DOCSLIB.ORG

Detecting Privacy-Sensitive Events in Medical Text

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Detecting Privacy-Sensitive Events in Medical Text Detecting Privacy-Sensitive Events in Medical Text Prateek Jindal Carl A. Gunter Dan Roth Yahoo! Inc. Department of Computer Department of Computer 2021 S. First St Science, UIUC Science, UIUC Suite 110 201 N. Goodwin Ave 201 N. Goodwin Ave Champaign, IL, USA Urbana, IL, USA Urbana, IL, USA [email protected] [email protected] [email protected] ABSTRACT view as extra-sensitive information when this information is In this paper, we present a novel semi-supervised technique not needed for a specific instance. For instance, a patient for finding privacy-sensitive events in clinical text. Unlike with a twisted ankle would not like her records of childhood traditional semi-supervised methods, we do not require large abuse to be shared automatically for this type of treatment. amounts of unannotated data. Instead, our approach relies There are several types of sensitive data that are found in on information contained in the hierarchical structure of a the clinical narratives. We categorize the sensitive data into large medical encyclopedia. 5 major types below: 1. Mental health and abuse in the family Categories and Subject Descriptors 2. Substance Abuse I.2.6 [Artificial Intelligence]: Learning|Concept Learn- ing; I.2.7 [Artificial Intelligence]: Natural Language Pro- 3. HIV Data cessing|Text Analysis; J.3 [Life and Medical Sciences]: 4. Presence of genetic information in EHRs Medical Information Systems; K.5.2 [Legal Aspects of 5. Sexually transmitted infections and reproductive health Computing]: Government Issues|Regulation In some hospital systems, structured information in the General Terms form of ICD9 codes is used to restrict the sharing of patients' Algorithms, Experimentation, Performance, Security clinical history. For instance, if a record contains ICD9 code 042 (HIV) and a patient has indicated that his HIV status should not be shared, then this can be done by preventing Keywords all or some of his record (including the HIV diagnosis) from Natural Language Processing, Health Informatics, Computer being shared. This strategy has a number of limitations, one Security, Active Learning, Semi-Supervision, Set Expansion, of the most serious of which is the fact that it does not work Concept Identification, Domain Knowledge, SNOMED CT for unstructured data like clinical narratives. In this paper, we present a semi-supervised technique for 1. INTRODUCTION finding phrases in clinical narratives which express a sensi- tive condition about the patient. The advantage of our tech- There is a growing interest in ways to exploit the increased nique is that we don't require any annotated data for train- use of Electronic Health Records (EHRs) to improve health- ing etc. Moreover, we don't even require any unannotated care and reduce its costs. One key goal is to enable records data. This is in contrast to traditional semi-supervised ap- of patients to be shared quickly to assure that the right in- proaches [9, 6] which rely on large amounts of unannotated formation is in the right place when it is needed (such as a data for building distributional contexts. Instead of relying list of allergies and medications for a patient who has arrived on distributional contexts of the relevant concepts, we use in an emergency room) and that redundancy is reduced (so the tree positions of the concepts in a medical encyclopedia that tests run at one institution do not need to be re-run at named SNOMED CT1 to find the similarity between them. another). This sharing raises privacy concerns, even when Problem of finding sensitive information in clinical notes it can be taken as given that a patient wants to allow his is complicated by the fact that the concepts may be negated records to be shared to aid his own care. One area of con- in the text or the concepts may not apply to the patient at cern is the risk of sharing what some patients and regulators all. We briefly discuss these issues as well. Permission to make digital or hard copies of part or all of this work for personal or 2. DESCRIPTION OF OUR METHOD classroom use is granted without fee provided that copies are not made or distributed The input to our algorithm consists of a few examples for profit or commercial advantage, and that copies bear this notice and the full ci- (seeds) of the concepts which the user is interested to find. tation on the first page. Copyrights for third-party components of this work must be For example, if one wants to find the instances of substance honored. For all other uses, contact the owner/author(s). Copyright is held by the author/owner(s). abuse, one may give the following concepts in the input: BCB’14, September 20–23, 2014, Newport Beach, CA, USA. \cocaine, barbiturates and alcohol". Let us represent this ACM 978-1-4503-2894-4/14/09. 1 http://dx.doi.org/10.1145/2649387.2662451. http://www.ihtsdo.org/snomed-ct/ ACM-BCB 2014 617 Level Concepts Level 0 Cocaine, Cocaine measurement Drug measurement, Tropane alkaloid, Level 1 Psychostimulant, Ester type local anesthetic Azabicyclo compound, Local anesthetic, Measurement of substance, Ester, Level 2 Psychotherapeutic agent, Stimulant, Heterocyclic compound, Tropane alkaloid CNS drug, Psychoactive substance, Aza compound, Anesthetic, Level 3 Drug pseudoallergen by function, Alkaloid, Measurement, Organic compound General drug type, Substance categorized functionally, Level 4 Drug pseudoallergen, Evaluation procedure, Techniques, Chemical categorized structurally Table 1: This table shows the descriptor for concept \cocaine". th seed set by S. Let si denote the i element of this seed set. trally acting muscle relaxant, Morphine Derivative, Opiate, Now, the various steps of our algorithm are described in the Hallucinogen, Alcoholic Beverage, Central Depressant. following subsections. 2.3 Step 3: Computing the Similarity of any 2.1 Step 1: Building Individual Descriptors Concept to Seed-Set Using SNOMED CT, we first build a detailed descriptor In this subsection, we describe how to compute the simi- of every concept specified in the seed set S. A concept can larity of any given SNOMED CT concept to the seed set, S, appear at multiple places in SNOMED CT. We define the provided by the user. Let us denote the given SNOMED CT descriptor of a concept to be simply the parents of the con- concept by the variable x. Then the similarity, sim(x; S), of cept upto 5 higher levels. We explain it below with the help the concept x to the seed set S is defined by the following of an example. Let us consider the concept \cocaine". The equation: descriptor of this concept is shown in Table 1. At level 0, two SNOMED CT concepts corresponding to \cocaine" are 4 ! shown. Concepts at any level i + 1 are basically the parents [ \ sim(x; S) = Li(x) MedRep(S) (2) of concepts at level i. It is normal for some of the concepts i=1 to repeat at later levels. These descriptors were made by In other words, similarity of a concept to the seed set is the a simple breadth-first search on the SNOMED CT graph number of unique SNOMED CT concepts in the descriptor starting from the concept under consideration. of the concept that also appear in the seed-set model learned 2.2 Step 2: Obtaining Model for Seed-Set Us- in step 2 above. ing Active Learning 2.4 Step 4: Concept Identification After computing the individual descriptors of all the con- First of all, we map the noun phrases occurring in the cepts in the seed set S, we merge those descriptors into a clinical text to corresponding SNOMED CT concepts us- single descriptor. Let us assume that for concept x, parents ing MetaMap software2. Then, by using the procedure de- at level i are denoted by the set Li(x). Then the levels of scribed in Step 3 above, we find the similarities of all the con- the overall descriptor are defined by the following equation: cepts in any given document to the given seed set. Finally, we rank the concepts in decreasing order of similarity and jSj then apply a threshold (which was computed empirically). [ Li(S) = Li(sj ) 8i (1) This gives us the desired list of most relevant concepts in j=1 the given document which belong to the same category as the seeds input by the user to begin with. After some preprocessing (removal of overly general con- cepts), the descriptor is shown to the user. Then the user is supposed to identify one or more most appropriate SNOMED 3. ASSERTION STATUS CT concepts from this overall descriptor. User response In the above section, we described a technique for finding is recorded into a list. This list constitutes the learned sensitive events in the clinical text. However, it should be model for the concept identification. Let us call this list appreciated that the mere presence of a sensitive concept as MedRep(S). No further input from user is now required. in clinical text does not necessarily raise privacy concerns To give an example, in one of our sample runs, MedRep(S) about patient's medical information. contained the following SNOMED CT concepts for the seed We give two examples to illustrate this fact. For the first set described at the beginning of this section: Psychoactive example, consider a clinical narrative that says, \The patient substance, Anxiolytic, sedative AND/OR hypnotic, Sympa- thomimetic agent, Centrally acting hypotensive agent, Cen- 2http://metamap.nlm.nih.gov/ ACM-BCB 2014 618 does not inject heroin". Even though the drug heroin is men- this simple seed set, we were able to identify in our corpus tioned in this sentence, there is no sensitive information be- several other products which are often used for substance- cause of the negation.
Load more

Recommended publications
  • The Evaluation of Drug Regulation - Economic Approaches Into the Valuation and Evaluation of the Drug Regulatory Framework
    The Evaluation of Drug Regulation - Economic approaches into the valuation and evaluation of the drug regulatory framework Jacoline Bouvy The evaluation of drug regulation – Economic approaches into the valuation and evaluation of the drug regulatory framework Bouvy, JC. ISBN 000000 Author Jacoline Bouvy Cover photo Bigstock.com Printed by Drukkerij Mostert en Van Onderen! The evaluation of drug regulation – Economic approaches into the valuation and evaluation of the drug regulatory framework Evaluatie van geneesmiddelenregulering – Economische toepassingen in de waardering en evaluatie van het regulatoire geneesmiddelensysteem (met een samenvatting in het Nederlands) Proefschrift ter verkrijging van de graad van doctor aan de Universiteit Utrecht op gezag van de rector magnificus, prof.dr. G.J. van der Zwaan, ingevolge het besluit van het college voor promoties in het openbaar te verdedigen op woensdag 23 januari 2013 des middags te 12.45 uur door Jacoline Catharina Bouvy geboren op 27 maart 1985 te Rotterdam Promotor: Prof. dr. H. Schellekens Co-promotor: Dr. M.A. Koopmanschap The studies presented in this thesis were performed in the context of the Escher project (T6- 202), a project of the Dutch Top Institute Pharma. ‘It is our choices, Harry, that show what we truly are, far more than our abilities.’ Albus Dumbledore (In J.K. Rowling’s Harry Potter and the Chamber of Secrets) Glossary ADR Adverse drug reaction CBG-MEB Dutch Medicines Evaluation Board CKD Chronic Kidney Disease DCE Discrete Choice Experiment DHPC Direct Healthcare
    [Show full text]
  • (12) United States Patent (10) Patent No.: US 8,603,526 B2 Tygesen Et Al
    USOO8603526B2 (12) United States Patent (10) Patent No.: US 8,603,526 B2 Tygesen et al. (45) Date of Patent: Dec. 10, 2013 (54) PHARMACEUTICAL COMPOSITIONS 2008. O152595 A1 6/2008 Emigh et al. RESISTANT TO ABUSE 2008. O166407 A1 7/2008 Shalaby et al. 2008/0299.199 A1 12/2008 Bar-Shalom et al. 2008/0311205 A1 12/2008 Habib et al. (75) Inventors: Peter Holm Tygesen, Smoerum (DK); 2009/0022790 A1 1/2009 Flath et al. Jan Martin Oevergaard, Frederikssund 2010/0203129 A1 8/2010 Andersen et al. (DK); Karsten Lindhardt, Haslev (DK); 2010/0204259 A1 8/2010 Tygesen et al. Louise Inoka Lyhne-versen, Gentofte 2010/0239667 A1 9/2010 Hemmingsen et al. (DK); Martin Rex Olsen, Holbaek 2010, O291205 A1 11/2010 Downie et al. (DK); Anne-Mette Haahr, Birkeroed 2011 O159100 A1 6/2011 Andersen et al. (DK); Jacob Aas Hoellund-Jensen, FOREIGN PATENT DOCUMENTS Frederikssund (DK); Pemille Kristine Hoeyrup Hemmingsen, Bagsvaerd DE 20 2006 014131 1, 2007 (DK) EP O435,726 8, 1991 EP O493513 7, 1992 EP O406315 11, 1992 (73) Assignee: Egalet Ltd., London (GB) EP 1213014 6, 2002 WO WO 89,09066 10, 1989 (*) Notice: Subject to any disclaimer, the term of this WO WO91,040 15 4f1991 patent is extended or adjusted under 35 WO WO95/22962 8, 1995 U.S.C. 154(b) by 489 days. WO WO99,51208 10, 1999 WO WOOOf 41704 T 2000 WO WO 03/024426 3, 2003 (21) Appl. No.: 12/701,429 WO WOO3,O24429 3, 2003 WO WOO3,O24430 3, 2003 (22) Filed: Feb.
    [Show full text]
  • American College of Epidemiology Annual Meeting Abstracts, September 7-10, 2019, Pasadena, California
    Annals of Epidemiology 36 (2019) 66e78 Contents lists available at ScienceDirect Annals of Epidemiology journal homepage: www.annalsofepidemiology.org American College of Epidemiology Annual Meeting Abstracts, September 7-10, 2019, Pasadena, California Oral Presentations Exploring uniformity of gestational diabetes Methods: We estimated the percentage of overdose deaths reported in the screening and diagnosis using real-world National Vital Statistics System with missing toxicology results from 2010- ’ electronic health record data 2016, overall and by decedents demographic and geographic characteristics. We used a multi-level model to evaluate prevalence of missingness by decedent characteristics, accounting for geographic clustering. & J.M. Lawrence, X. Li. Department of Research Evaluation, Kaiser Results: One-fifth of 351,345 drug overdose deaths from 2010-2016 did not Permanente Southern California, Pasadena, CA indicate a specific drug, declining from 24.4% in 2010 to 14.6% in 2016. In a multi-level model controlling for all predictors, deaths were less likely to Purpose: Gestational diabetes (GDM) surveillance frequently relies on In- have missing information if they occurred in metro counties compared to ternational Classification of Disease (ICD) codes to identify cases. GDM di- rural counties (aOR: 0.31, 95%CI: 0.24, 0.41) and in counties with medical agnoses can be based on several criteria including Carpenter & Coustan examiners versus coroners (aOR: 0.57, 95%CI: 0.47, 0.69). Male decedents (C&C) and International Association of Diabetes in Pregnancy Group were less likely to have missing information than females (aOR: 0.73, 95% (IADPSG). Our objectives were to describe GDM testing patterns within one CI: 0.69, 0.77), and non-Hispanic whites were more likely to have missing large health system and evaluate how well diagnostic coding corresponds information than non-Hispanic blacks (aOR: 1.31, 95%CI: 1.2, 1.4).
    [Show full text]
  • Methadone Maintenance Treatment and Its Psychosocial Effects on Individuals
    St. Catherine University SOPHIA Master of Social Work Clinical Research Papers School of Social Work 5-2014 Methadone Maintenance Treatment and its Psychosocial Effects on Individuals Fatai Adeshina Popoola St. Catherine University Follow this and additional works at: https://sophia.stkate.edu/msw_papers Part of the Social Work Commons Recommended Citation Popoola, Fatai Adeshina. (2014). Methadone Maintenance Treatment and its Psychosocial Effects on Individuals. Retrieved from Sophia, the St. Catherine University repository website: https://sophia.stkate.edu/msw_papers/378 This Clinical research paper is brought to you for free and open access by the School of Social Work at SOPHIA. It has been accepted for inclusion in Master of Social Work Clinical Research Papers by an authorized administrator of SOPHIA. For more information, please contact [email protected]. Methadone Maintenance Treatment and its Psychosocial Effects on Individuals by Fatai Adeshina Popoola (BEd\ Political Science, LADC) Proposal for a Clinical Research Paper Presented to the Faculty of the School of Social Work St. Catherine University and the University of St. Thomas St. Paul, Minnesota in Partial fulfillment of the Requirements for the Degree of Master of Social Work Committee Members Rajean P. Moone Ph.D., LNHA, (Chair) Rashad Hameed, MA, LADC Neerja Singh, Ph.D., LICSW The Clinical Research Project is a graduation requirement for MSW students at St. Catherine University/University of St. Thomas School of Social Work in St Paul, Minnesota and is conducted within a nine-month time frame to demonstrate facility with basic social research methods. Students must independently conceptualize a research problem, formulate a research design that is approved by a research committee and the university Institutional Review Board, implement the project, and publicly present the findings of the study.
    [Show full text]
  • Question of the Day Archives: Monday, December 5, 2016 Question: Calcium Oxalate Is a Widespread Toxin Found in Many Species of Plants
    Question Of the Day Archives: Monday, December 5, 2016 Question: Calcium oxalate is a widespread toxin found in many species of plants. What is the needle shaped crystal containing calcium oxalate called and what is the compilation of these structures known as? Answer: The needle shaped plant-based crystals containing calcium oxalate are known as raphides. A compilation of raphides forms the structure known as an idioblast. (Lim CS et al. Atlas of select poisonous plants and mushrooms. 2016 Disease-a-Month 62(3):37-66) Friday, December 2, 2016 Question: Which oral chelating agent has been reported to cause transient increases in plasma ALT activity in some patients as well as rare instances of mucocutaneous skin reactions? Answer: Orally administered dimercaptosuccinic acid (DMSA) has been reported to cause transient increases in ALT activity as well as rare instances of mucocutaneous skin reactions. (Bradberry S et al. Use of oral dimercaptosuccinic acid (succimer) in adult patients with inorganic lead poisoning. 2009 Q J Med 102:721-732) Thursday, December 1, 2016 Question: What is Clioquinol and why was it withdrawn from the market during the 1970s? Answer: According to the cited reference, “Between the 1950s and 1970s Clioquinol was used to treat and prevent intestinal parasitic disease [intestinal amebiasis].” “In the early 1970s Clioquinol was withdrawn from the market as an oral agent due to an association with sub-acute myelo-optic neuropathy (SMON) in Japanese patients. SMON is a syndrome that involves sensory and motor disturbances in the lower limbs as well as visual changes that are due to symmetrical demyelination of the lateral and posterior funiculi of the spinal cord, optic nerve, and peripheral nerves.
    [Show full text]
  • Levacetylmethadol
    Leflunomide/Lornoxicam 77 6. Maddison P, et al. Leflunomide in rheumatoid arthritis: recom- Levomethadone Hydrochloride (rINNM) ⊗ Lithium Salicylate mendations through a process of consensus. Rheumatology (Ox- ford) 2005; 44: 280–6. Correction. ibid.; 569. Hidrocloruro de levometadona; Levometadonhidroklorid; Lev- Lithium Salicylicum; Salicilato de litio. 7. Silverman E, et al. Long-term open-label preliminary study of ometadonhydroklorid; Levometadonihydrokloridi; Levometado- Лития Салицилат the safety and efficacy of leflunomide in patients with polyartic- no hidrochloridas; Lévométhadone, chlorhydrate de; Levometh- C H LiO = 144.1. ular-course juvenile rheumatoid arthritis. Arthritis Rheum 2005; adon-hydrochlorid; Levomethadoni hydrochloridum; (−)-Metha- 7 5 3 52: 554–62. CAS — 552-38-5. 8. Silverman E, et al. Leflunomide in Juvenile Rheumatoid Arthri- done Hydrochloride. (−)-6-Dimethylamino-4,4-diphenylheptan- tis (JRA) Investigator Group. Leflunomide or methotrexate for 3-one hydrochloride. juvenile rheumatoid arthritis. N Engl J Med 2005; 352: 1655–66. Левометадона Гидрохлорид HO Spondyloarthropathies. References to the use of leflunomide C21H27NO,HCl = 345.9. Li+ -O in ankylosing spondylitis and psoriatic arthritis (see Spondyloar- CAS — 125-58-6 (levomethadone); 5967-73-7 (levometh- thropathies, p.13). adone hydrochloride). 1. Cuchacovich M, Soto L. Leflunomide decreases joint erosions O and induces reparative changes in a patient with psoriatic arthri- tis. Ann Rheum Dis 2002; 61: 942–3. 2. Kaltwasser JP, et al. Treatment of Psoriatic Arthritis Study Profile Group. Efficacy and safety of leflunomide in the treatment of Lithium salicylate is a salicylic acid derivative (see Aspirin, psoriatic arthritis and psoriasis: a multinational, double-blind, randomized, placebo-controlled clinical trial. Arthritis Rheum p.20) that has been used in rheumatic disorders, but its use cannot 2004; 50: 1939–50.
    [Show full text]
  • Supplement 1: Additional Tables and Figures
    BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) BMJ Global Health Supplement 1: Additional tables and figures Box S1: Substances included and excluded from the International Narcotic Control Board (INCB) data on narcotic consumption, in alphabetical order. Opioids included in the opioid consumption calculation: 1. (+)-cis-3-methylfental 35. Bezitramide 2. 3-Acetylmorphine 36. Butyrfentanyl 3. 3-Methylfentanyl 37. Carfentanil 4. 3-Methylthiofentanyl 38. Carfentanyl 5. 3-Monoacetylmorphine 39. Clonitazene 6. 4-Fluoroisobutyrfentanyl 40. Codeine 7. 6-Acetylmorphine 41. Codeine-6GLUC 8. 6-Monoacetylmorphine 42. Codeine-6-glucuronide 9. Acetorphine 43. Codeine-Methyl 10. Acetyl-alpha-methylfentanyl 44. Codeine-N-oxide 11. Acetyldihydrocodeine 45. Codoxime 12. Acetylfentanyl 46. Conc. of poppy straw (C) ACA 13. Acetylmethadol 47. Conc. of poppy straw (C) AMA 14. Acetylmorphine 48. Conc. of poppy straw (C) AOA 15. Acrylfentanyl 49. Conc. of poppy straw (C) ATA 16. AH-7921 50. Conc. of poppy straw (C) GW 17. Alfentanil 51. Conc. of poppy straw (M) ACA 18. Allylprodine 52. Conc. of poppy straw (M) AMA 19. Alphacetylmethadol 53. Conc. of poppy straw (M) AOA 20. Alphameprodine 54. Conc. of poppy straw (M) ATA 21. Alphamethadol 55. Conc. of poppy straw (M) GW 22. alpha-Methylfentanyl 56. Conc. of poppy straw (N) GW 23. alpha-Methylthiofentanyl 57. Conc. of poppy straw (O) 24. Alphaprodine 58. Conc. of poppy straw (O) ACA 25. Anileridine 59. Conc. of poppy straw (O) AMA 26. Benzethidine 60. Conc. of poppy straw (O) AOA 27.
    [Show full text]
  • Alcohol and Drug Abuse Subchapter 9
    Chapter 8 – Alcohol and Drug Abuse Subchapter 9 Regulated Drug Rule 1.0 Authority This rule is established under the authority of 18 V.S.A. §§ 4201 and 4202 which authorizes the Vermont Board of Health to designate regulated drugs for the protection of public health and safety. 2.0 Purpose This rule designates drugs and other chemical substances that are illegal or judged to be potentially fatal or harmful for human consumption unless prescribed and dispensed by a professional licensed to prescribe or dispense them and used in accordance with the prescription. The rule restricts the possession of certain drugs above a specified quantity. The rule also establishes benchmark unlawful dosages for certain drugs to provide a baseline for use by prosecutors to seek enhanced penalties for possession of higher quantities of the drug in accordance with multipliers found at 18 V.S.A. § 4234. 3.0 Definitions 3.1 “Analog” means one of a group of chemical components similar in structure but different with respect to elemental composition. It can differ in one or more atoms, functional groups or substructures, which are replaced with other atoms, groups or substructures. 3.2 “Benchmark Unlawful Dosage” means the quantity of a drug commonly consumed over a twenty-four-hour period for any therapeutic purpose, as established by the manufacturer of the drug. Benchmark Unlawful dosage is not a medical or pharmacologic concept with any implication for medical practice. Instead, it is a legal concept established only for the purpose of calculating penalties for improper sale, possession, or dispensing of drugs pursuant to 18 V.S.A.
    [Show full text]
  • Pharmacogenomic Study of Opioid Addicts in Methadone Treatment
    Pharmacogenomic study of opioid addicts in methadone treatment PhD candidate: Francina Fonseca Casals Doctoral thesis Universitat Pompeu Fabra / 2010 PhD directors: Dr. Rafael de la Torre i Fornell (CEXS, Universitat Pompeu Fabra) Dra. Marta Torrens Mèlich (Departament de Psiquiatria, Universitat Autònoma de Barcelona) “It's not the mountain we conquer, but ourselves" Sir Edmund Percival Hillary iii AGRAÏMENTS De tots aquests anys treballant en aquest projecte, el més essencial ha estat aprendre la importància del treball en equip; els resultats que es detallaran són fruit de l’esforç de moltes persones. En primer lloc, agrair la col·laboració dels pacients del CAS Barceloneta que han participat a l’estudi; sense ells, no hagués estat possible. Vull agrair també la implicació de l’equip d’infermeria del CAS Barceloneta i el seu suport desinteressat en la recollida de mostres. A la Laura Díaz, per l’ajuda amb les entrevistes. A l’equip del CRG: en Rafa De Cid, la Mònica Gratacòs i el Xavier Estivill per tota la feina en l’anàlisi genètica. L’equip de Farmacologia de l’IMIM, en Toni Pastor, l’Elisabet Cuyàs i molt especialment a la Neus Pizarro que va tenir la paciència d’explicar-me tot el procés d’anàlisi de les mostres. L’Esther Español que ha editat el document i la Carla Astals pel disseny de la coberta. A l’Institut Municipal d’Investigació Mèdica (IMIM), per l’ajut rebut pel pagament de les despeses finals d’enquadernació de la tesi. La Rocío Martín-Santos i en Magí Farré, pel seu recolzament constant i les idees brillants quan ens encallàvem.
    [Show full text]
  • (12) Patent Application Publication (10) Pub. No.: US 2014/0144429 A1 Wensley Et Al
    US 2014O144429A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2014/0144429 A1 Wensley et al. (43) Pub. Date: May 29, 2014 (54) METHODS AND DEVICES FOR COMPOUND (60) Provisional application No. 61/887,045, filed on Oct. DELIVERY 4, 2013, provisional application No. 61/831,992, filed on Jun. 6, 2013, provisional application No. 61/794, (71) Applicant: E-NICOTINE TECHNOLOGY, INC., 601, filed on Mar. 15, 2013, provisional application Draper, UT (US) No. 61/730,738, filed on Nov. 28, 2012. (72) Inventors: Martin Wensley, Los Gatos, CA (US); Publication Classification Michael Hufford, Chapel Hill, NC (US); Jeffrey Williams, Draper, UT (51) Int. Cl. (US); Peter Lloyd, Walnut Creek, CA A6M II/04 (2006.01) (US) (52) U.S. Cl. CPC ................................... A6M II/04 (2013.O1 (73) Assignee: E-NICOTINE TECHNOLOGY, INC., ( ) Draper, UT (US) USPC ..................................................... 128/200.14 (21) Appl. No.: 14/168,338 (57) ABSTRACT 1-1. Provided herein are methods, devices, systems, and computer (22) Filed: Jan. 30, 2014 readable medium for delivering one or more compounds to a O O Subject. Also described herein are methods, devices, systems, Related U.S. Application Data and computer readable medium for transitioning a Smoker to (63) Continuation of application No. PCT/US 13/72426, an electronic nicotine delivery device and for Smoking or filed on Nov. 27, 2013. nicotine cessation. Patent Application Publication May 29, 2014 Sheet 1 of 26 US 2014/O144429 A1 FIG. 2A 204 -1 2O6 Patent Application Publication May 29, 2014 Sheet 2 of 26 US 2014/O144429 A1 Area liquid is vaporized Electrical Connection Agent O s 2.
    [Show full text]
  • Abstinence Importance of Early Intervention 247 Treatment to Attain
    Cambridge University Press 978-0-521-89882-9 - Ghodse’s Drugs and Addictive Behaviour: A Guide to Treatment, Fourth Edition Hamid Ghodse Index More information Index abstinence AIDS see HIV and AIDS DSM-IV system 155–57 importance of early intervention alcohol 106 ICD-10 system 148–53 247 adverse effects of misuse 111 drug history 131–32 treatment to attain 252 alcohol use disorder (AUD) drug screening programmes 146–47 versus controlled drinking 116 diagnosis and screening 110–11 family assessments 135–36 versus maintenance on opiates extent and nature of problem laboratory investigations 191–92 107–09 interpretation of results 145–46 abstinence syndromes management of 113–15 methods 144–45 neonatal 225–26 policies controlling 117–19 tests 140–44 opiates 77–78, 180–81, 236 relapse prevention 115–17 life history 132–33 sedative hypnotics 84, 218 combined with drugs 103–05 mental state examination 139–40 see also detoxification; withdrawal definitions 106–07 physical examination 136–38 syndromes/states dependence syndrome 107 psychological 140 acamprosate, alcohol dependence genetics of use and dependence 109 social work 133–35 116–17 metabolism of 109–10 time scale for outcome assessment accelerated detoxification, opiates Alcoholics Anonymous (AA) 174–75 245 184–85 alternative medicine 186 workplace drug testing 147 accident and emergency (A & E) the Americas AUDIT (Alcohol Use Disorders departments drug policy, United States 73–74 Identification Test) 110–11 management of drug-dependent drug problems audits patients 235–37 Central America
    [Show full text]
  • The Impact of Chronic Pain on Opioid Addiction
    Dennis et al. Systematic Reviews (2015) 4:49 DOI 10.1186/s13643-015-0042-2 PROTOCOL Open Access The impact of chronic pain on opioid addiction treatment: a systematic review protocol Brittany B Dennis1,2, Monica Bawor2,3,JamesPaul1,4, Michael Varenbut5, Jeff Daiter5, Carolyn Plater5, Guillaume Pare1, David C Marsh5,6,AndrewWorster5,7, Dipika Desai2,9,LehanaThabane1,9,10,11 and Zainab Samaan1,2,12,13* Abstract Background: The consequences of opioid relapse among patients being treated with opioid substitution treatment (OST) are serious and can result in abnormal cardiovascular function, overdose, and mortality. Chronic pain is a major risk factor for opioid relapse within the addiction treatment setting. There exist a number of opioid maintenance therapies including methadone, buprenorphine, naltrexone, and levomethadyl acetate (LAAM), of which the mediating effects of pain on treatment attrition, substance use behavior, and social functioning may differ across therapies. We aim to 1) evaluate the impact of pain on the treatment outcomes of addiction patients being managed with OST and 2) identify the most recently published opioid maintenance treatment guidelines from the United States, Canada, and the UK to determine how the evidence is being translated into clinical practice. Methods/design: The authors will search Medline, EMBASE, PubMed, PsycINFO, Web of Science, Cochrane Database of Systematic Reviews, ProQuest Dissertations and theses Database, Cochrane Central Register of Controlled Trials (CENTRAL), World Health Organization International Clinical Trials Registry Platform Search Portal, and the National Institutes for Health Clinical Trials Registry. We will search www.guidelines.gov and the National Institute for Care and Excellence (NICE) databases to identify the most recently published OST guidelines.
    [Show full text]