scholarly journals One Size Fits All? Application of Susceptible-Dose-Dependent Breakpoints to Pediatric Patients and Laboratory Reporting

2019 ◽  
Vol 58 (1) ◽  
Author(s):  
Lindsey E. Nielsen ◽  
Jeanne B. Forrester ◽  
Jennifer Ellis Girotto ◽  
Aimee M. Dassner ◽  
Romney Humphries
Keyword(s):  
Clinical Outcome ◽  
Drug Exposure ◽  
Pediatric Patients ◽  
Treatment Success ◽  
Outcome Data ◽  
Drug Combinations ◽  
Clinical Outcome Data ◽  
Dose Dependent

ABSTRACT The Clinical and Laboratory Standards Institute antimicrobial and antifungal standards define a susceptible-dose-dependent (SDD) category for certain organisms and drug combinations. Reporting MICs within the SDD category suggests that treatment success is likely with increased drug exposure. These breakpoints are based on pharmacokinetic, pharmacodynamic, and clinical outcome data from adults and not pediatric patients. This commentary aims to discuss the implications of reporting SDD interpretations for pediatric patients and recommends laboratory reporting comments.

Increasing engagement with clinical outcome data

2011 ◽  
Vol 17 (12) ◽  
pp. 585-589
Author(s):  
Riaz Dharamshi ◽  
Toby Hillman ◽  
Rory Shaw
Keyword(s):  
Clinical Outcome ◽  
Outcome Data ◽  
Clinical Outcome Data

scholarly journals Association between duration of untreated bipolar disorder and clinical outcome: data from a Brazilian sample

2016 ◽  
Vol 38 (1) ◽  
pp. 6-10 ◽  
Author(s):  
Gustavo C. Medeiros ◽  
Sofia B. Senço ◽  
Beny Lafer ◽  
Karla M. Almeida
Keyword(s):  
Bipolar Disorder ◽  
Clinical Outcome ◽  
Outcome Data ◽  
Brazilian Sample ◽  
Clinical Outcome Data

scholarly journals Establishment and Use of Epidemiological Cutoff Values for Molds and Yeasts by Use of the Clinical and Laboratory Standards Institute M57 Standard

2017 ◽  
Vol 55 (5) ◽  
pp. 1262-1268 ◽  
Author(s):  
Shawn R. Lockhart ◽  
Mahmoud A. Ghannoum ◽  
Barbara D. Alexander
Keyword(s):  
Clinical Practice ◽  
Clinical Outcome ◽  
Antifungal Agent ◽  
Outcome Data ◽  
Fungal Isolate ◽  
Wild Type ◽  
Clinical Outcome Data ◽  
Cutoff Values

ABSTRACT Breakpoints are used to predict whether an antifungal agent will be clinically effective against a particular fungal isolate. They are based on a combination of MIC values, pharmacokinetic/pharmacodynamic values, and clinical outcome data. For many fungus-antifungal combinations, these data might never be available. For these combinations, epidemiological cutoff values (ECVs) provide a methodology for categorizing isolates as either wild type (WT) or non-WT. In this review, we define ECVs, explain how they are generated using the CLSI methodology in standard M57, and describe how they can be used in clinical practice.

scholarly journals Thrombolytic-Related Asymptomatic Hemorrhagic Transformation Does Not Deteriorate Clinical Outcome: Data from TIMS in China

PLoS ONE ◽  
2015 ◽  
Vol 10 (11) ◽  
pp. e0142381 ◽  
Author(s):  
Weihua Jia ◽  
Xiaoling Liao ◽  
Yuesong Pan ◽  
Yilong Wang ◽  
Tao Cui ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Hemorrhagic Transformation ◽  
Outcome Data ◽  
Clinical Outcome Data

WE-D-T-6E-07: Incorporating Clinical Outcome Data Into IMRT Inverse Planning

2005 ◽  
Vol 32 (6Part19) ◽  
pp. 2140-2140
Author(s):  
L Xing ◽  
Y Yang ◽  
B Widrow
Keyword(s):  
Clinical Outcome ◽  
Outcome Data ◽  
Inverse Planning ◽  
Clinical Outcome Data

Measuring outcomes for TC clients: Higher Ground Drug Rehabilitation Trust

2016 ◽  
Vol 37 (3) ◽  
pp. 121-130 ◽  
Author(s):  
Julian King ◽  
Johnny Dow ◽  
Brendan Stevenson
Keyword(s):  
Clinical Outcome ◽  
Psychological Health ◽  
Outcome Data ◽  
Control Group ◽  
Drug Rehabilitation ◽  
Post Discharge ◽  
Discharge Data ◽  
Content Type ◽  
Clinical Outcome Data

Purpose The purpose of this paper is to analyse the clinical outcome data collected as part of an 18-week, abstinence-based residential therapeutic community (TC) programme, Higher Ground Drug Rehabilitation Trust (Higher Ground) in New Zealand. Lessons and implications for routine collection of clinical outcome data are identified. Design/methodology/approach Higher Ground collects longitudinal data on all consenting clients using a battery of validated psychometric tools, with repeated measures at up to nine points in time from first presentation through to 12-month post-discharge follow up. Data analysis covered clients who entered Higher Ground between 1 July 2012 and 2 June 2015 (n=524). Findings Clients presented with histories of addiction which often had significant negative associations with their physical and psychological health, their relationships, work, accommodation and criminal behaviour. By the time they exited the programme, clinically and statistically significant improvements were seen across multiple indicators including: substance use and abstinence; symptoms of post-traumatic stress disorder, depression, anxiety and stress; and a range of social indicators. Research limitations/implications Attrition in follow-up research is a significant challenge, with people completing the TC programme being more likely to participate than those who do not. This limits generalizability in post-discharge data. There was no control group, making causal attribution a challenge. Identifying suitable benchmarks from the literature is challenging because of the variety of outcome measures and research methodologies used. Practical implications Tracking client outcomes longitudinally using psychometric tools is potentially valuable for TCs and their funding bodies, as it provides insights into patterns of client recovery that can inform ongoing service improvements and resource allocation decisions. However, significant challenges remain. Originality/value The study demonstrates the value, and practical challenges, of collecting high-quality outcome data in a TC setting.

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