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Idy Tam - One of the best experts on this subject based on the ideXlab platform.

  • skin tape stripping identifies gene transcript signature associated with allergic contact dermatitis
    Contact Dermatitis, 2021
    Co-Authors: Idy Tam, Kathryn R Hill, Jin Mo Park
    Abstract:

    Background Allergic contact dermatitis (ACD) and irritant contact dermatitis (ICD) are common skin conditions with an overlapping clinical and histological appearance, but distinct underlying mechanisms. Patch testing is the gold standard for ACD diagnosis, yet the interpretation of its results may be confounded by weak and varying macroscopic reactions. Objective To examine whether gene transcript profiling of RNA sampled from patch tested patient skin by tape stripping (TS) could differentiate ACD from ICD and the baseline skin state (control) METHODS: Nine patients (seven females, two males; mean age 38.6 years, range 24-72 years) with confirmed ACD through patch testing were recruited. Total RNA was isolated from TS samples and relative transcript abundance was determined by quantitative real-time polymeraise chain reaction using 39 gene-specific primers. Results TS captured gene transcripts derived from diverse skin cell types, including not only keratinocytes, but also epidermal and dermal antigen-presenting cells. Among the genes analysed in transcript profiling, genes encoding epidermal barrier components and inflammatory mediators exhibited changes in transcript abundance in ACD skin compared to ICD or control skin. Conclusions Our findings reveal the potential of skin TS for non-invasive biopsy during patch testing and molecular marker-based ACD diagnosis.

  • skin tape stripping identifies gene transcript signature associated with allergic contact dermatitis
    Contact Dermatitis, 2020
    Co-Authors: Idy Tam, Kathryn R Hill, Jin Mo Park
    Abstract:

    BACKGROUND Allergic contact dermatitis (ACD) and irritant contact dermatitis (ICD) are common skin conditions with overlapping clinical and histologic appearance but distinct underlying mechanisms. Patch testing is the gold standard for ACD diagnosis, yet the interpretation of its results may be confounded by weak and varying macroscopic reactions. OBJECTIVE To examine whether gene transcript profiling of RNA sampled from patch-tested patient skin by tape stripping (TS) could differentiate ACD from ICD and the baseline skin state (control; CON). METHODS Nine patients (7 females and 2 males; age 24-72 [mean 38.6]) with confirmed ACD through patch testing were recruited. Total RNA was isolated from TS samples and relative transcript abundance was determined by quantitative real-time PCR using 39 gene-specific primers. RESULTS TS captured gene transcripts derived from diverse skin cell types including not only keratinocytes but also epidermal and dermal antigen-presenting cells. Among the genes analysed in transcript profiling, genes encoding epidermal barrier components and inflammatory mediators exhibited changes in transcript abundance in ACD skin compared to ICD or CON skin. CONCLUSIONS Our findings reveal the potential of skin TS for non-invasive biopsy during patch testing and molecular marker-based ACD diagnosis. This article is protected by copyright. All rights reserved.

Jin Mo Park - One of the best experts on this subject based on the ideXlab platform.

  • skin tape stripping identifies gene transcript signature associated with allergic contact dermatitis
    Contact Dermatitis, 2021
    Co-Authors: Idy Tam, Kathryn R Hill, Jin Mo Park
    Abstract:

    Background Allergic contact dermatitis (ACD) and irritant contact dermatitis (ICD) are common skin conditions with an overlapping clinical and histological appearance, but distinct underlying mechanisms. Patch testing is the gold standard for ACD diagnosis, yet the interpretation of its results may be confounded by weak and varying macroscopic reactions. Objective To examine whether gene transcript profiling of RNA sampled from patch tested patient skin by tape stripping (TS) could differentiate ACD from ICD and the baseline skin state (control) METHODS: Nine patients (seven females, two males; mean age 38.6 years, range 24-72 years) with confirmed ACD through patch testing were recruited. Total RNA was isolated from TS samples and relative transcript abundance was determined by quantitative real-time polymeraise chain reaction using 39 gene-specific primers. Results TS captured gene transcripts derived from diverse skin cell types, including not only keratinocytes, but also epidermal and dermal antigen-presenting cells. Among the genes analysed in transcript profiling, genes encoding epidermal barrier components and inflammatory mediators exhibited changes in transcript abundance in ACD skin compared to ICD or control skin. Conclusions Our findings reveal the potential of skin TS for non-invasive biopsy during patch testing and molecular marker-based ACD diagnosis.

  • skin tape stripping identifies gene transcript signature associated with allergic contact dermatitis
    Contact Dermatitis, 2020
    Co-Authors: Idy Tam, Kathryn R Hill, Jin Mo Park
    Abstract:

    BACKGROUND Allergic contact dermatitis (ACD) and irritant contact dermatitis (ICD) are common skin conditions with overlapping clinical and histologic appearance but distinct underlying mechanisms. Patch testing is the gold standard for ACD diagnosis, yet the interpretation of its results may be confounded by weak and varying macroscopic reactions. OBJECTIVE To examine whether gene transcript profiling of RNA sampled from patch-tested patient skin by tape stripping (TS) could differentiate ACD from ICD and the baseline skin state (control; CON). METHODS Nine patients (7 females and 2 males; age 24-72 [mean 38.6]) with confirmed ACD through patch testing were recruited. Total RNA was isolated from TS samples and relative transcript abundance was determined by quantitative real-time PCR using 39 gene-specific primers. RESULTS TS captured gene transcripts derived from diverse skin cell types including not only keratinocytes but also epidermal and dermal antigen-presenting cells. Among the genes analysed in transcript profiling, genes encoding epidermal barrier components and inflammatory mediators exhibited changes in transcript abundance in ACD skin compared to ICD or CON skin. CONCLUSIONS Our findings reveal the potential of skin TS for non-invasive biopsy during patch testing and molecular marker-based ACD diagnosis. This article is protected by copyright. All rights reserved.

Hude Quan - One of the best experts on this subject based on the ideXlab platform.

  • systematic review and assessment of validated case definitions for depression in administrative data
    BMC Psychiatry, 2014
    Co-Authors: Hude Quan, Nathalie Jette, Cynthia A Beck, Kirsten M Fiest, Christine St Germainesmith, Amy Metcalfe, Scott B Patten
    Abstract:

    Administrative data are increasingly used to conduct research on depression and inform health services and health policy. Depression surveillance using administrative data is an alternative to surveys, which can be more resource-intensive. The objectives of this study were to: (1) systematically review the literature on validated case definitions to identify depression using International Classification of Disease and Related Health Problems (ICD) codes in administrative data and (2) identify individuals with and without depression in administrative data and develop an enhanced case definition to identify persons with depression in ICD-coded hospital data. (1) Systematic review: We identified validation studies using ICD codes to indicate depression in administrative data up to January 2013. (2) Validation: All depression case definitions from the literature and an additional three ICD-9-CM and three ICD-10 enhanced definitions were tested in an inpatient database. The diagnostic accuracy of all case definitions was calculated [sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV)]. (1) Systematic review: Of 2,014 abstracts identified, 36 underwent full-text review and three met eligibility criteria. These depression studies used ICD-9 and ICD-10 case definitions. (2) Validation: 4,008 randomly selected medical charts were reviewed to assess the performance of new and previously published depression-related ICD case definitions. All newly tested case definitions resulted in Sp >99%, PPV >89% and NPV >91%. Sensitivities were low (28-35%), but higher than for case definitions identified in the literature (1.1-29.6%). Validating ICD-coded data for depression is important due to variation in coding practices across jurisdictions. The most suitable case definitions for detecting depression in administrative data vary depending on the context. For surveillance purposes, the most inclusive ICD-9 & ICD-10 case definitions resulted in PPVs of 89.7% and 89.5%, respectively. In cases where diagnostic certainty is required, the least inclusive ICD-9 and −10 case definitions are recommended, resulting in PPVs of 92.0% and 91.1%. All proposed case definitions resulted in suboptimal levels of sensitivity (ranging from 28.9%-35.6%). The addition of outpatient data (such as pharmacy records) for depression surveillance is recommended and should result in improved measures of validity.

  • the development evolution and modifications of icd 10 challenges to the international comparability of morbidity data
    Medical Care, 2010
    Co-Authors: Nathalie Jette, Hude Quan, Vijaya Sundararajan, Saskia E. Drösler, Lori Moskal, Brenda R Hemmelgarn, Christina Maass, Wansa Paoin, Song Gao, Robert Jakob
    Abstract:

    Background:The United States is about to make a major nationwide transition from ICD-9-CM coding of hospital discharges to ICD-10-CM, a country-specific modification of the World Health Organization's ICD-10. As this transition occurs, the WHO is already in the midst of developing ICD-11. Given this

  • assessing validity of icd 9 cm and icd 10 administrative data in recording clinical conditions in a unique dually coded database
    Health Services Research, 2008
    Co-Authors: Hude Quan, Duncan L Saunders, Gerry A Parsons, Carolyn Nilsson, Arif Alibhai, William A Ghali
    Abstract:

    The World Health Organization adopted the first version of the International Classification of Diseases (ICD) in 1900 to internationally monitor and compare mortality statistics and causes of death. Since then, the classification has been revised periodically to accommodate new knowledge of disease and health. The sixth revision, published in 1949, was more radical than the previous five revisions because this edition made it possible to record information from patient charts to compile morbidity statistics. Subsequent revisions were made in 1958 (7th Edition), in 1968 (8th Edition), and in 1979 (9th Edition). The United States modified ICD-9 by specifying many categories and extending coding rubrics to describe the clinical picture in more detail. These modifications resulted in the publication of ICD-9 Clinical Modification (ICD-9-CM) in 1979 for coding diagnoses in patient charts (Commission on Professional and Hospital Activities 1986). The latest version, ICD-10, was introduced in 1992 (World Health Organization 1992). The major differences between the ICD-10 and ICD-9-CM coding systems are: (1) the tabular list in ICD-10 has 21 categories of disease compared with 19 categories in ICD-9-CM and the category of diseases of the nervous system and sense organs in ICD-9-CM is divided into three categories in ICD-10, including diseases of the nervous system, diseases of the eye and adnexa, and diseases of the ear and mastoid process; and (2) the codes in ICD-10 are alphanumeric while codes in ICD-9-CM are numeric. Each code in ICD-10 starts with a letter (i.e., A–Z), followed by two numeric digits, a decimal, and a digit (e.g., acute bronchiolitis due to respiratory syncytial virus is J21.0). In contrast, codes in ICD-9-CM begin with three digit numbers (i.e., 001–999), that are followed by a decimal and up to two digits (e.g., acute bronchiolitis due to respiratory syncytial virus is 466.11). Canada, Australia, Germany, and other countries have enhanced ICD-10 by adding more specific codes and released country-specific ICD-10 versions, such as ICD-10-Canada (ICD-10-CA; Canadian Institute for Health Information 2003). However, ICD-10-CA has maintained its comparability with ICD-10. The basic ICD-10 structure, scope, content, and definition of existing codes are not altered in ICD-10-CA. This means that none of the ICD-10 codes are relocated or deleted. ICD-10-CA mainly extends code character levels, from third and fourth levels of ICD-10 to fourth, fifth, or sixth character levels (e.g., from I15.0 for renovascular hypertension to I15.00 for benign renovascular hypertension and I15.01 for malignant renovascular hypertension). A few additions of third- and fourth-level codes were also included in ICD-10-CA in a manner consistent with the existing classification. All of these additional codes are indicated with red maple leaf symbols in ICD-10-CA coding manuals. To continuously study the health care system and investigate or monitor population health status with ICD-10 data, it is imperative to assess errors that could occur in the process of creating administrative data due to the introduction of the new coding system, ICD-10. We conducted this study to evaluate the validity of ICD-10 administrative hospital discharge data and to determine whether there were improvements in the validity compared with the validity of ICD-9-CM data. To achieve this aim, we reviewed randomly selected charts coded using ICD-10 at four Canadian teaching hospitals, determined the presence or absence of recorded conditions, and then separately recoded the same charts using ICD-9-CM. Then we assessed the agreement between originally coded ICD-10 administrative and chart review data, and the recoded ICD-9-CM administrative data and chart review data for recording the same conditions. This permitted us to compare the accuracy of ICD-10 data relative to the chart review data, with the accuracy of ICD-9-CM data relative to the chart review data for these conditions.

  • an administrative data merging solution for dealing with missing data in a clinical registry adaptation from icd 9 to icd 10
    BMC Medical Research Methodology, 2008
    Co-Authors: Danielle A. Southern, Hude Quan, Min Gao, Karin H Humphries, Colleen M Norris, Fiona M Shrive, Diane P Galbraith, Merril L Knudtson
    Abstract:

    We have previously described a method for dealing with missing data in a prospective cardiac registry initiative. The method involves merging registry data to corresponding ICD-9-CM administrative data to fill in missing data 'holes'. Here, we describe the process of translating our data merging solution to ICD-10, and then validating its performance. A multi-step translation process was undertaken to produce an ICD-10 algorithm, and merging was then implemented to produce complete datasets for 1995–2001 based on the ICD-9-CM coding algorithm, and for 2002–2005 based on the ICD-10 algorithm. We used cardiac registry data for patients undergoing cardiac catheterization in fiscal years 1995–2005. The corresponding administrative data records were coded in ICD-9-CM for 1995–2001 and in ICD-10 for 2002–2005. The resulting datasets were then evaluated for their ability to predict death at one year. The prevalence of the individual clinical risk factors increased gradually across years. There was, however, no evidence of either an abrupt drop or rise in prevalence of any of the risk factors. The performance of the new data merging model was comparable to that of our previously reported methodology: c-statistic = 0.788 (95% CI 0.775, 0.802) for the ICD-10 model versus c-statistic = 0.784 (95% CI 0.780, 0.790) for the ICD-9-CM model. The two models also exhibited similar goodness-of-fit. The ICD-10 implementation of our data merging method performs as well as the previously-validated ICD-9-CM method. Such methodological research is an essential prerequisite for research with administrative data now that most health systems are transitioning to ICD-10.

  • coding algorithms for defining comorbidities in icd 9 cm and icd 10 administrative data
    Medical Care, 2005
    Co-Authors: Hude Quan, Vijaya Sundararajan, Bernard Burnand, Patricia Halfon, Jean Christophe Luthi, Andrew Fong, Duncan L Saunders, Cynthia A Beck, Thomas E Feasby, William A Ghali
    Abstract:

    Objectives:Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define C

William A Ghali - One of the best experts on this subject based on the ideXlab platform.

  • ICD-11 for quality and safety: overview of the who quality and safety topic advisory group
    International journal for quality in health care : journal of the International Society for Quality in Health Care, 2013
    Co-Authors: William A Ghali, Vijaya Sundararajan, Harold Alan Pincus, Danielle A. Southern, Susan E Brien, Patrick S. Romano, Bernard Burnand, Saskia E. Drösler, Lori Moskal, Alan J. Forster
    Abstract:

    This paper outlines the approach that the WHO’s Family of International Classifications (WHO-FIC) network is undertaking to create ICD-11. We also outline the more focused work of the Quality and Safety Topic Advisory Group, whose activities include the following: (i) cataloguing existing ICD-9 and ICD-10 quality and safety indicators; (ii) reviewing ICD morbidity coding rules for main condition, diagnosis timing, numbers of diagnosis fields and diagnosis clustering; (iii) substantial restructuring of the healthcare related injury concepts coded in the ICD-10 chapters 19/20, (iv) mapping of ICD-11 quality and safety concepts to the information model of the WHO’s International Classification for Patient Safety and the AHRQ Common Formats; (v) the review of vertical chapter content in all chapters of the ICD-11 beta version and (vi) downstream field testing of ICD-11 prior to its official 2015 release. The transition from ICD-10 to ICD-11 promises to produce an enhanced classification that will have better potential to capture important concepts relevant to measuring health system safety and quality—an important use case for the classification.

  • assessing validity of icd 9 cm and icd 10 administrative data in recording clinical conditions in a unique dually coded database
    Health Services Research, 2008
    Co-Authors: Hude Quan, Duncan L Saunders, Gerry A Parsons, Carolyn Nilsson, Arif Alibhai, William A Ghali
    Abstract:

    The World Health Organization adopted the first version of the International Classification of Diseases (ICD) in 1900 to internationally monitor and compare mortality statistics and causes of death. Since then, the classification has been revised periodically to accommodate new knowledge of disease and health. The sixth revision, published in 1949, was more radical than the previous five revisions because this edition made it possible to record information from patient charts to compile morbidity statistics. Subsequent revisions were made in 1958 (7th Edition), in 1968 (8th Edition), and in 1979 (9th Edition). The United States modified ICD-9 by specifying many categories and extending coding rubrics to describe the clinical picture in more detail. These modifications resulted in the publication of ICD-9 Clinical Modification (ICD-9-CM) in 1979 for coding diagnoses in patient charts (Commission on Professional and Hospital Activities 1986). The latest version, ICD-10, was introduced in 1992 (World Health Organization 1992). The major differences between the ICD-10 and ICD-9-CM coding systems are: (1) the tabular list in ICD-10 has 21 categories of disease compared with 19 categories in ICD-9-CM and the category of diseases of the nervous system and sense organs in ICD-9-CM is divided into three categories in ICD-10, including diseases of the nervous system, diseases of the eye and adnexa, and diseases of the ear and mastoid process; and (2) the codes in ICD-10 are alphanumeric while codes in ICD-9-CM are numeric. Each code in ICD-10 starts with a letter (i.e., A–Z), followed by two numeric digits, a decimal, and a digit (e.g., acute bronchiolitis due to respiratory syncytial virus is J21.0). In contrast, codes in ICD-9-CM begin with three digit numbers (i.e., 001–999), that are followed by a decimal and up to two digits (e.g., acute bronchiolitis due to respiratory syncytial virus is 466.11). Canada, Australia, Germany, and other countries have enhanced ICD-10 by adding more specific codes and released country-specific ICD-10 versions, such as ICD-10-Canada (ICD-10-CA; Canadian Institute for Health Information 2003). However, ICD-10-CA has maintained its comparability with ICD-10. The basic ICD-10 structure, scope, content, and definition of existing codes are not altered in ICD-10-CA. This means that none of the ICD-10 codes are relocated or deleted. ICD-10-CA mainly extends code character levels, from third and fourth levels of ICD-10 to fourth, fifth, or sixth character levels (e.g., from I15.0 for renovascular hypertension to I15.00 for benign renovascular hypertension and I15.01 for malignant renovascular hypertension). A few additions of third- and fourth-level codes were also included in ICD-10-CA in a manner consistent with the existing classification. All of these additional codes are indicated with red maple leaf symbols in ICD-10-CA coding manuals. To continuously study the health care system and investigate or monitor population health status with ICD-10 data, it is imperative to assess errors that could occur in the process of creating administrative data due to the introduction of the new coding system, ICD-10. We conducted this study to evaluate the validity of ICD-10 administrative hospital discharge data and to determine whether there were improvements in the validity compared with the validity of ICD-9-CM data. To achieve this aim, we reviewed randomly selected charts coded using ICD-10 at four Canadian teaching hospitals, determined the presence or absence of recorded conditions, and then separately recoded the same charts using ICD-9-CM. Then we assessed the agreement between originally coded ICD-10 administrative and chart review data, and the recoded ICD-9-CM administrative data and chart review data for recording the same conditions. This permitted us to compare the accuracy of ICD-10 data relative to the chart review data, with the accuracy of ICD-9-CM data relative to the chart review data for these conditions.

  • coding algorithms for defining comorbidities in icd 9 cm and icd 10 administrative data
    Medical Care, 2005
    Co-Authors: Hude Quan, Vijaya Sundararajan, Bernard Burnand, Patricia Halfon, Jean Christophe Luthi, Andrew Fong, Duncan L Saunders, Cynthia A Beck, Thomas E Feasby, William A Ghali
    Abstract:

    Objectives:Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define C

  • new icd 10 version of the charlson comorbidity index predicted in hospital mortality
    Journal of Clinical Epidemiology, 2004
    Co-Authors: Vijaya Sundararajan, Hude Quan, Toni Henderson, Catherine Perry, Amanda Muggivan, William A Ghali
    Abstract:

    Abstract Background and objective The ICD-9-CM adaptation of the Charlson comorbidity score has been a valuable resource for health services researchers. With the transition into ICD-10 coding worldwide, an ICD-10 version of the Deyo adaptation was developed and validated using population-based hospital data from Victoria, Australia. Methods The algorithm was translated from ICD-9-CM into ICD-10-AM (Australian modification) in a multistep process. After a mapping algorithm was used to develop an initial translation, these codes were manually examined by the coding experts and a general physician for face validity. Because the ICD-10 system is country specific, our goal was to keep many of the translated code at the three-digit level for generalizability of the new index. Results There appears to be little difference in the distribution of the Charlson Index score between the two versions. A strong association between increasing index scores and mortality exists: the area under the ROC curve is 0.865 for the last year using the ICD-9-CM version and remains high, at 0.855, for the ICD-10 version. Conclusion This work represents the first rigorous adaptation of the Charlson comorbidity index for use with ICD-10 data. In comparison with a well-established ICD-9-CM coding algorithm, it yields closely similar prevalence and prognosis information by comorbidity category.

Gary L Glish - One of the best experts on this subject based on the ideXlab platform.

  • simultaneous collision induced dissociation of the charge reduced parent ion during electron capture dissociation
    Analytical Chemistry, 2009
    Co-Authors: Jared M Bushey, Takashi Baba, Gary L Glish
    Abstract:

    A method of performing collision induced dissociation (CID) on the charge-reduced parent ion as it is formed during electron capture dissociation (ECD), called ECD+CID, is described. In ECD+CID, the charge-reduced parent ion is selectively activated using resonant excitation and collisions with the helium bath gas inside a linear quadrupole ion trap ECD device (ECDLIT). It has been observed that ECD+CID can improve the sequence coverage for β-endorphin over performing ECD alone (i.e., from 72 to 97%). Perhaps just as important, ECD+CID can be used to reduce the extent of multiple electron capture events observed when performing ECD in the ECDLIT. Consequently, the abundance of mass-to-charge ratios corresponding to ECD product ions that contain neutralized protons is decreased, simplifying the interpretation of the product ion spectrum.

  • Simultaneous collision induced dissociation of the charge reduced parent ion during electron capture dissociation.
    Analytical chemistry, 2009
    Co-Authors: Jared M Bushey, Takashi Baba, Gary L Glish
    Abstract:

    A method of performing collision induced dissociation (CID) on the charge-reduced parent ion as it is formed during electron capture dissociation (ECD), called ECD+CID, is described. In ECD+CID, the charge-reduced parent ion is selectively activated using resonant excitation and collisions with the helium bath gas inside a linear quadrupole ion trap ECD device (ECDLIT). It has been observed that ECD+CID can improve the sequence coverage for β-endorphin over performing ECD alone (i.e., from 72 to 97%). Perhaps just as important, ECD+CID can be used to reduce the extent of multiple electron capture events observed when performing ECD in the ECDLIT. Consequently, the abundance of mass-to-charge ratios corresponding to ECD product ions that contain neutralized protons is decreased, simplifying the interpretation of the product ion spectrum.