A novel framework for predicting patients at risk of readmission

Uncertainty in decision-making for patients’ risk of re-admission arises due to non-uniform data and lack of knowledge in health system variables. The knowledge of the impact of risk factors will provide clinicians better decision-making and in reducing the number of patients admitted to the hospital. Traditional approaches are not capable to account for the uncertain nature of risk of hospital re-admissions. More problems arise due to large amount of uncertain information. Patients can be at high, medium or low risk of re-admission, and these strata have ill-defined boundaries. We believe that our model that adapts fuzzy regression method will start a novel approach to handle uncertain data, uncertain relationships between health system variables and the risk of re-admission. Because of nature of ill-defined boundaries of risk bands, this approach does allow the clinicians to target individuals at boundaries. Targeting individuals at boundaries and providing them proper care may provide some ability to move patients from high risk to low risk band. In developing this algorithm, we aimed to help potential users to assess the patients for various risk score thresholds and avoid readmission of high risk patients with proper interventions. A model for predicting patients at high risk of re-admission will enable interventions to be targeted before costs have been incurred and health status have deteriorated. A risk score cut off level would flag patients and result in net savings where intervention costs are much higher per patient. Preventing hospital re-admissions is important for patients, and our algorithm may also impact hospital income.

Antioxidant status in J774A.1 macrophage cell line during chronic exposure to glycated serum

Advanced glycation end-products (AGEs) are linked to aging and correlated diseases. The aim of present study was to evaluate oxidative stress related parameters in J774A.1 murine macrophage cells during chronic exposure to a subtoxic concentration of AGE (5% ribose-glycated serum (GS)) and subsequently for 48 h to a higher dose (10% GS). No effects on cell viability were evident in either experimental condition. During chronic treatment, glycative markers (free and bound pentosidine) increased significantly in intra- and extracellular environments, but the production and release of thiobarbituric acid reactive substances (TBARs), as an index of lipid peroxidation, underwent a time-dependent decrease. Exposure to 10% GS evidenced that glycative markers rose further, while TBARs elicited a cellular defence against oxidative stress. Nonadapted cultures showed an accumulation of AGEs, a marked oxidative stress, and a loss of viability. During 10% GS exposure, reduced glutathione levels in adapted cultures remained constant, as did the oxidized glutathione to reduced glutathione ratio, while nonadapted cells showed a markedly increased redox ratio. A constant increase of heat shock protein 70 (HSP70) mRNA was observed in all experimental conditions. On the contrary, HSP70 expression became undetectable for a longer exposure time; this could be due to the direct involvement of HSP70 in the refolding of damaged proteins. Our findings suggest an adaptive response of macrophages to subtoxic doses of AGE, which could constitute an important factor in the spread of damage to other cellular types during aging.Key words: in vitro cytotoxicity, AGE, pentosidine, glycoxidation, oxidative stress, TBARs.