Aim: The optimal risk assessment model (RAM) to stratify the risk of venous thromboembolism (VTE) in medical inpatients is not known. We examined and compared how well the Padua Prediction Score (PPS) and the Caprini RAM stratify VTE risk in medical inpatients.Methods: We undertook a retrospective case-control study among medical inpatients admitted to a large general hospital in China during a 4-year period. In total, 902 cases were confirmed to have VTE during hospitalization and 902 controls were selected randomly to match cases by medical service.Results: The VTE risk increased significantly with an increase of the cumulative PPS or Caprini RAM score. A PPS and Caprini RAM “high risk” classification was, respectively, associated with a 5.01-fold and 4.10-fold increased VTE risk. However, the Caprini RAM could identify 84.3% of the VTE cases to receive prophylaxis according to American College of Chest Physicians guidelines, whereas the PPS could only identify 49.1% of the VTE cases. In the medical inpatients studied, five risk factors seen more frequently in VTE cases than in controls in the Caprini RAM were not included in the PPS. The Caprini RAM risk levels were linked almost perfectly to in-hospital and 6-month mortality.Conclusions: Both the PPS and Caprini RAM can be used to stratify the VTE risk in medical inpatients effectively, but the Caprini RAM may be considered as the first choice in a general hospital because of its incorporation of comprehensive risk factors, higher sensitivity to identify patients who may benefit from prophylaxis, and potential for prediction of mortality.

BackgroundMost resting energy expenditure (REE) predictive equations for adults were derived from research conducted in western populations; whether they can also be used in Chinese young people is still unclear. Therefore, we conducted this study to determine the best REE predictive equation in Chinese normal weight young adults.MethodsForty-three (21 male, 22 female) healthy college students between the age of 18 and 25 years were recruited. REE was measured by the indirect calorimetry (IC) method. Harris-Benedict, World Health Organization (WHO), Owen, Mifflin and Liu’s equations were used to predictREE (REEe). REEe that was within 10% of measured REE (REEm) was defined as accurate. Student’s t test, Wilcoxon Signed Ranks Test, McNemar Test and the Bland-Altman method were used for data analysis.ResultsREEm was significantly lower (P < 0.05 or P < 0.01) than REEe from equations, except for Liu’s, Liu’s-s, Owen, Owen-s and Mifflin in men and Liu’s and Owen in women. REEe calculated by ideal body weight was significantly higher than REEe calculated by current body weight ( P < 0.01), the only exception being Harris-Benedict equation in men. Bland-Altman analysis showed that the Owen equation with current body weight generated the least bias. The biases of REEe from Owen with ideal body weight and Mifflin with both current and ideal weights were also lower.ConclusionsLiu’s, Owen, and Mifflin equations are appropriate for the prediction of REE in young Chinese adults. However, the use of ideal body weight did not increase the accuracy of REEe.

Aim: The appropriate selection of hospitalized patients for venous thromboembolism (VTE) prophylaxis is an important unresolved issue. We sought to validate the Caprini model, a famous individual VTE risk assessment model (RAM), in hospitalized Chinese patients. Methods: We performed a retrospective case-control study among unselected hospitalized patients admitted to a comprehensive hospital in China. A total of 347 patients were confirmed to have VTE during hospitalization, and 651 controls were randomly selected to match the patients according to medical service. Both the patients and controls were retrospectively assessed for the risk of VTE using the Caprini RAM. Results: The average Caprini cumulative risk score in the patients was significantly higher than that observed in the controls (4.69±2.58 vs 3.16±1.82, p＜0.0001). Compared with that observed in the low-risk group, a classification of high-risk according to the Caprini model was associated with a 1.65-fold increased risk of VTE (95%CI 1.05-2.61), while that of highest-risk was associated with a 4.84-fold increased risk of VTE (95%CI 3.06-7.64). After further stratifying the highest risk level with a cumulative risk score of ≥ 5 into scores of 5-6, 7-8 and ≥ 9, the patients with a score of 5-6 were found to exhibit a 3.33-fold increased risk of VTE (95%CI 2.06-5.40), those with a score 7-8 exhibited a 9.41-fold increased risk of VTE (95%CI 4.90-18.08) and those with a score of ≥ 9 exhibited a 24.69-fold (95%CI 7.98-76.40) increased risk of VTE compared with their low-risk counterparts. Conclusions: Our study suggests that the Caprini RAM can be used to effectively stratify hospitalized Chinese patients into VTE risk categories based on individual risk factors. The classification of the highest risk level with a cumulative risk score of ≥ 5 provided significantly more clinical information, and further stratification of this group of patients is needed. J Atheroscler Thromb, 2014; 21:261-272.

These results suggested that plasma miRNAs could be potential specific biomarker for early detection COPD.