scholarly journals An exploratory study of information sources and key findings on UK cocaine-related deaths

2017 ◽  
Vol 31 (8) ◽  
pp. 996-1014 ◽  
Author(s):  
John M Corkery ◽  
Hugh Claridge ◽  
Christine Goodair ◽  
Fabrizio Schifano
Keyword(s):  
Drug Addiction ◽  
Cause Of Death ◽  
Focal Point ◽  
International Classification Of Diseases ◽  
Aggregated Data ◽  
Monitoring Centre ◽  
Classification Of Diseases ◽  
The Uk ◽  
General Mortality

Cocaine-related deaths have increased since the early 1990s in Europe, including the UK. Being multi-factorial, they are difficult to define, detect and record. The European Monitoring Centre for Drugs and Drug Addiction commissioned research to: describe trends reported to Special Mortality Registries and General Mortality Registers; provide demographic and drug-use characteristic information of cases; and establish how deaths are identified and classified. A questionnaire was developed and piloted amongst all European Monitoring Centre for Drugs and Drug Addiction Focal Point experts/Special Mortality Registries: 19 (63%) responded; nine countries provided aggregated data. UK General Mortality Registers use cause of death and toxicology to identify cocaine-related deaths. Categorisation is based on International Classification of Diseases codes. Special Mortality Registries use toxicology, autopsy, evidence and cause of death. The cocaine metabolites commonly screened for are: benzoylecgonine, ecgonine methyl ester, cocaethylene and ecgonine. The 2000s saw a generally accelerating upward trend in cases, followed by a decline in 2009. The UK recorded 2700–2900 deaths during 1998–2012. UK Special Mortality Registry data (2005–2009) indicate: 25–44 year-olds account for 74% of deaths; mean age=34 (range 15–81) years; 84% male. Cocaine overdoses account for two-thirds of cases; cocaine alone being mentioned/implicated in 23% in the UK. Opioids are involved in most (58%) cocaine overdose cases.

Suicide among drug addicts in the UK

1999 ◽  
Vol 175 (3) ◽  
pp. 277-282 ◽  
Author(s):  
Adenekan Oyefeso ◽  
Hamid Ghodse ◽  
Carmel Clancy ◽  
John M. Corkefy
Keyword(s):  
Drug Overdose ◽  
International Classification Of Diseases ◽  
Drug Addicts ◽  
Suicide Rates ◽  
Percentage Difference ◽  
Classification Of Diseases ◽  
Standardised Mortality Ratios ◽  
The Uk ◽  
Methods Of Suicide

BackgroundThe extent of suicide among addicts in the UK has not been sufficiently examined.AimsTo examine suicide trends among registered addicts in the UK over a 25-year period.MethodWe quantified suicide using International Classification of Diseases (ICD) external death codes E950–959, calculated annual age-standardised suicide rates, standardised mortality ratios (SMRs) and described trends in methods of suicide and drug overdose suicides in five successive cohorts of registered addicts.ResultsMale and female suicide rates are 69.0 and 44.8 per 100 000 person-years, respectively. There was a consistent decline in suicide rate throughout the 25-year period. Among males, the SMR for suicide declined from 17.2 in 1968–1972 to 4.4 in 1988–1992 (SMR ratio=3.9, 95% CI=2.5–6.1); among females it declined from 52.6 to 11.3 in the same period (SMR ratio=4.7, 95% CI=1.9–10.8). Drug overdose was the most common method of suicide, accounting for 45% of cases. Significant increase in antidepressant (percentage difference=23.5%, 95% CI=15.2–31.8) and methadone (percentage difference=1.0%, 95% CI=0.5, 21.5) overdose in 1988–1992 compared with 1968–1972 was reported.ConclusionsThe findings confirm that addicts are still at higher risk of suicide than the general population and that prescribed drugs, notably antidepressants and methadone, influence this heightened risk.

scholarly journals Developing and Evaluating Mappings of ICD-10 and ICD-10-CM Codes to PheCodes

2018 ◽  
Author(s):  
Patrick Wu ◽  
Aliya Gifford ◽  
Xiangrui Meng ◽  
Xue Li ◽  
Harry Campbell ◽  
...  
Keyword(s):  
Medical Center ◽  
Association Studies ◽  
International Classification Of Diseases ◽  
Snomed Ct ◽  
Unified Medical Language System ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
The Uk ◽  
Systematized Nomenclature Of Medicine

AbstractBackgroundThe PheCode system was built upon the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) for phenome-wide association studies (PheWAS) in the electronic health record (EHR).ObjectiveHere, we present our work on the development and evaluation of maps from ICD-10 and ICD-10-CM codes to PheCodes.MethodsWe mapped ICD-10 and ICD-10-CM codes to PheCodes using a number of methods and resources, such as concept relationships and explicit mappings from the Unified Medical Language System (UMLS), Observational Health Data Sciences and Informatics (OHDSI), Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT), and National Library of Medicine (NLM). We assessed the coverage of the maps in two databases: Vanderbilt University Medical Center (VUMC) using ICD-10-CM and the UK Biobank (UKBB) using ICD-10. We assessed the fidelity of the ICD-10-CM map in comparison to the gold-standard ICD-9-CM→PheCode map by investigating phenotype reproducibility and conducting a PheWAS.ResultsWe mapped >75% of ICD-10-CM and ICD-10 codes to PheCodes. Of the unique codes observed in the VUMC (ICD-10-CM) and UKBB (ICD-10) cohorts, >90% were mapped to PheCodes. We observed 70-75% reproducibility for chronic diseases and <10% for an acute disease. A PheWAS with a lipoprotein(a) (LPA) genetic variant, rs10455872, using the ICD-9-CM and ICD-10-CM maps replicated two genotype-phenotype associations with similar effect sizes: coronary atherosclerosis (ICD-9-CM: P < .001, OR = 1.60 vs. ICD-10-CM: P < .001, OR = 1.60) and with chronic ischemic heart disease (ICD-9-CM: P < .001, OR = 1.5 vs. ICD-10-CM: P < .001, OR = 1.47).ConclusionsThis study introduces the initial “beta” versions of ICD-10 and ICD-10-CM to PheCode maps that will enable researchers to leverage accumulated ICD-10 and ICD-10-CM data for high-throughput PheWAS in the EHR.

scholarly journals CAUSAS DE MORTALIDAD A CONSECUENCIA DE LA VEJEZ EN JEREZ DE LOS CABALLEROS (BADAJOZ, ESPAÑA) EN EL SIGLO XIX

2015 ◽  
Vol 63 (2) ◽  
pp. 229-234
Author(s):  
FRANCISCO JAVIER SUÁREZ GUZMÁN
Keyword(s):  
Mortality Rate ◽  
Cause Of Death ◽  
The Elderly ◽  
International Classification Of Diseases ◽  
Age Related ◽  
Historical Archives ◽  
Classification Of Diseases ◽  
Siglo Xix ◽  
Las Mujeres

<p><strong>RESUMEN</strong></p><p><strong>         </strong>Introducción:<strong> </strong>Según la Clasificación Internacional de Enfermedades de Bertillon de 1899, se han reunido las causas de defunción ocasionadas por la vejez en Jerez de los Caballeros (Badajoz) durante el siglo XIX.</p><p>Material y métodos: Se han recopilado un total de 26.203 defunciones de las cuales en 7.665 no consta la causa del fallecimiento, y sí en 18.538, para ello se han estudiado los Libros de Defunciones del Archivo Parroquial y legajos del Archivo Histórico.</p><p>Resultados: El primer difunto aparece el 28 de junio de 1808. Las tasas brutas de mortalidad específica promedian un 0,3‰. El término vejez fue cambiado a lo largo de los años, sobre todo al aumentar la esperanza de vida, pero continuaría la condición de marginado social del anciano.</p><p>Conclusiones: Las enfermedades relacionadas con el envejecimiento causaron 204 defunciones, el 1,1% del total de la mortalidad de la población durante el siglo XIX, correspondiendo a la decimosegunda causa de mortalidad en la población. La mayor mortalidad se da entre los 75 y 84 años con 85 defunciones (41,7%). Las mujeres presentan las cifras más elevadas 128 fallecimientos (62,7%). Enero es el mes con más óbitos.</p><p><strong>ABSTRACT</strong></p><p>Introduction: We have compiled the causes of age-related decease in Jerez de los Caballeros (Badajoz) during the 20th century following Bertillon’s International Classification of Diseases of 1899.</p><p>Materials and Methods: A total of 26.203 deceases has been found. For 7.665 of these no cause of death is recorded. We have consulted the Books of the Death, located in the Parish Archives, and files of the Historical Archives.</p><p>Results: The first decease appears on 28th June 1808. Gross specific mortality rates average 00,3‰. The application of the term old age changed with the passing of time, especially with the increase in life expectancy, but the elderly remain an object of social marginalization.</p><p>Conclusions: Age-related diseases caused 204 deceases, 1,1% of the total for the period under research, being the twelfth most frequent cause of death in the population. The highest mortality rate occurs between the ages of 75 and 84 (41%). Females have a higher mortality rate than males (128 deceases, 62,7%). January is the month with most deceases.</p><br /><p> </p><p> </p>

scholarly journals WikiMedMap: Expanding the Phenotyping Mapping Toolbox Using Wikipedia

2019 ◽  
Author(s):  
Lina Sulieman ◽  
Patrick Wu ◽  
Joshua C. Denny ◽  
Lisa Bastarache
Keyword(s):  
International Classification Of Diseases ◽  
Mendelian Inheritance ◽  
Medical Subject Headings ◽  
Phenotypic Data ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Conventional Mapping ◽  
The Uk ◽  
Omim Database

AbstractResearchers utilizing phenotypic data from diverse sources require matching of phenotypes to standard clinical vocabularies. Mapping phenotypes to vocabulary can be difficult, as existing tools are often incomplete, can be difficult to access, and can be cumbersome to use, especially for non-experts. We created WikiMedMap as a simple tool that leverages Wikipedia and maps phenotype strings to standard clinical vocabularies. We assessed WikiMedMap by mapping phenotype strings from questionnaires in the UK Biobank and from Mendelian diseases in Online Mendelian Inheritance in Man (OMIM) database to eight vocabularies: International Classification of Diseases, Ninth Revision (ICD-9), ICD-10, ICD-O, Medical Subject Headings (MeSH), OMIM, Disease Database, and MedlinePlus. WikiMedMap outperformed conventional mapping tools in finding potential matches for phenotype strings. We envision WikiMedMap as a technique that complements existing and established tools to map strings to clinical vocabularies that usually do not coexist in one source.

scholarly journals Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation

10.2196/14325 ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. e14325 ◽  
Author(s):  
Patrick Wu ◽  
Aliya Gifford ◽  
Xiangrui Meng ◽  
Xue Li ◽  
Harry Campbell ◽  
...  
Keyword(s):  
Medical Center ◽  
Association Studies ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Initial Evaluation ◽  
Unified Medical Language System ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
The Uk

Background The phecode system was built upon the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) for phenome-wide association studies (PheWAS) using the electronic health record (EHR). Objective The goal of this paper was to develop and perform an initial evaluation of maps from the International Classification of Diseases, 10th Revision (ICD-10) and the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes to phecodes. Methods We mapped ICD-10 and ICD-10-CM codes to phecodes using a number of methods and resources, such as concept relationships and explicit mappings from the Centers for Medicare & Medicaid Services, the Unified Medical Language System, Observational Health Data Sciences and Informatics, Systematized Nomenclature of Medicine-Clinical Terms, and the National Library of Medicine. We assessed the coverage of the maps in two databases: Vanderbilt University Medical Center (VUMC) using ICD-10-CM and the UK Biobank (UKBB) using ICD-10. We assessed the fidelity of the ICD-10-CM map in comparison to the gold-standard ICD-9-CM phecode map by investigating phenotype reproducibility and conducting a PheWAS. Results We mapped >75% of ICD-10 and ICD-10-CM codes to phecodes. Of the unique codes observed in the UKBB (ICD-10) and VUMC (ICD-10-CM) cohorts, >90% were mapped to phecodes. We observed 70-75% reproducibility for chronic diseases and <10% for an acute disease for phenotypes sourced from the ICD-10-CM phecode map. Using the ICD-9-CM and ICD-10-CM maps, we conducted a PheWAS with a Lipoprotein(a) genetic variant, rs10455872, which replicated two known genotype-phenotype associations with similar effect sizes: coronary atherosclerosis (ICD-9-CM: P<.001; odds ratio (OR) 1.60 [95% CI 1.43-1.80] vs ICD-10-CM: P<.001; OR 1.60 [95% CI 1.43-1.80]) and chronic ischemic heart disease (ICD-9-CM: P<.001; OR 1.56 [95% CI 1.35-1.79] vs ICD-10-CM: P<.001; OR 1.47 [95% CI 1.22-1.77]). Conclusions This study introduces the beta versions of ICD-10 and ICD-10-CM to phecode maps that enable researchers to leverage accumulated ICD-10 and ICD-10-CM data for PheWAS in the EHR.

scholarly journals Comparative evaluation of underlying causes of death processed by the Automated Classification of Medical Entities and the Underlying Cause of Death Selection Systems

1998 ◽  
Vol 32 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Augusto H. Santo ◽  
Celso E. Pinheiro ◽  
Eliana M. Rodrigues
Keyword(s):  
Cause Of Death ◽  
Comparative Evaluation ◽  
Causes Of Death ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Automated Classification ◽  
Classification Of Diseases ◽  
Underlying Causes ◽  
Underlying Cause Of Death

INTRODUCTION: The correct identification of the underlying cause of death and its precise assignment to a code from the International Classification of Diseases are important issues to achieve accurate and universally comparable mortality statistics These factors, among other ones, led to the development of computer software programs in order to automatically identify the underlying cause of death. OBJECTIVE: This work was conceived to compare the underlying causes of death processed respectively by the Automated Classification of Medical Entities (ACME) and the "Sistema de Seleção de Causa Básica de Morte" (SCB) programs. MATERIAL AND METHOD: The comparative evaluation of the underlying causes of death processed respectively by ACME and SCB systems was performed using the input data file for the ACME system that included deaths which occurred in the State of S. Paulo from June to December 1993, totalling 129,104 records of the corresponding death certificates. The differences between underlying causes selected by ACME and SCB systems verified in the month of June, when considered as SCB errors, were used to correct and improve SCB processing logic and its decision tables. RESULTS: The processing of the underlying causes of death by the ACME and SCB systems resulted in 3,278 differences, that were analysed and ascribed to lack of answer to dialogue boxes during processing, to deaths due to human immunodeficiency virus [HIV] disease for which there was no specific provision in any of the systems, to coding and/or keying errors and to actual problems. The detailed analysis of these latter disclosed that the majority of the underlying causes of death processed by the SCB system were correct and that different interpretations were given to the mortality coding rules by each system, that some particular problems could not be explained with the available documentation and that a smaller proportion of problems were identified as SCB errors. CONCLUSION: These results, disclosing a very low and insignificant number of actual problems, guarantees the use of the version of the SCB system for the Ninth Revision of the International Classification of Diseases and assures the continuity of the work which is being undertaken for the Tenth Revision version.

scholarly journals A NICE game of Minecraft: philosophical flaws underpinning UK depression guideline nosology

2019 ◽  
Vol 46 (3) ◽  
pp. 162-165 ◽  
Author(s):  
Susan McPherson
Keyword(s):  
Mental Disorders ◽  
Treatment Options ◽  
International Classification Of Diseases ◽  
Building Structures ◽  
Diagnostic And Statistical Manual ◽  
Classification Of Diseases ◽  
Persistent Depression ◽  
The Uk ◽  
Heuristic Devices

Categorising mental disorders for purposes of diagnosis, research and practice has historically been justified on philosophical terms as a pragmatic activity; categories which have been subject to wide-ranging philosophical critique have been defended on the grounds that they serve as heuristic devices providing loose representations of shared experiences, not labels for real structures. In acknowledgement of this, there has been increasing recognition that subclassifying multiple discrete forms of persistent depression moves too far away from the notion of a heuristic and that attempts to create more precise categories become less clinically useful. Hence the most recent Diagnostic and Statistical Manual of Mental Disorders (V.5) and International Classification of Diseases (V.11) both group persistent forms of depression together. However, the UK National Institute for Health and Care Excellence has delineated certain subclassifications of persistent depression in its new guideline, which grossly distorts the phenomenology of depression. This approach commits a fundamental philosophical error in conflating absence of knowledge with knowledge of absence. In this sense, the new guideline appears to be engaging in an activity akin to the digital game Minecraft, in which the craft of building structures from units of construction is largely divorced from the laws of physics. The risk of ignoring these philosophical errors and making false claims about scientific plausibility is that the guideline recommendations inevitably represent a highly distorted phenomenology of depression and will be of very little value to patients or practitioners looking for guidance on best possible treatment options.

Comparison of Alcohol Use Disorders in DSM and ICD

2020 ◽  
Vol 66 (3) ◽  
pp. 143-153
Author(s):  
Jessica W. M. Wong ◽  
Friedrich M. Wurst ◽  
Ulrich W. Preuss
Keyword(s):  
Alcohol Use Disorders ◽  
International Classification Of Diseases ◽  
Clinical Use ◽  
Diagnostic Systems ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5 ◽  
Classification Of Diseases ◽  
Historical Developments

Abstract. Introduction: With advances in medicine, our understanding of diseases has deepened and diagnostic criteria have evolved. Currently, the most frequently used diagnostic systems are the ICD (International Classification of Diseases) and the DSM (Diagnostic and Statistical Manual of Mental Disorders) to diagnose alcohol-related disorders. Results: In this narrative review, we follow the historical developments in ICD and DSM with their corresponding milestones reflecting the scientific research and medical considerations of their time. The current diagnostic concepts of DSM-5 and ICD-11 and their development are presented. Lastly, we compare these two diagnostic systems and evaluate their practicability in clinical use.

Angststörungen – von der ICD-10 zur ICD-11

2020 ◽  
pp. 1-5
Author(s):  
Timo D. Vloet ◽  
Marcel Romanos
Keyword(s):  
Mental Disorders ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5 ◽  
Classification Of Diseases ◽  
Icd 10

Zusammenfassung. Hintergrund: Nach 12 Jahren Entwicklung wird die 11. Version der International Classification of Diseases (ICD-11) von der Weltgesundheitsorganisation (WHO) im Januar 2022 in Kraft treten. Methodik: Im Rahmen eines selektiven Übersichtsartikels werden die Veränderungen im Hinblick auf die Klassifikation von Angststörungen von der ICD-10 zur ICD-11 zusammenfassend dargestellt. Ergebnis: Die diagnostischen Kriterien der generalisierten Angststörung, Agoraphobie und spezifischen Phobien werden angepasst. Die ICD-11 wird auf Basis einer Lebenszeitachse neu organisiert, sodass die kindesaltersspezifischen Kategorien der ICD-10 aufgelöst werden. Die Trennungsangststörung und der selektive Mutismus werden damit den „regulären“ Angststörungen zugeordnet und können zukünftig auch im Erwachsenenalter diagnostiziert werden. Neu ist ebenso, dass verschiedene Symptomdimensionen der Angst ohne kategoriale Diagnose verschlüsselt werden können. Diskussion: Die Veränderungen im Bereich der Angsterkrankungen umfassen verschiedene Aspekte und sind in der Gesamtschau nicht unerheblich. Positiv zu bewerten ist die Einführung einer Lebenszeitachse und Parallelisierung mit dem Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Schlussfolgerungen: Die entwicklungsbezogene Neuorganisation in der ICD-11 wird auch eine verstärkte längsschnittliche Betrachtung von Angststörungen in der Klinik sowie Forschung zur Folge haben. Damit rückt insbesondere die Präventionsforschung weiter in den Fokus.

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