BackgroundHospitalized medical patients are at risk for venous thromboembolism (VTE). Universal application of pharmacological thromboprophylaxis has the potential to place a large number of patients at increased bleeding risk. In this study, we aimed to externally validate the International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) VTE risk assessment model in a hospitalized general medical population.Methods and ResultsWe identified medical discharges that met the IMPROVE protocol. Cases were defined as hospital‐acquired VTE and confirmed by diagnostic study within 90 days of index hospitalization; matched controls were also identified. Risk factors for VTE were based on the IMPROVE risk assessment model (aged >60 years, prior VTE, intensive care unit or coronary care unit stay, lower limb paralysis, immobility, known thrombophilia, and cancer) and were measured and assessed. A total of 19 217 patients met the inclusion criteria. The overall VTE event rate was 0.7%. The IMPROVE risk assessment model identified 2 groups of the cohort by VTE incidence rate: The low‐risk group had a VTE event rate of 0.42 (95% CI 0.31 to 0.53), corresponding to a score of 0 to 2, and the at‐risk group had a VTE event rate of 1.29 (95% CI 1.01 to 1.57), corresponding to a score of ≥3. Low‐risk status for VTE encompassed 68% of the patient cohort. The area under the receiver operating characteristic curve was 0.702, which was in line with the derivation cohort findings.ConclusionsThe IMPROVE VTE risk assessment model validation cohort revealed good discrimination and calibration for both the overall VTE risk model and the identification of low‐risk and at‐risk medical patient groups, using a risk score of ≥3. More than two thirds of the entire cohort had a score ≤2.

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The IMPROVE Bleed Risk Assessment Model (RAM) remains the only bleed RAM in hospitalised medical patients using 11 clinical and laboratory factors. The aim of our study was to externally validate the IMPROVE Bleed RAM. A retrospective chart review was conducted between October 1, 2012 and July 31, 2014. We applied the point scoring system to compute risk scores for each patient in the validation sample. We then dichotomised the patients into those with a score <7 (low risk) vs ≥ 7 (high risk), as outlined in the original study, and compared the rates of any bleed, non-major bleed, and major bleed. Among the 12,082 subjects, there was an overall 2.6 % rate of any bleed within 14 days of admission. There was a 2.12 % rate of any bleed in those patients with a score of < 7 and a 4.68 % rate in those with a score ≥ 7 [Odds Ratio (OR) 2.3 (95 % CI=1.8-2.9), p<0.0001]. MB rates were 1.5 % in the patients with a score of < 7 and 3.2 % in the patients with a score of ≥ 7, [OR 2.2 (95 % CI=1.6-2.9), p<0.0001]. The ROC curve was 0.63 for the validation sample. This study represents the largest externally validated Bleed RAM in a hospitalised medically ill patient population. A cut-off point score of 7 or above was able to identify a high-risk patient group for MB and any bleed. The IMPROVE Bleed RAM has the potential to allow for more tailored approaches to thromboprophylaxis in medically ill hospitalised patients.

Diabetics appear to have a lower risk of prostate cancer, though this effect may be limited to whites. An understanding of this association and its race specificity may help to explain the major difference in incidence rates for prostate cancer between blacks and whites.

Pain is a complex multidimensional experience encompassing sensory-discriminative, affective-motivational and cognitive-emotional components mediated by different neural mechanisms. Investigations of neurophysiological signals from simultaneous recordings of two or more cortical circuits may reveal important circuit mechanisms on cortical pain processing. The anterior cingulate cortex (ACC) and primary somatosensory cortex (S1) represent two most important cortical circuits related to sensory and affective processing of pain. Here, we recorded in vivo extracellular activity of the ACC and S1 simultaneously from male adult Sprague-Dale rats ( n = 5), while repetitive noxious laser stimulations were delivered to animalÕs hindpaw during pain experiments. We identified spontaneous pain-like events based on stereotyped pain behaviors in rats. We further conducted systematic analyses of spike and local field potential (LFP) recordings from both ACC and S1 during evoked and spontaneous pain episodes. From LFP recordings, we found stronger phase-amplitude coupling (theta phase vs. gamma amplitude) in the S1 than the ACC ( n = 10 sessions), in both evoked ( p = 0.058) and spontaneous pain-like behaviors ( p = 0.017, paired signed rank test). In addition, pain-modulated ACC and S1 neuronal firing correlated with the amplitude of stimulus-induced event-related potentials (ERPs) during evoked pain episodes. We further designed statistical and machine learning methods to detect pain signals by integrating ACC and S1 ensemble spikes and LFPs. Together, these results reveal differential coding roles between the ACC and S1 in cortical pain processing, as well as point to distinct neural mechanisms between evoked and putative spontaneous pain at both LFP and cellular levels.