Usefulness of clinical risk markers and ischemic threshold to stratify risk in patients undergoing major noncardiac surgery

The risk of cardiac events in patients undergoing major noncardiac surgery is dependent on their clinical characteristics and the results of stress testing. The purpose of this study was to develop a composite approach to defining levels of risk and to examine whether different approaches to prophylaxis influenced this prediction of outcome. One hundred forty-five consecutive patients (aged 68 +/- 9 years, 79 men) with >1 clinical risk variable were studied with standard dobutamine-atropine stress echo before major noncardiac surgery. Risk levels were stratified according to the presence of ischemia (new or worsening wall motion abnormality), ischemic threshold (heart rate at development of ischemia), and number of clinical risk variables. Patients were followed for perioperative events (during hospital admission) and death or infarction over the subsequent 16 10 months. Ten perioperative events occurred in 105 patients who proceeded to surgery (10%, 95% confidence interval [CI] 5% to 17%), 40 being cancelled because of cardiac or other risk. No ischemia was identified in 56 patients, 1 of whom (1.8%) had a perioperative infarction. Of the 49 patients with ischemia, 22 (45%) had 1 or 2 clinical risk factors; 2 (9%, 95% CI 1% to 29%) had events. Another 15 patients had a high ischemic threshold and 3 or 4 risk factors; 3 (20%, 95% Cl 4% to 48%) had events. Twelve patients had a low ischemic threshold and 3 or 4 risk factors; 4 (33%, 95% CI 10% to 65%) had events. Preoperative myocardial revascularization was performed in only 3 patients, none of whom had events. Perioperative and long-term events occurred despite the use of beta blockers; 7 of 41 eta blocker-treated patients had a perioperative event (17%, 95% CI 7% to 32%); these treated patients were at higher anticipated risk than untreated patients (20 +/- 24% vs 10 +/- 19%, p = 0.02). The total event rate over late follow-up was 13%, and was predicted by dobutamine-atropine stress echo results and heart rate response. (C) 2002 by Excerpta Medica, Inc.

Myocardial infarction and type II diabetes - preferential treatment for high risk patients?

Objectives: To compare variability of blood glucose concentration in patients with type II diabetes with (cases) and without (controls) myocardial infarction. A secondary objective was identification of predictive factors for higher blood glucose on discharge from hospital. Design: A retrospective matched case-control study. Participants: Medical notes of 101 type II diabetic patients admitted with a myocardial infarction (MI) and 101 type II diabetic patients (controls) matched on gender and age with no MI were reviewed. Blood glucose concentrations over two consecutive 48-h periods were collected. Demographic data and therapy on admission/discharge were also collected. Results: Patient characteristics were comparable on recruitment excluding family history of cardiovascular disease (P =0.003), dyslipidaemia (P =0.004) and previous history of MI (P =0.007). Variability of blood glucose in cases was greater over the first 48 h compared with the second 48 h (P =0.03), and greater when compared with controls over the first 48 h (P =0.01). Cases with blood glucose on discharge >8.2 mmol / L (n =45) were less likely to have a history of previous MI (P =0.04), ischaemic heart disease (P =0.03) or hypertension (P =0.02). Conclusions: Type II diabetics with an MI have higher and more variable blood glucose concentrations during the first 48 h of admission. Only cardiovascular 'high risk' patients had target blood glucose set on discharge. The desirability of all MI patients with diabetes, having standardized-glucose infusions to reduce variability of blood glucose, should be evaluated in a randomized controlled trial.

Impact numbers: measures of risk factor impact on the whole population from case-control and cohort studies

Objective: To describe new measures of risk from case-control and cohort studies, which are simple to understand and relate to numbers of the population at risk. Design: Theoretical development of new measures of risk. Setting: Review of literature and previously described measures. Main results: The new measures are: (1) the population impact number (PIN), the number of those in the whole population among whom one case is attributable to the exposure or risk factor (this is equivalent to the reciprocal of the population attributable risk),- (2) the case impact number (CIN) the number of people with the disease or outcome for whom one case will be attributable to the exposure or risk factor (this is equivalent to the reciprocal of the population attributable fraction); (3) the exposure impact number (EIN) the number of people with the exposure among whom one excess case is attributable to the exposure (this is equivalent to the reciprocal of the attributable risk); (4) the exposed cases impact number (ECIN) the number of exposed cases among whom one case is attributable to the exposure (this is equivalent to the reciprocal of the aetiological fraction). The impact number reflects the number of people in each population (the whole population, the cases, all those exposed, and the exposed cases) among whom one case is attributable to the particular risk factor. Conclusions: These new measures should help communicate the impact on a population, of estimates of risk derived from cohort or case-control studies.

Risk and protective factors for depressive symptomatology among a community sample of adolescents and young adults

Objectives: The study explores the risk and protective factors for current depressive symptomatology in a large community sample of 15-to-24-year-olds. Methods: The study was designed as a cross-sectional household survey, which used telephone recruitment followed by an anonymous self-report postal questionnaire. The final sample included 3,082 adolescents and young adults from Queensland, Australia. Results: The vast majority of measured risk and protective factors were associated with current depressive symptomatology. Key risk factors included high levels of neuroticism, perceived problems with parents, sexual abuse, relationship breakups, educational failure and sexual identity conflict. A different profile of protective factors was evident for each of these high-risk groups. Of particular note was the importance of well-developed intrapersonal skills as protective for both males and females. The significance of social connectedness as a protective factor for the males overall and across a range of high-risk groups was a central finding. Conclusions and implications: The implications of these findings in relation to a range of mental health promotion and mental illness prevention and early intervention initiatives are discussed. Supported initiatives include parenting programs that consider the realities of modern families, increasing community awareness of the impact on young people of the breakdown of their intimate relationships, initiatives in educational settings and workplaces to increase tolerance of gay/lesbian and bisexual lifestyles and the enhancement of social connectedness.

Risk factors for non-haemorrhagic stroke in patients with coronary heart disease and the effect of lipid-modifying therapy with pravastatin

Objective To determine the relative importance of recognised risk factors for non-haemorrhagic stroke, including serum cholesterol and the effect of cholesterol-lowering therapy, on the occurrence of non-haemorrhagic stroke in patients enrolled in the LIPID (Long-term Intervention with Pravastatin in Ischaemic Disease) study. Design The LIPID study was a placebo-controlled, double-blind trial of the efficacy on coronary heart disease mortality of pravastatin therapy over 6 years in 9014 patients with previous acute coronary syndromes and baseline total cholesterol of 4-7 mmol/l. Following identification of patients who had suffered non-haemorrhagic stroke, a pre-specified secondary end point, multivariate Cox regression was used to determine risk in the total population. Time-to-event analysis was used to determine the effect of pravastatin therapy on the rate of non-haemorrhagic stroke. Results There were 388 non-haemorrhagic strokes in 350 patients. Factors conferring risk of future non-haemorrhagic stroke were age, atrial fibrillation, prior stroke, diabetes, hypertension, systolic blood pressure, cigarette smoking, body mass index, male sex and creatinine clearance. Baseline lipids did not predict non-haemorrhagic stroke. Treatment with pravastatin reduced non-haemorrhagic stroke by 23% (P= 0.016) when considered alone, and 21% (P= 0.024) after adjustment for other risk factors. Conclusions The study confirmed the variety of risk factors for non-haemorrhagic stroke. From the risk predictors, a simple prognostic index was created for nonhaemorrhagic stroke to identify a group of patients at high risk. Treatment with pravastatin resulted in significant additional benefit after allowance for risk factors. (C) 2002 Lippincott Williams Wilkins.