OBJECTIVEBy correlating known diabetes duration with the prevalence of retinopathy, more than 10 years have been estimated to lapse between the onset and diagnosis of type 2 diabetes. Such calculations, however, assumed a linear model, included stages of retinopathy not specific to diabetes, and allowed 5 years for retinopathy to occur after the onset of diabetes. We calculated the duration of undiagnosed type 2 diabetes in outpatients screened for retinopathy in a hospital-based diabetes clinic after correcting these assumptions. RESEARCH DESIGN AND METHODSDiabetic patients (n = 12,074; 35,545 fundus examinations) were stratified into younger onset (YO; age at onset <30 years) or older onset (OO; age at onset ‡30 years), insulin treated (IT) or not IT (NIT), and with mild/more severe diabetic retinopathy (AnyDR) or moderate/more severe diabetic retinopathy (ModDR). The best-fitting equation correlating known duration among the OO-NIT group with the prevalence of ModDR was used to extrapolate time from appearance of retinopathy to diagnosis of type 2 diabetes. Time for retinopathy to develop after diabetes was calculated from the equation correlating the duration among the YO-IT group with appearance of ModDR. RESULTSThere were 1,719 patients in the OO-NIT group with AnyDR and 685 with ModDR and 756 in the YO-IT group with AnyDR and 385 with ModDR. A linear model showed ModDR appeared 2.66 years before diagnosis among those in the OO-NIT group. A quadratic model suggested that ModDR appeared 3.29 years after diagnosis among those in the YO-IT group. The resulting estimate was 6.05 years (2.66 + 3.29) between the onset and diagnosis of diabetes, compared with 13.36 years using standard criteria. CONCLUSIONSUsing best-fitting models and stratifying by glucose-lowering treatment and severity of retinopathy substantially lowers the estimated duration of undiagnosed type 2 diabetes.

No abstract

BackgroundChanges of volume status can be readily inferred from variations in diameter of the inferior vena cava (IVC) measured by ultrasound. However the effect of IVC changes following acute blood loss are not fully established. In this study, three different approaches to measuring IVC variables were compared in healthy blood donors, as a model of acute volume depletion, in order to establish their relative ability to detect acute blood loss.MethodsInspiratory and expiratory IVC diameters were measured before and after blood donation in hepatic long axis, hepatic short axis and renal short axis views using a 2–5 MHz curvilinear probe. All measurements were recorded and examined in real-time and post-processing sessions.ResultsAll windows performed satisfactorily but the renal window approach was feasible in only 30 out of 47 subjects. After blood donation, IVC diameters decreased in hepatic long axis, hepatic short axis and renal short axis (expiratory: −19.9, −18.0, −26.5 %; CI 95 %: 14.5–24.1; 13.1–22.9; 16.0–35.9, respectively) (inspiratory: −31.1, −31.6, −36.5 %; CI 95 %: 21.3–40.1; 18.8–45.2; 23.4–46.0, respectively), whereas the IVC collapsibility index increased by 21.6, 22.6 and 19.3 % (CI 95 %: 11.6–42.9; 18.5–39.5; 7.7–30.0). IVC diameters appeared to return to pre-donation values within 20 min but this was only detected by the hepatic long axis view.ConclusionsIVC diameter and collapsibility index variations, as measured in M mode, consistently detect volume changes after blood donation. The longitudinal mid-hepatic approach performed better by allowing a panoramic view, avoiding anatomical aberrancies at fixed points and permitting to identify the best possible perpendicular plane to the IVC. In addition, it was able to detect time-dependent physiological volume replacement. In contrast, in our hands, the renal window could not be visualized consistently well.

No abstract