SUMMARY Background Craniotomy, when evaluated in trials, does not improve outcome after intracerebral haemorrhage (ICH). Whether minimally invasive catheter evacuation followed by thrombolysis is safe and can achieve a good functional outcome by removing clot is unknown. We investigated safety and efficacy of alteplase with minimally invasive surgery (MIS) in patients with intracerebral haemorrhage. Methods MISTIE was an international, randomized, open-label study and was done in 26 hospitals in the USA, Canada, the UK, and Germany. Patients (aged 18–80 years), with non-traumatic (spontaneous) ICH ≥20 mL were randomly allocated, centrally, to medical care or image-guided MIS plus rt-PA (0.3 mg or 1.0 mg every 8 hours for up to 9 doses) to remove clot using surgical aspiration followed with alteplase clot irrigation. The primary efficacy outcome was the adjusted dichotomized modified Rankin Scale (mRS) 0–3 vs 4–6 assessed at day 180 after symptom onset. Analysis was by intention to treat. (ClinicalTrials.gov number NCT00224770). Findings Between February 2, 2006 and April 8, 2013, 96 subjects were randomized and completed follow-up: 54 received treatment and 42 medical care. Primary safety outcomes: mortality, symptomatic bleeding, brain infections, as well as withdrawal of care, did not differ between groups. Asymptomatic hemorrhages were more common in the surgical group (3 (7%) vs. 12 (22%) p= 0.05) producing a difference of 15.1% (95% CI: 1.5% to 28.6%). The estimated absolute benefit, i.e., the unadjusted difference in observed proportions of all subjects with mRS 0–3 (33% vs 21%) at 180 days comparing MISPA vs. medical control, is 0.109 [95%CI: −0.088, 0.294; p=0.26], and is 0.162 [95%CI: 0.003, 0.323; p=0.05] after adjustment for potential imbalances in baseline severity between study arms (primary efficacy outcome). Interpretation MIS+rt-PA appears safe with an apparent advantage of better functional outcome at 180 days. Increased asymptomatic bleeding is a major cautionary finding. The MISTIE trial results, if replicable, could produce a meaningful functional benefit adding surgical management as a therapeutic strategy for ICH. Funding National Institute of Neurologic Disorders and Stroke, Genentech, and Codman.

The critical deterioration rate is a valid, pragmatic proximate outcome associated with in-hospital mortality. It has great potential for complementing existing patient safety measures for evaluating RRS performance.

IMPORTANCE Patient-generated health data captured from smartphone sensors have the potential to better quantify the physical outcomes of surgery. The ability of these data to discriminate between postoperative trends in physical activity remains unknown. OBJECTIVE To assess whether physical activity captured from smartphone accelerometer data can be used to describe postoperative recovery among patients undergoing cancer operations. DESIGN, SETTING, AND PARTICIPANTS This prospective observational cohort study was conducted from July 2017 to April 2019 in a single academic tertiary care hospital in the United States. Preoperatively, adults (age Ն18 years) who spoke English and were undergoing elective operations for skin, soft tissue, head, neck, and abdominal cancers were approached. Patients were excluded if they did not own a smartphone. EXPOSURES Study participants downloaded an application that collected smartphone accelerometer data continuously for 1 week preoperatively and 6 months postoperatively. MAIN OUTCOMES AND MEASURES The primary end points were trends in daily exertional activity and the ability to achieve at least 60 minutes of daily exertional activity after surgery among patients with vs without a clinically significant postoperative event. Postoperative events were defined as complications, emergency department presentations, readmissions, reoperations, and mortality. RESULTS A total of 139 individuals were approached. In the 62 enrolled patients, who were followed up for a median (interquartile range [IQR]) of 147 (77-179) days, there were no preprocedural differences between patients with vs without a postoperative event. Seventeen patients (27%) experienced a postoperative event. These patients had longer operations than those without a postoperative event (median [IQR], 225 [152-402] minutes vs 107 [68-174] minutes; P < .001), as well as greater blood loss (median [IQR], 200 [35-515] mL vs 25 [5-100] mL; P = .006) and more follow-up visits (median [IQR], 2 [2-4] visits vs 1 [1-2] visits; P = .002). Compared with mean baseline daily exertional activity, patients with a postoperative event had lower activity at week 1

The primary analysis in many randomized controlled trials focuses on the average treatment e↵ect and does not address whether treatment benefits are widespread or limited to a select few. This problem a↵ects many disease areas, since it stems from how randomized trials, often the gold standard for evaluating treatments, are designed and analyzed. Our goal is to learn about the fraction who benefit from a treatment, based on randomized trial data. We consider the case where the outcome is ordinal, with binary outcomes as a special case. In general, the fraction who benefit is a non-identifiable parameter, and the best that can be obtained are sharp lower and upper bounds on it. Our main contributions include (i) showing that the naive (plugin) estimator of the bounds can be inconsistent, in the case that support restrictions are made on the joint distribution of the potential outcomes (such as the no harm assumption); (ii) developing the first consistent estimator for this case; (iii) applying this estimator to a randomized trial dataset of a medical treatment to determine whether the estimates can be informative. Our estimator is computed using linear programming, allowing fast implementation. R and MATLAB software are provided (https://github.com/emhuang1/fraction-who-benefit).

The ubiquity of personal digital devices offers unprecedented opportunities to study human behavior. Current state-of-the-art methods quantify physical activity using “activity counts,” a measure which overlooks specific types of physical activities. We propose a walking recognition method for sub-second tri-axial accelerometer data, in which activity classification is based on the inherent features of walking: intensity, periodicity, and duration. We validate our method against 20 publicly available, annotated datasets on walking activity data collected at various body locations (thigh, waist, chest, arm, wrist). We demonstrate that our method can estimate walking periods with high sensitivity and specificity: average sensitivity ranged between 0.92 and 0.97 across various body locations, and average specificity for common daily activities was typically above 0.95. We also assess the method’s algorithmic fairness to demographic and anthropometric variables and measurement contexts (body location, environment). Finally, we release our method as open-source software in Python and MATLAB.