We determined the relationship between secondary insults (hypoxia, hypotension, and hypothermia) occurring prior to or on admission to hospital and 6-month outcome after traumatic brain injury (TBI). A meta-analysis of individual patient data, from seven Phase III randomized clinical trials (RCT) in moderate or severe TBI and three TBI population-based series, was performed to model outcome as measured by the Glasgow Outcome Scale (GOS). Proportional odds modeling was used to relate the probability of a poor outcome to hypoxia (N = 5661), hypotension ( N = 6629), and hypothermia ( N = 4195) separately. We additionally analyzed the combined effects of hypoxia and hypotension and performed exploratory analysis of associations with computerized tomography (CT) classification and month of injury. Having a pre-enrollment insult of hypoxia, hypotension or hypothermia is strongly associated with a poorer outcome (odds ratios of 2.1 95% CI [1.7-2.6], 2.7 95% CI [2.1-3.4], and 2.2 95% CI [1.6-3.2], respectively). Patients with both hypoxia and hypotension had poorer outcomes than those with either insult alone. Radiological signs of raised intracranial pressure (CT class III or IV) were more frequent in patients who had sustained hypoxia or hypotension. A significant association was observed between month of injury and hypothermia. The occurrence of secondary insults prior to or on admission to hospital in TBI patients is strongly related to poorer outcome and should therefore be a priority for emergency department personnel.

The incidence of postoperative desaturation, respiratory failure, postoperative cardiac events, and ICU transfers was higher in patients with OSA.

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Aims Statin intolerance (SI) represents a significant public health problem for which precise estimates of prevalence are needed. Statin intolerance remains an important clinical challenge, and it is associated with an increased risk of cardiovascular events. This meta-analysis estimates the overall prevalence of SI, the prevalence according to different diagnostic criteria and in different disease settings, and identifies possible risk factors/conditions that might increase the risk of SI. Methods and results We searched several databases up to 31 May 2021, for studies that reported the prevalence of SI. The primary endpoint was overall prevalence and prevalence according to a range of diagnostic criteria [National Lipid Association (NLA), International Lipid Expert Panel (ILEP), and European Atherosclerosis Society (EAS)] and in different disease settings. The secondary endpoint was to identify possible risk factors for SI. A random-effects model was applied to estimate the overall pooled prevalence. A total of 176 studies [112 randomized controlled trials (RCTs); 64 cohort studies] with 4 143 517 patients were ultimately included in the analysis. The overall prevalence of SI was 9.1% (95% confidence interval 8.0–10%). The prevalence was similar when defined using NLA, ILEP, and EAS criteria [7.0% (6.0–8.0%), 6.7% (5.0–8.0%), 5.9% (4.0–7.0%), respectively]. The prevalence of SI in RCTs was significantly lower compared with cohort studies [4.9% (4.0–6.0%) vs. 17% (14–19%)]. The prevalence of SI in studies including both primary and secondary prevention patients was much higher than when primary or secondary prevention patients were analysed separately [18% (14–21%), 8.2% (6.0–10%), 9.1% (6.0–11%), respectively]. Statin lipid solubility did not affect the prevalence of SI [4.0% (2.0–5.0%) vs. 5.0% (4.0–6.0%)]. Age [odds ratio (OR) 1.33, P = 0.04], female gender (OR 1.47, P = 0.007), Asian and Black race (P < 0.05 for both), obesity (OR 1.30, P = 0.02), diabetes mellitus (OR 1.26, P = 0.02), hypothyroidism (OR 1.37, P = 0.01), chronic liver, and renal failure (P < 0.05 for both) were significantly associated with SI in the meta-regression model. Antiarrhythmic agents, calcium channel blockers, alcohol use, and increased statin dose were also associated with a higher risk of SI. Conclusion Based on the present analysis of >4 million patients, the prevalence of SI is low when diagnosed according to international definitions. These results support the concept that the prevalence of complete SI might often be overestimated and highlight the need for the careful assessment of patients with potential symptoms related to SI. Key question What is the overall prevalence of statin intolerance (SI) worldwide? What are the main risk factors of SI? Key finding The overall prevalence of SI is 9.1% and even lower using the international definitions: National Lipid Association, International Lipid Expert Panel, European Atherosclerosis Society (7.0, 6.7, 5.9%). Female gender, hypothyroidism, high statin dose, advanced age, antiarrhythmics, and obesity are the main factors that increase the risk of SI. Take-home message Clinicians should use these results to encourage adherence to statin therapy in the patients they treat.

The aim of this study was to quantify the potential reduction in sample size that can be achieved by adjustment for predictors of outcome in traumatic brain injury (TBI) trials. We used individual patient data from seven therapeutic phase III randomized clinical trials (RCTs; n = 6166) in moderate or severe TBI, and three TBI surveys (n = 2238). The primary outcome was the dichotomized Glasgow Outcome Scale at 6 months (favorable/unfavorable). Baseline predictors of outcome considered were age, motor score, pupillary reactivity, computed tomography (CT) classification, traumatic subarachnoid hemorrhage, hypoxia, hypotension, glycemia, and hemoglobin. We calculated the potential sample size reduction obtained by adjustment of a hypothetical treatment effect for one to seven predictors with logistic regression models. The distribution of predictors was more heterogeneous in surveys than in trials. Adjustment of the treatment effect for the strongest predictors (age, motor score, and pupillary reactivity) yielded a reduction in sample size of 16-23% in RCTs and 28-35% in surveys. Adjustment for seven predictors yielded a reduction of about 25% in most studies: 20-28% in RCTs and 32-39% in surveys. A major reduction in sample size can be obtained with covariate adjustment in TBI trials. Covariate adjustment for strong predictors should be incorporated in the analysis of future TBI trials.