PubMed · 13201689
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J C STANLEY. 1954. Gellerman's complex crossover design.. https://doi.org/10.1037/h0056096
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OBJECTIVES: This study sought to test whether insulin improves exercise ventilatory efficiency (VE/VCO2 slope) and oxygen uptake at peak exercise (peak VO2) in patients with type 2 diabetes-heart failure (HF) comorbidity. BACKGROUND: In type 2 diabetes-HF comorbidity, depression of alveolar-capillary diffusion (DL(CO)) correlates with deterioration of exercise VE/VCO2 slope and peak VO2. Insulin potentiates DL(CO) in these patients. METHODS: Exercise ventilatory efficiency and peak VO2 (cycle ergometry ramp protocol), as well as DL(CO) at rest and its subdivisions (membrane conductance [D(M)] and pulmonary capillary blood volume [V(C)]) were assessed in 18 patients with type 2 diabetes-HF comorbidity at baseline and after 50 ml of saline + regular insulin (10 IU), or saline, was infused on consecutive days, according to a random crossover design. Glycemia was kept at pre-insulin level for the experiment duration. RESULTS: Baseline DL(CO), D(M), peak VO2, and VE/VCO2 slope were compromised in these patients. At measurements performed in the 60 min after infusions, compared with at baseline, saline was ineffective, whereas insulin augmented peak VO2 (+13.5%) and lowered VE/VCO(2) slope (-18%), and also increased time to anaerobic threshold (+29.4%), maximal O2 pulse (+12.3%), aerobic efficiency (+21.2%), DL(CO) (+12.5%), and D(M) (+21.6%), despite a reduction in V(C) (-16.3%); insulin did not vary cardiac index and ejection fraction at rest. Changes in peak VO2 and VE/VCO2 slope (r = 0.67, p = 0.002; r = -0.73, p < 0.001, respectively) correlated with those in DL(CO). These responses were unrelated to glycohemoglobin and baseline fasting blood sugar. They were persistent at 6 h after insulin infusion, and were undetectable at 24 h. CONCLUSIONS: In diabetes-HF comorbidity, insulin causes a prolonged improvement in physical performance through activation of multiple factors, among which facilitation of gas conductance seems to be predominant.
OBJECTIVE: The aim of this study was to determine the effect that the computer interpretation (CI) of electrocardiograms (EKGs) has on the accuracy of resident (noncardiologist) physicians reading EKGs. DESIGN: A randomized, controlled trial was conducted in a laboratory setting from February through June 2001, using a two-period crossover design with matched pairs of subjects randomly assigned to sequencing groups. MEASUREMENTS: Subjects' interpretive accuracy of discrete, cardiologist-determined EKG findings were measured as judged by a board-certified internist. RESULTS: Without the CI, subjects interpreted 48.9% (95% confidence interval, 45.0% to 52.8%) of the findings correctly. With the CI, subjects interpreted 55.4% (51.9% to 58.9%) correctly (p < 0.0001). When the CIs that agreed with the gold standard (Correct CIs) were not included, 53.1% (47.7% to 58.5%) of the findings were interpreted correctly. When the correct CI was included, accuracy increased to 68.1% (63.2% to 72.7%; p < 0.0001). When computer advice that did not agree with the gold standard (Incorrect CI) was not provided to the subjects, 56.7% (48.5% to 64.5%) of findings were interpreted correctly. Accuracy dropped to 48.3% (40.4% to 56.4%) when the incorrect computer advice was provided (p = 0.131). Subjects erroneously agreed with the incorrect CI more often when it was presented with the EKG 67.7% (57.2% to 76.7%) than when it was not 34.6% (23.8% to 47.3%; p < 0.0001). CONCLUSIONS: Computer decision support systems can generally improve the interpretive accuracy of internal medicine residents in reading EKGs. However, subjects were influenced significantly by incorrect advice, which tempers the overall usefulness of computer-generated advice in this and perhaps other areas.
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