38 results about "Adverse outcomes" patented technology

Methods and compositions disclosed herein generally relate to methods of improving clinical and economic outcomes to address adverse effects related to anesthesia, analgesics, opioids, and inadequate pain relief. Embodiments of the invention relate to the association between genes, specific polymorphisms of genes, and non-genetic factors with inadequate pain relief and anesthesia-, analgesic, and / or opioid-related adverse effects. Embodiments of the invention can be used to determine and manage patient risk factors for development of adverse perioperative effects and can allow for personalized anesthesia and pain management for improvement of pain control and reduction of anesthesia-, analgesic-, and opioid-related adverse outcomes. These methods and compositions apply to non-surgical pain management with opioids. Therefore, patients who are genetically predisposed to risk of inadequate pain relief and / or serious side effects from anesthesia, analgesics, and / or opioids can be identified and individualized treatment plans developed for implementation by the clinician to improve clinical and economic outcomes.

A method and system for computing a relative score indicative of an individual infant's feeding performance based, at least in part, upon a comparison of one or more feeding factor measurements of the individual infant with a corresponding database metric that is derived from a population-based sample of infants, where the comparison optionally provides a statistical association between normative metric values and adverse outcomes recorded for the same population-based sample and, thereby, a means for assessing the tested infant's risk for said adverse outcomes.

A method of identifying insights related to the occurrence of an adverse health outcome of interest, comprises extracting electronic clinical data associated with historical healthcare encounters. The method also comprises defining patient groups based upon similar data patterns present in the extracted electronic clinical data wherein the patient groups have varying likelihood for the adverse health outcome. Still further, the method comprises deriving hypothesized etiological explanations for why one or more patient groups have higher likelihood when compared to other patient groups. Optionally, the method comprises identifying clinical interventions that are intended to reduce the likelihood of the adverse outcome for certain patient groups.

The present disclosure provides methods involving use of BIN1 expression levels, in heart tissue, in evaluating the risk of a poor outcome in a patient diagnosed with congestive heart failure. The methods finds use in evaluating patients who are heart transplant candidates as well as in assessing therapy options and efficacy of treatment in congestive heart failure patients.

Transcriptomics data from tumor tissue of patients diagnosed with metastatic breast cancer are clustered and associated with overall survival of the patients. A subset of genes from one of the clusterassociated with poor outcome are used to generate a survival prediction model predicting a survival time based on expression levels of a plurality of genes. Using such generated survival prediction model, a survival time of a patient diagnosed with metastatic breast cancer can be predicted and a treatment regimen can be updated or generated based on the survival time.

The present disclosure provides methods involving use of BIN1 expression levels, in heart tissue, in evaluating the risk of a poor outcome in a patient diagnosed with congestive heart failure. The methods finds use in evaluating patients who are heart transplant candidates as well as in assessing therapy options and efficacy of treatment in congestive heart failure patients.

Predictive models are built for the estimation of adverse health likelihood by identifying candidate model risk variables, constructing a model form for an outcome likelihood model that estimates the likelihood of an adverse outcome type using a group of risk variables selected from the set of candidate model risk variables and by classifying each selected risk variable into either a baseline group or a dynamic group. Additionally, predictive models are built by constructing separate baseline and dynamic outcome likelihood model forms and by fitting the constructed model forms to a training data set to produce final models to be used as scoring functions that compute a baseline outcome likelihood and a dynamic outcome likelihood for patient data that is not represented in the training data set. The predictive models can be used with alerting and attribution algorithms to predict the likelihood of an adverse outcome for individuals receiving care.

The present disclosure provides methods involving use of BIN1 protein levels in biological fluid of a subject in evaluating cardiac health of the subject. The method provided herein may be used to predict a risk of a poor outcome in a subject. The methods also find use in evaluating subjects for assessing patients diagnosed with heart failure. These methods are also useful in assessing therapy options and efficacy of treatment in heart failure patients.

Provided herein are devices and methods for connecting a transcutaneous external prosthetic device to a bone, such as a bone of an amputee. The device is a two-piece transcutaneous implant device to provide reversible connection for ease of implantation, reliability, and relatively easy access for removal, while maximizing tissue ingrowth to reduce risk of infection and attendant adverse outcomes. The devices provided herein comprise a prosthetic interface and a bone anchor. A through-hole that traverses a longitudinal length of the prosthetic interface and at least a longitudinal portion of the bone anchor receives a fastener to reversibly connect the prosthetic interface to the bone anchor implanted in bone. A connector may connect to a failsafe element which, in turn, connects to an external prosthetic device.