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  • 1
    In: Journal of Diabetes, Wiley, Vol. 8, No. 1 ( 2016-01), p. 148-157
    Abstract: 自我监测血糖(Self‐monitoring of blood glucose,SMBG)是一种被用来检测与预防糖尿病患者出现低血糖的方法。然而,目前基于SMBG的与低血糖相关的随时间变化的餐前与餐后血糖波动信息的纵向测量(轨迹)信息还十分有限。在每周1次使用艾塞那肽(exenatide once weekly,EQW)或者甘精胰岛素(insulin glargine,IG)治疗的患者中,这项研究比较了治疗期间出现过低血糖与未出现过低血糖患者的超过52周的SMBG特征曲线。 方法 分析所用的数据来源于3项对照试验,汇总了在52周中使用EQW( n = 531)或者IG( n = 219)治疗后患者水平的纵向数据。 结果 在EQW组与IG组中至少出现1次低血糖事件的患者比例分别为23%与54%。与未出现过低血糖的患者相比,在两个治疗组中出现过低血糖的患者的餐前血糖SMBG测量值都显著更低。与未出现过低血糖的患者相比,出现过低血糖的患者在超过52周的治疗期间平均餐前血糖水平都显著更低,在EQW组与IG组中分别低了0.64与0.66 mmol/L(二组均 P 〈 0.01)。在两个治疗组中,出现过低血糖与未出现过低血糖的患者之间的平均餐后血糖水平都没有显著性差异。在出现过低血糖的患者中,与IG组相比,EQW组的平均早餐前血糖轨迹高出了0.48 mmol/L。 结论 这项研究的结果显示,出现过低血糖与未出现过低血糖的患者之间的餐前以及餐后血糖特征都具有不同的轨迹。然而,使用EQW与IG治疗的患者之间的SMBG轨迹是相似的。
    Type of Medium: Online Resource
    ISSN: 1753-0393 , 1753-0407
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2016
    detail.hit.zdb_id: 2485432-3
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  • 2
    Online Resource
    Online Resource
    Bentham Science Publishers Ltd. ; 2017
    In:  The Open Bioinformatics Journal Vol. 10, No. 1 ( 2017-12-12), p. 16-27
    In: The Open Bioinformatics Journal, Bentham Science Publishers Ltd., Vol. 10, No. 1 ( 2017-12-12), p. 16-27
    Abstract: Identification of diseased patients from primary care based electronic medical records (EMRs) has methodological challenges that may impact epidemiologic inferences. Objective: To compare deterministic clinically guided selection algorithms with probabilistic machine learning (ML) methodologies for their ability to identify patients with type 2 diabetes mellitus (T2DM) from large population based EMRs from nationally representative primary care database. Methods: Four cohorts of patients with T2DM were defined by deterministic approach based on disease codes. The database was mined for a set of best predictors of T2DM and the performance of six ML algorithms were compared based on cross-validated true positive rate, true negative rate, and area under receiver operating characteristic curve. Results: In the database of 11,018,025 research suitable individuals, 379 657 (3.4%) were coded to have T2DM. Logistic Regression classifier was selected as best ML algorithm and resulted in a cohort of 383,330 patients with potential T2DM. Eighty-three percent (83%) of this cohort had a T2DM code, and 16% of the patients with T2DM code were not included in this ML cohort. Of those in the ML cohort without disease code, 52% had at least one measure of elevated glucose level and 22% had received at least one prescription for antidiabetic medication. Conclusion: Deterministic cohort selection based on disease coding potentially introduces significant mis-classification problem. ML techniques allow testing for potential disease predictors, and under meaningful data input, are able to identify diseased cohorts in a holistic way.
    Type of Medium: Online Resource
    ISSN: 1875-0362
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2017
    detail.hit.zdb_id: 2413371-1
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  • 3
    In: Clinical Infectious Diseases, Oxford University Press (OUP), Vol. 72, No. 8 ( 2021-04-26), p. 1369-1378
    Abstract: The optimal dosing of antibiotics in critically ill patients receiving renal replacement therapy (RRT) remains unclear. In this study, we describe the variability in RRT techniques and antibiotic dosing in critically ill patients receiving RRT and relate observed trough antibiotic concentrations to optimal targets. Methods We performed a prospective, observational, multinational, pharmacokinetic study in 29 intensive care units from 14 countries. We collected demographic, clinical, and RRT data. We measured trough antibiotic concentrations of meropenem, piperacillin-tazobactam, and vancomycin and related them to high- and low-target trough concentrations. Results We studied 381 patients and obtained 508 trough antibiotic concentrations. There was wide variability (4–8-fold) in antibiotic dosing regimens, RRT prescription, and estimated endogenous renal function. The overall median estimated total renal clearance (eTRCL) was 50 mL/minute (interquartile range [IQR], 35–65) and higher eTRCL was associated with lower trough concentrations for all antibiotics (P & lt; .05). The median (IQR) trough concentration for meropenem was 12.1 mg/L (7.9–18.8), piperacillin was 78.6 mg/L (49.5–127.3), tazobactam was 9.5 mg/L (6.3–14.2), and vancomycin was 14.3 mg/L (11.6–21.8). Trough concentrations failed to meet optimal higher limits in 26%, 36%, and 72% and optimal lower limits in 4%, 4%, and 55% of patients for meropenem, piperacillin, and vancomycin, respectively. Conclusions In critically ill patients treated with RRT, antibiotic dosing regimens, RRT prescription, and eTRCL varied markedly and resulted in highly variable antibiotic concentrations that failed to meet therapeutic targets in many patients.
    Type of Medium: Online Resource
    ISSN: 1058-4838 , 1537-6591
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2002229-3
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