 2014 and September 2015, we enrolled 220 patients (average age ~ 71 yr) who were admitted to ICU in a major tertiary hospital in Ho Chi Minh City, Vietnam. Data concerning demographic characteristics and clinical history were collected from each patient. The Bauer-Kirby disk diffusion method was used to detect the antimicrobial susceptibility.
Antimicrobial resistance was commonly found in ceftriaxone (88%), ceftazidime (80%), ciprofloxacin (77%), cefepime (75%), levofloxacin (72%). Overall, the rate of antimicrobial resistance to any drug was 93% (n = 153/164), with the majority (87%) being resistant to at least 2 drugs. The three commonly isolated microorganisms were Acinetobacter (n = 75), Klebsiella (n = 39), and Pseudomonas aeruginosa (n = 29). Acinetobacter baumannii were virtually resistant to ceftazidime, ceftriaxone, piperacilin, imipenem, meropenem, ertapenem, ciprofloxacin and levofloxacin. High rates (>70%) of ceftriaxone and ceftazidime-resistant Klebsiella were also observed.
These data indicated that critically ill patients on ventilator in Vietnam were at disturbingly high risk of antimicrobial resistance. The data also imply that these Acinetobacter, Klebsiella, and Pseudomonas aeruginosa and multidrug resistance pose serious therapeutic problems in ICU patients. A concerted and systematic effort is required to rapidly identify high risk patients and to reduce the burden of antimicrobial resistance in developing countries.
Carbapenemase-producing Enterobacteriaceae (CPE) are well known to cause many serious infections resulting in increasing mortality rate, treatment cost, and prolonged hospitalization. Among the ...widely recognized types of carbapenemases, New Delhi β-lactamase (NDM) and Klebsiella pneumoniae carbapenemase (KPC) are the most important enzymes. However, in Vietnam, there are only scattered reports of CPE due to the lack of simple and affordable methods that are suitable to laboratory conditions. This study aims to survey the characteristics of carbapenem-resistant E. coli and K. pneumoniae (CR-E/K) at two hospitals in Southern Vietnam and perform some simple methods to detect the two enzymes. A total of 100 CR-E/K strains were collected from clinical isolates of Gia Dinh People’s Hospital and Dong Nai General Hospital, Vietnam, from November 2017 to May 2018. The patient-related information was also included in the analysis. We conducted real-time polymerase chain reaction (PCR), Modified Hodge Test (MHT), and combined disk test (CDT) on all isolates. Carbapenemase-encoding genes were detected in 47 isolates (36 NDM, 10 KPC, and one isolate harboring both genes). The E. coli strain carrying simultaneously these two genes was the first case reported here. Most of isolates were collected from patients in ICU, Infectious Disease Department, and Department of Urologic Surgery. Urine and sputum were two common specimens. The true positive rate (sensitivity, TPR) and specificity (SPC) of the imipenem–EDTA (ethylen diamine tetra acetic acid) for NDM detection and the imipenem–PBA (phenylboronic acid) for KPC detection on E. coli were 93.8%, 97.1% and 66.7%, 95.7%, respectively. Meanwhile, the imipenem–EDTA for NDM detection and the imipenem–PBA for KPC detection among K. pneumonia achieved 90.5%, 100% and 100%, 92.9% TPR and SPC, respectively. However, MHT showed low sensitivity and specificity. Our findings showed that CP-E/K were detected with high prevalence in the two hospitals. We suggest that CDT can be used as a low-priced and accurate method of detection.
Spin Torque—Generated Magnetic Droplet Solitons Mohseni, S. M.; Sani, S. R.; Persson, J. ...
Science (American Association for the Advancement of Science),
03/2013, Volume:
339, Issue:
6125
Journal Article
Peer reviewed
Dissipative solitons have been reported in a wide range of nonlinear systems, but the observation of their magnetic analog has been experimentally challenging. Using spin transfer torque underneath a ...nanocontact on a magnetic thin film with perpendicular magnetic anisotropy (PMA), we have observed the generation of dissipative magnetic droplet solitons and report on their rich dynamical properties. Micromagnetic simulations identify a wide range of automodulation frequencies, including droplet oscillatory motion, droplet "spinning," and droplet "breather" states. The droplet can be controlled by using both current and magnetic fields and is expected to have applications in spintronics, magnonics, and PMA-based domain-wall devices.
Abstract
STUDY QUESTION
Can an artificial intelligence (AI)-based model predict human embryo viability using images captured by optical light microscopy?
SUMMARY ANSWER
We have combined computer ...vision image processing methods and deep learning techniques to create the non-invasive Life Whisperer AI model for robust prediction of embryo viability, as measured by clinical pregnancy outcome, using single static images of Day 5 blastocysts obtained from standard optical light microscope systems.
WHAT IS KNOWN ALREADY
Embryo selection following IVF is a critical factor in determining the success of ensuing pregnancy. Traditional morphokinetic grading by trained embryologists can be subjective and variable, and other complementary techniques, such as time-lapse imaging, require costly equipment and have not reliably demonstrated predictive ability for the endpoint of clinical pregnancy. AI methods are being investigated as a promising means for improving embryo selection and predicting implantation and pregnancy outcomes.
STUDY DESIGN, SIZE, DURATION
These studies involved analysis of retrospectively collected data including standard optical light microscope images and clinical outcomes of 8886 embryos from 11 different IVF clinics, across three different countries, between 2011 and 2018.
PARTICIPANTS/MATERIALS, SETTING, METHODS
The AI-based model was trained using static two-dimensional optical light microscope images with known clinical pregnancy outcome as measured by fetal heartbeat to provide a confidence score for prediction of pregnancy. Predictive accuracy was determined by evaluating sensitivity, specificity and overall weighted accuracy, and was visualized using histograms of the distributions of predictions. Comparison to embryologists’ predictive accuracy was performed using a binary classification approach and a 5-band ranking comparison.
MAIN RESULTS AND THE ROLE OF CHANCE
The Life Whisperer AI model showed a sensitivity of 70.1% for viable embryos while maintaining a specificity of 60.5% for non-viable embryos across three independent blind test sets from different clinics. The weighted overall accuracy in each blind test set was >63%, with a combined accuracy of 64.3% across both viable and non-viable embryos, demonstrating model robustness and generalizability beyond the result expected from chance. Distributions of predictions showed clear separation of correctly and incorrectly classified embryos. Binary comparison of viable/non-viable embryo classification demonstrated an improvement of 24.7% over embryologists’ accuracy (P = 0.047, n = 2, Student’s t test), and 5-band ranking comparison demonstrated an improvement of 42.0% over embryologists (P = 0.028, n = 2, Student’s t test).
LIMITATIONS, REASONS FOR CAUTION
The AI model developed here is limited to analysis of Day 5 embryos; therefore, further evaluation or modification of the model is needed to incorporate information from different time points. The endpoint described is clinical pregnancy as measured by fetal heartbeat, and this does not indicate the probability of live birth. The current investigation was performed with retrospectively collected data, and hence it will be of importance to collect data prospectively to assess real-world use of the AI model.
WIDER IMPLICATIONS OF THE FINDINGS
These studies demonstrated an improved predictive ability for evaluation of embryo viability when compared with embryologists’ traditional morphokinetic grading methods. The superior accuracy of the Life Whisperer AI model could lead to improved pregnancy success rates in IVF when used in a clinical setting. It could also potentially assist in standardization of embryo selection methods across multiple clinical environments, while eliminating the need for complex time-lapse imaging equipment. Finally, the cloud-based software application used to apply the Life Whisperer AI model in clinical practice makes it broadly applicable and globally scalable to IVF clinics worldwide.
STUDY FUNDING/COMPETING INTEREST(S)
Life Whisperer Diagnostics, Pty Ltd is a wholly owned subsidiary of the parent company, Presagen Pty Ltd. Funding for the study was provided by Presagen with grant funding received from the South Australian Government: Research, Commercialisation and Startup Fund (RCSF). ‘In kind’ support and embryology expertise to guide algorithm development were provided by Ovation Fertility. J.M.M.H., D.P. and M.P. are co-owners of Life Whisperer and Presagen. Presagen has filed a provisional patent for the technology described in this manuscript (52985P pending). A.P.M. owns stock in Life Whisperer, and S.M.D., A.J., T.N. and A.P.M. are employees of Life Whisperer.
Training on multiple diverse data sources is critical to ensure unbiased and generalizable AI. In healthcare, data privacy laws prohibit data from being moved outside the country of origin, ...preventing global medical datasets being centralized for AI training. Data-centric, cross-silo federated learning represents a pathway forward for training on distributed medical datasets. Existing approaches typically require updates to a training model to be transferred to a central server, potentially breaching data privacy laws unless the updates are sufficiently disguised or abstracted to prevent reconstruction of the dataset. Here we present a completely decentralized federated learning approach, using knowledge distillation, ensuring data privacy and protection. Each node operates independently without needing to access external data. AI accuracy using this approach is found to be comparable to centralized training, and when nodes comprise poor-quality data, which is common in healthcare, AI accuracy can exceed the performance of traditional centralized training.
This article represents the first in a series of tutorials on model evaluation in nonlinear mixed effect models (NLMEMs), from the International Society of Pharmacometrics (ISoP) Model Evaluation ...Group. Numerous tools are available for evaluation of NLMEM, with a particular emphasis on visual assessment. This first basic tutorial focuses on presenting graphical evaluation tools of NLMEM for continuous data. It illustrates graphs for correct or misspecified models, discusses their pros and cons, and recalls the definition of metrics used.
Background Glycosylated hemoglobin (HbA1c) is diagnostic of and a measure of the quality of control of diabetes mellitus. Both HbA1c and perioperative hyperglycemia have been targeted as modifiable ...risk factors for postoperative complications. The HbA1c percent cutoff that best predicts major complications has not been defined. Study Design A prospective study of all abdominal operations from a single institution from 2007 to 2010 was performed. All patients with HbA1c within 3 months before surgery were included. The primary end point was major complication, using the Clavien-Dindo complication system, within 30 days of surgery. Stepwise, multivariate analysis was performed including clinically relevant variables chosen a priori. Results Among 438 patients who had a measured HbA1c, 96 (21.9%) experienced a major complication. On multivariate analysis, HbA1c ≥6.5% (odds ratio = 1.95; 95% CI, 1.17–3.24; p = 0.01) was found to be the most significant predictor of major complications. Glyosylated hemoglobin and glucose were strongly correlated (correlation coefficient 0.414, p < 0.01). Predicted probabilities demonstrated that both HbA1c and glucose together contributed to major complications; and HbA1c impacted the ability to achieve optimal perioperative glucose control. Patients with a BMI >30 kg/m2 , history of coronary artery disease, and nonwhite race were more likely to have a HbA1c ≥6.5%. Conclusions Elevated HbA1c ≥6.5% and perioperative hyperglycemia were associated with an increased rate of major complications after abdominal surgery. Elevated peak postoperative glucose levels were correlated with elevated HbA1c and were independently associated with major complications. More liberal HbA1c testing should be considered in high-risk patients before elective surgery. Safe, feasible, and effective strategies to reduce both HbA1c and perioperative hyperglycemia need to be developed to optimize patient outcomes.
Objective: Obesity is related to increased risk of several health complications, including depression. Many studies have reported improvements in mood with weight loss, but results have been ...equivocal. The present meta-analysis examined changes in symptoms of depression that were reported in trials of weight loss interventions. Between-groups comparisons of different weight loss methods (for example, lifestyle modification, diet-alone and pharmacotherapy) were examined, as were within-group changes for each treatment type. Method: MEDLINE was searched for articles published between 1950 and January 2009. Several obesity-related terms were intersected with terms related to depression. Results were filtered to return only studies of human subjects, published in English. Of 5971 articles, 394 were randomized controlled trials. Articles were excluded if they did not report mean changes in weight or symptoms of depression, included children or persons with psychiatric disorders (other than depression), or provided insufficient data for analysis. Thirty-one studies (n=7937) were included. Two authors independently extracted a description of each study treatment, sample characteristics, assessment methods and changes in weight and symptoms of depression. Treatments were categorized as lifestyle modification, non-dieting, dietary counseling, diet-alone, exercise-alone, pharmacotherapy, placebo or control interventions. Results: Random effects models found that lifestyle modification was superior to control and non-dieting interventions for reducing symptoms of depression, and marginally better than dietary counseling and exercise-alone programs. Exercise-alone programs were superior to controls. No differences were found for comparisons of pharmacologic agents and placebos. Within-group analyses found significant reductions in symptoms of depression for nearly all active interventions. A meta-regression found no relationship between changes in weight and changes in symptoms of depression in lifestyle modification interventions. Conclusions: On average, obese individuals in weight loss trials experienced reductions in symptoms of depression. Future studies should examine incidence and resolution of clinically significant depressive disorders with weight loss interventions.
Recent years have disclosed a remarkable proliferation of compute-intensive applications in smart cities. Such applications continuously generate enormous amounts of data which demand strict ...latency-aware computational processing capabilities. Although edge computing is an appealing technology to compensate for stringent latency-related issues, its deployment engenders new challenges. In this article, we highlight the role of edge computing in realizing the vision of smart cities. First, we analyze the evolution of edge computing paradigms. Subsequently, we critically review the state-of-the-art literature focusing on edge computing applications in smart cities. Later, we categorize and classify the literature by devising a comprehensive and meticulous taxonomy. Furthermore, we identify and discuss key requirements, and enumerate recently reported synergies of edge computing-enabled smart cities. Finally, several indispensable open challenges along with their causes and guidelines are discussed, serving as future research directions.
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