Alain Junod

The relationship between the dose of intravenously administered streptozotocin (a N-nitroso derivative of glucosamine) and the diabetogenic response has been explored by use of the following indices of diabetogenic action: serum glucose, urine volume, and glycosuria, ketonuria, serum immunoreactive insulin (IRI), and pancreatic IRI content. Diabetogenic activity could be demonstrated between the doses of 25 and 100 mg/kg, all indices used showing some degree of correlation with the dose administered. Ketonuria was only seen with the largest dose, 100 mg/kg. The most striking and precise correlation was that between the dose and the pancreatic IRI content 24 hr after administration of the drug, and it is suggested that this represents a convenient test system either for both related and unrelated beta cytotoxic compounds or for screening for modifying agents or antidiabetic substances of a novel type. Ability to produce graded depletion of pancreatic IRI storage capacity led to an analysis of the relationship between pancreatic IRI content and deranged carbohydrate metabolism. Abnormal glucose tolerance and insulin response were seen when pancreatic IRI was depleted by about one-third, while fasting hyperglycemia and gross glycosuria occurred when the depletion had reached two-thirds and three-quarters, respectively. The mild yet persistent anomaly produced by the lowest effective streptozotocin dose, 25 mg/kg, exhibits characteristics resembling the state of chemical diabetes in humans and might thus warrant further study as a possible model. Finally, the loss of the diabetogenic action of streptozotocin by pretreatment with nicotinamide was confirmed and was shown to be a function of the relative doses of nicotinamide and streptozotocin and of the interval between injections.

OBJECTIVE: To develop a simple standardized clinical score to stratify emergency ward patients with clinically suspected pulmonary embolism (PE) into groups with a high, intermediate, or low probability of PE to improve and simplify the diagnostic approach. METHODS: Analysis of a database of 1090 consecutive patients admitted to the emergency ward for suspected PE in whom diagnosis of PE was ruled in or out by a standard diagnostic algorithm. Logistic regression was used to predict clinical parameters associated with PE. RESULTS: A total of 296 (27%) of 1090 patients were found to have PE. The optimal estimate of clinical probability was based on 8 variables: recent surgery, previous thromboembolic event, older age, hypocapnia, hypoxemia, tachycardia, band atelectasis, or elevation of a hemidiaphragm on chest x-ray film. A probability score was calculated by adding points assigned to these variables. A cutoff score of 4 best identified patients with low probability of PE. A total of 486 patients (49%) had a low clinical probability of PE (score </=4), of which 50 (10.3%) had a proven PE. The prevalence of PE was 38% in the 437 patients with an intermediate probability (score of 5-8; n = 437) and 81% in the 63 patients with a high probability (score >/=9). CONCLUSIONS: This clinical score, based on easily available and objective variables, provides a standardized assessment of the clinical probability of PE. Applying this score to emergency ward patients suspected of having PE could allow a more effective diagnostic process.

Reliable prediction of adverse outcomes in acute pulmonary embolism may help choose between in-hospital and ambulatory treatment. We aimed to identify predictors of adverse events in patients with pulmonary embolism and to generate a simple risk score for use in clinical settings. We prospectively followed 296 consecutive patients with pulmonary embolism admitted through the emergency ward. Logistic regression was used to predict death, recurrent thromboembolic event, or major bleeding at 3 months. Thirty patients (10.1%) had one or more adverse events during the 3-month follow-up period: 25 patients (8.4%) died, thromboembolic events recurred in 10 patients (3.4%), and major bleeding occurred in 5 patients (1.7%). Factors associated with an adverse outcome in multivariate analysis were cancer, heart failure, previous deep vein thrombosis, systolic blood pressure <100 mmHg, arterial PaO2 <8 kPa, and presence of deep vein thrombosis on ultrasound. A risk score was calculated by adding 2 points for cancer and hypotension, and 1 point each for the other predictors. A score of 2 best identified patients at risk of an adverse outcome in a receiver operating characteristic curve analysis. Of 180 low-risk patients (67.2%) (score < or =2), only 4 experienced an adverse outcome (2.2%), compared to 23 (26.1%) of 88 high-risk patients (score > or =3). A simple risk score based on easily available variables can accurately identify patients with pulmonary embolism at low risk of an adverse outcome. Such a score may be useful for selecting patients with pulmonary embolism eligible for outpatient care.

BACKGROUND: Helical computed tomography (CT) is commonly used to diagnose pulmonary embolism, although its operating characteristics have been insufficiently evaluated. OBJECTIVE: To assess the sensitivity and specificity of helical CT in suspected pulmonary embolism. DESIGN: Observational study. SETTING: Emergency department of a teaching and community hospital. PATIENTS: 299 patients with clinically suspected pulmonary embolism and a plasma D -dimer level greater than 500 microgram/L. INTERVENTION: Pulmonary embolism was established by using a validated algorithm that included clinical assessment, lower-limb compression ultrasonography, lung scanning, and pulmonary angiography. MEASUREMENTS: Sensitivity, specificity, and likelihood ratios of helical CT and interobserver agreement. Helical CT scans were withheld from clinicians and were read 3 months after acquisition by radiologists blinded to all clinical data. RESULTS: 118 patients (39%) had pulmonary embolism. In 12 patients (4%), 2 of whom had pulmonary embolism, results of helical CT were inconclusive. For patients with conclusive results, sensitivity of helical CT was 70% (95% CI, 62% to 78%) and specificity was 91% (CI, 86% to 95%). Interobserver agreement was high (kappa = 0.823 to 0.902). The false-negative rate was lower for helical CT used after initial negative results on ultrasonography than for helical CT alone (21% vs. 30%). Use of helical CT after normal results on initial ultrasonography and nondiagnostic results on lung scanning had a false-negative rate of only 5% and a false-positive rate of only 7%. CONCLUSION: Helical CT should not be used alone for suspected pulmonary embolism but could replace angiography in combined strategies that include ultrasonography and lung scanning.