Complex PTSD symptom clusters and executive function in UK Armed Forces veterans: a cross-sectional study.

BACKGROUND: Less is known about complex posttraumatic stress disorder (CPTSD) than postrraumatic stress disorder (PTSD) in military veterans, yet this population may be at greater risk of the former diagnosis. Executive function impairment has been linked to PTSD treatment outcomes. The current study therefore aimed to explore possible associations between each CPTSD symptom cluster and executive function to understand if similar treatment trajectories might be observed with the disorder. METHODS: A total of 428 veterans from a national charity responded to a self-report questionnaire which measured CPTSD symptom clusters using the International Trauma Questionnaire, and executive function using the Adult Executive Function Inventory. Single and multiple linear regression models were used to analyse the relationship between CPTSD symptom clusters and executive function, including working memory and inhibition. RESULTS: Each CPTSD symptom cluster was significantly associated with higher executive function impairment, even after controlling for possible mental health confounding variables. Emotion dysregulation was the CPTSD symptom cluster most strongly associated with executive function impairment. CONCLUSIONS: This is the first study to explore the relationship between executive function and CPTSD symptom clusters. The study builds on previous findings and suggests that executive function could be relevant to CPTSD treatment trajectories, as is the case with PTSD alone. Future research should further explore such clinical implications.

Validity of ICD-10-based algorithms to identify patients with influenza in inpatient and outpatient settings.

PURPOSE: To evaluate the validity of ICD-10-CM code-based algorithms as proxies for influenza in inpatient and outpatient settings in the USA. METHODS: Administrative claims data (2015-2018) from the largest commercial insurer in New Jersey (NJ), USA, were probabilistically linked to outpatient and inpatient electronic health record (EHR) data containing influenza test results from a large NJ health system. The primary claims-based algorithms defined influenza as presence of an ICD-10-CM code for influenza, stratified by setting (inpatient/outpatient) and code position for inpatient encounters. Test characteristics and 95% confidence intervals (CIs) were calculated using test-positive influenza as a reference standard. Test characteristics of alternative outpatient algorithms incorporating CPT/HCPCS testing codes and anti-influenza medication pharmacy claims were also calculated. RESULTS: There were 430 documented influenza test results within the study period (295 inpatient, 135 outpatient). The claims-based influenza definition had a sensitivity of 84.9% (95% CI 72.9%-92.1%), specificity of 96.3% (95% CI 93.1%-98.0%), and PPV of 83.3% (95% CI 71.3%-91.0%) in the inpatient setting, and a sensitivity of 76.7% (95% CI 59.1%-88.2%), specificity of 96.2% (95% CI 90.6%-98.5%), PPV of 85.2% (95% CI 67.5%-94.1%) in the outpatient setting. Primary inpatient discharge diagnoses had a sensitivity of 54.7% (95% CI 41.5%-67.3%), specificity of 99.6% (95% CI 97.7%-99.9%), and PPV of 96.7% (95% CI 83.3%-99.4%). CPT/HCPCS codes and anti-influenza medication claims were present for few outpatient encounters (sensitivity 3%-10%). CONCLUSIONS: In a large US healthcare system, inpatient ICD-10-CM codes for influenza, particularly primary inpatient diagnoses, had high predictive value for test-positive influenza. Outpatient ICD-10-CM codes were moderately predictive of test-positive influenza.

Validation of alopecia coding in US claims data among women of childbearing age.

BACKGROUND: Accurately identifying alopecia in claims data is important to study this rare medication side effect. OBJECTIVES: To develop and validate a claims-based algorithm to identify alopecia in women of childbearing age. METHODS: We linked electronic health records from a large healthcare system in Massachusetts (Mass General Brigham) with Medicaid claims data from 2016 through 2018 to identify all women aged 18 to 50 years with an ICD-10 code for alopecia, including alopecia areata, androgenic alopecia, non-scarring alopecia, or cicatricial alopecia, from a visit to the MGB system. Using eight predefined algorithms to identify alopecia in Medicaid claims data, we randomly selected 300 women for whom we reviewed their charts to validate the alopecia diagnosis. Positive predictive values (PPVs) were computed for the primary algorithm and seven algorithm variations, stratified by race. RESULTS: Out of 300 patients with at least 1 ICD-10 code for alopecia in the Medicaid claims, 286 had chart-confirmed alopecia (PPV = 95.3%). The algorithm requiring two diagnosis codes plus one prescription claim for alopecia treatment identified 55 patients (PPV = 100%). The algorithm requiring 1 diagnosis code for alopecia plus 1 procedure claim for intralesional triamcinolone injection identified 35 patients (PPV = 100%). Across all 8 algorithms tested, the PPV varied between 95.3% and 100%. The PPV for alopecia ranged from 94% to 100% in White and 96%-100% in 48 non-White women. The exact date of alopecia onset was difficult to determine in charts. CONCLUSION: At least one recorded ICD-10 code for alopecia in claims data identified alopecia in women of childbearing age with high accuracy.

Los trastornos de la personalidad ¿realidad o ficción? El sombrío futuro de su diagnóstico / Personality disorders: reality or fiction? The bleak future of your diagnosis

El diagnóstico categorial de los trastornos de la personalidad (TTPP) ha sido criticado por diversas razones, entras las que se encuentran el solapamiento de síntomas entre distintos trastornos, su elevada comorbilidad o el carácter dicotómico de su diagnóstico. Estas críticas han llevado al desarrollo de un planteamiento dimensional en las últimas versiones de los sistemas de clasificación, DSM-5/DSM-5-TR y CIE-11, considerando dos aspectos: el funcionamiento de la personalidad y una serie de rasgos patológicos. A pesar de la cuantiosa literatura publicada desde principio de este siglo sobre esta propuesta dimensional, no está claro, a día de hoy, que tenga alguna utilidad clínica. La vaga, abstracta y poco operativizable exposición de lo que constituye el funcionamiento de la personalidad y la compleja y forzada designación de rasgos mayores y menores (facetas) en el DSM-5/DSM-5-TR o sólo mayores y opcionales en la CIE-11, complican el diagnóstico dimensional de los TTPP. En este trabajo se discuten todas estas cuestiones en un intento de aportar algo de luz para un futuro menos sombrío que el actual panorama de los TTPP.(AU)

The categorical diagnosis of personality disorders (PDs) has been criticized forvarious reasons, among which are overlapping of symptoms between differentdisorders, their high comorbidity, and the dichotomous nature of their diagnosis.These criticisms have led to the development of a dimensional approach in thelatest versions of the classification systems, DSM-5/DSM-5-TR and ICD-11,considering two substantial aspects for its new diagnosis: personality functioning,and a series of pathological features. Despite the large amount of literature thathas been published since the beginning of this century on this dimensionalproposal, it is not clear, to date, that this approach enhances clinical utility. Thevague, abstract, and inoperative exposition of what constitutes personalityfunctioning and the complex and forced designation of major and minor traits(facets) in the DSM-5/DSM-5-TR, and only major and optional traits in the ICD-11,complicate, in an unusual way, the dimensional diagnosis of PDs. This paperdiscusses all of these issues in an attempt to shed some light on the potentially darkfuture of the current PDs panorama.(AU)

International Classification of Diseases Coding for Inflammatory Arthritides.

This quality improvement study investigates usage patterns of codes for inflammatory arthritides under International Statistical Classification of Diseases and Related Health Problems, Tenth Revision vs International Classification of Diseases, Ninth Revision.

Automatic inference of ICD-10 codes from German ophthalmologic physicians' letters using natural language processing.

Physicians' letters are the optimal source of diagnoses for registries. However, most registries demand for diagnosis codes such as ICD-10. We herein describe an algorithm that infers ICD-10 codes from German ophthalmologic physicians' letters. We assess the method in three German eye hospitals. Our algorithm is based on the nearest-neighbor method as well as on a large thesaurus for ICD-10 codes. This thesaurus was embedded into a Word2Vec space created from anonymized physicians' reports of the first hospital. For evaluation, each of the three hospitals sent all diagnoses taken from 100 letters. The inferred ICD-10 codes were evaluated for correctness by the senders. A total of 3332 natural language terms had been sent in (812 hospital one, 1473 hospital two, 1047 hospital three). A total of 526 non-diagnoses were excluded upfront. 2806 ICD-10 codes were inferred (771 hospital one, 1226 hospital two, 809 hospital three). In the first hospital, 98% were fully correct and 99% correct at the level of the superordinate disease concept. The percentages in hospital two were 69% and 86%. The respective numbers for hospital three were 69% and 91%. Our simple method is capable of inferring ICD-10 codes for German natural language diagnoses, especially when the embedding space has been built with physicians' letters from the same hospital. The method may yield sufficient accuracy for many tasks in the multi-centric setting and can easily be adapted to other languages/specialities.

Driver's Licensure and Driving Outcomes Among Youths With Mood Disorders.

Importance: Mood disorders are prevalent among adolescents and young adults, and their onset often coincides with driving eligibility. The understanding of how mood disorders are associated with youth driving outcomes is limited. Objective: To examine the association between the presence of a mood disorder and rates of licensing, crashes, violations, and suspensions among adolescents and young adults. Design, Setting, and Participants: This cohort study was conducted among New Jersey residents who were born 1987 to 2000, age eligible to acquire a driver's license from 2004 to 2017, and patients of the Children's Hospital of Philadelphia network within 2 years of licensure eligibility at age 17 years. The presence of a current (ie, ≤2 years of driving eligibility) mood disorder was identified using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) or International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes. Rates of licensure and driving outcomes among youths who were licensed were compared among 1879 youths with and 84 294 youths without a current mood disorder from 2004 to 2017. Data were analyzed from June 2022 to July 2023. Main Outcomes and Measures: Acquisition of a driver's license and first involvement as a driver in a police-reported crash and rates of other adverse driving outcomes were assessed. Survival analysis was used to estimate adjusted hazard ratios (aHRs) for licensing and driving outcomes. Adjusted rate ratios (aRRs) were estimated for driving outcomes 12 and 48 months after licensure. Results: Among 86 173 youths (median [IQR] age at the end of the study, 22.8 [19.7-26.5] years; 42 894 female [49.8%]), there were 1879 youths with and 84 294 youths without a mood disorder. A greater proportion of youths with mood disorders were female (1226 female [65.2%]) compared with those without mood disorders (41 668 female [49.4%]). At 48 months after licensure eligibility, 75.5% (95% CI, 73.3%-77.7%) and 83.8% (95% CI, 83.5%-84.1%) of youths with and without mood disorders, respectively, had acquired a license. Youths with mood disorders were 30% less likely to acquire a license than those without a mood disorder (aHR, 0.70 [95% CI, 0.66-0.74]). Licensed youths with mood disorders had higher overall crash rates than those without mood disorders over the first 48 months of driving (137.8 vs 104.8 crashes per 10 000 driver-months; aRR, 1.19 [95% CI, 1.08-1.31]); licensed youths with mood disorders also had higher rates of moving violations (aRR, 1.25 [95% CI, 1.13-1.38]) and license suspensions (aRR, 1.95 [95% CI, 1.53-2.49]). Conclusions and Relevance: This study found that youths with mood disorders were less likely to be licensed and had higher rates of adverse driving outcomes than youths without mood disorders. These findings suggest that opportunities may exist to enhance driving mobility in this population and elucidate the mechanisms by which mood disorders are associated with crash risk.

Review of codelists used to define hypertension in electronic health records and development of a codelist for research.

BACKGROUND AND AIMS: Hypertension is a leading risk factor for cardiovascular disease. Electronic health records (EHRs) are routinely collected throughout a person's care, recording all aspects of health status, including current and past conditions, prescriptions and test results. EHRs can be used for epidemiological research. However, there are nuances in the way conditions are recorded using clinical coding; it is important to understand the methods which have been applied to define exposures, covariates and outcomes to enable interpretation of study findings. This study aimed to identify codelists used to define hypertension in studies that use EHRs and generate recommended codelists to support reproducibility and consistency. ELIGIBILITY CRITERIA: Studies included populations with hypertension defined within an EHR between January 2010 and August 2023 and were systematically identified using MEDLINE and Embase. A summary of the most frequently used sources and codes is described. Due to an absence of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) codelists in the literature, a recommended SNOMED CT codelist was developed to aid consistency and standardisation of hypertension research using EHRs. FINDINGS: 375 manuscripts met the study criteria and were eligible for inclusion, and 112 (29.9%) reported codelists. The International Classification of Diseases (ICD) was the most frequently used clinical terminology, 59 manuscripts provided ICD 9 codelists (53%) and 58 included ICD 10 codelists (52%). Informed by commonly used ICD and Read codes, usage recommendations were made. We derived SNOMED CT codelists informed by National Institute for Health and Care Excellence guidelines for hypertension management. It is recommended that these codelists be used to identify hypertension in EHRs using SNOMED CT codes. CONCLUSIONS: Less than one-third of hypertension studies using EHRs included their codelists. Transparent methodology for codelist creation is essential for replication and will aid interpretation of study findings. We created SNOMED CT codelists to support and standardise hypertension definitions in EHR studies.

Using a data-driven approach to define post-COVID conditions in US electronic health record data.

OBJECTIVE: To create a data-driven definition of post-COVID conditions (PCC) by directly measure changes in symptomatology before and after a first COVID episode. MATERIALS AND METHODS: Retrospective cohort study using Optum® de-identified Electronic Health Record (EHR) dataset from the United States of persons of any age April 2020-September 2021. For each person with COVID (ICD-10-CM U07.1 "COVID-19" or positive test result), we selected up to 3 comparators. The final COVID symptom score was computed as the sum of new diagnoses weighted by each diagnosis' ratio of incidence in COVID group relative to comparator group. For the subset of COVID cases diagnosed in September 2021, we compared the incidence of PCC using our data-driven definition with ICD-10-CM code U09.9 "Post-COVID Conditions", first available in the US October 2021. RESULTS: The final cohort contained 588,611 people with COVID, with mean age of 48 years and 38% male. Our definition identified 20% of persons developed PCC in follow-up. PCC incidence increased with age: (7.8% of persons aged 0-17, 17.3% aged 18-64, and 33.3% aged 65+) and did not change over time (20.0% among persons diagnosed with COVID in 2020 versus 20.3% in 2021). For cases diagnosed in September 2021, our definition identified 19.0% with PCC in follow-up as compared to 2.9% with U09.9 code in follow-up. CONCLUSION: Symptom and U09.9 code-based definitions alone captured different populations. Maximal capture may consider a combined approach, particularly before the availability and routine utilization of specific ICD-10 codes and with the lack consensus-based definitions on the syndrome.

Prevalence and correlates of ICD-11 prolonged grief disorder among adults living in Ukraine during the war with Russia.

BACKGROUND: Although high rates of bereavement are evident in war-affected populations, no study has investigated the prevalence and correlates of probable ICD-11 prolonged grief disorder (PGD) under these circumstances. METHODS: Participants were 2050 adults who participated in a nationwide survey exploring the effects of the Ukraine-Russia war on the daily lives and mental health of Ukrainian people. RESULTS: Of the total sample, 87.7% (n = 1797) of people indicated a lifetime bereavement. In the full sample, 11.4% met the diagnostic requirements for probable ICD-11 PGD, and amongst those with a lifetime bereavement, the conditional rate of probable ICD-11 PGD was 13.0%. Significant risk factors of ICD-11 PGD included the recent loss of a loved one (6 months to a year ago), being most affected by a partner or spouse's death, loved one dying in the war, no recent contact with the deceased prior to their death, and meeting depression and anxiety diagnostic requirements. CONCLUSION: The study reveals that a significant percentage of Ukrainian bereaved individuals have probable ICD-11 PGD, and identifying risk factors, particularly war-related losses, will aid in the development of intervention and prevention programs for bereaved adults.

Development of the complex trauma screener: A brief measure of ICD-11 PTSD and complex PTSD.

The purpose of this study was to develop the Complex Trauma Screener (CTS), a brief screener (seven items) of the ICD-11 trauma disorders that can be used in "quick-paced" facilities. We examined the factor structure of the CTS in two separate samples: civilian college students (N = 823) and military veterans (N = 130) who reported exposure to at least one traumatic event. Confirmatory factor analyses (CFAs) supported two highly-correlated factors (post-traumatic stress disorder [PTSD] and Disturbances in Self-Organization [DSO]) that loaded on the ICD-11-consistent items. The model fit indices indicated good to excellent model fit in both samples, and the internal consistencies for the scales were borderline to good (α = 0.68-0.86). Supplementary analyses supported the gender invariance of the CFA model in the civilian student sample, as well as convergent (with another trauma inventory) and discriminant validity (with borderline disorder features, depression, and mania) of the CTS in both samples. The CTS is, to our knowledge, the shortest instrument designed to measure the ICD-11 trauma disorders and is ideal for "fast-paced" facilities that have significant assessment time restraints. The CTS is, therefore, is a psychometrically-validated instrument that can help mental health professionals efficiently screen adults for ICD-11 trauma disorders.

The Association Between Metformin Use and New-Onset ICD Coding of Geographic Atrophy.

Purpose: Metformin has been suggested to protect against the development of age-related macular degeneration (AMD) in multiple observational studies. However, the association between metformin and geographic atrophy (GA), a debilitating subtype of AMD, has not been analyzed. Methods: We conducted a case-control study of patients ages 60 years and older with new-onset International Classification of Diseases (ICD) coding of GA in the Merative MarketScan Commercial and Medicare Databases between 2017 and 2021. Cases were matched with propensity scores estimated by age, region, hypertension, and Charlson Comorbidity Index to a control without GA of the same year. Exposure to metformin was assessed for cases and controls in the year prior to their index visit. Conditional multivariable logistic regression, adjusting for AMD risk factors, was used to calculate odd ratios and 95% confidence intervals (CIs). This study design and analysis were repeated in a sample of patients without diabetes. Results: In the full sample, we identified 10,505 cases with GA and 10,502 matched controls without GA. In total, 1149 (10.9%) cases and 1277 (12.2%) controls were exposed to metformin, and in multivariable regression, metformin decreased the odds of new-onset ICD coding of GA by 12% (95% CI, 0.79-0.99). In the sample of patients without diabetes, we identified 7611 cases with GA and 7608 matched controls without GA. Twenty-nine (0.4%) cases and 63 (0.8%) controls were exposed to metformin, and in multivariable regression, metformin decreased the odds of new-onset ICD coding of GA by 47% (95% CI, 0.33-0.83). Conclusions: Metformin may hold promise as a noninvasive, alternative agent to prevent the development of GA. This finding is notable due to shortcomings in recently approved therapeutics for GA and metformin's overall ease of use and few adverse effects. Additional studies are required to explore our findings further and motivate a clinical trial.

Can personality disorder be accurately assessed in older age? A differential item functioning analysis of ICD-11 inventories.

OBJECTIVES: The contested categorical personality disorder (PD) criteria are not well suited to inform PD diagnoses in older adults. Yet, the classification of PDs is undergoing a critical transition phase with a paradigm shift to a dimensional approach for diagnosing PDs. No special attention was given to the expression of PDs in older age when the dimensional ICD-11 model was developed. Given that PDs are highly prevalent in older adults, there is an urgent need to examine if ICD-11 related instruments are able to adequately assess for PDs in older adults. METHODS: The age-neutrality of ICD-11 measures was examined in a sample of 208 Dutch community-dwelling adults (N = 208, M age = 54.96, SD = 21.65), matched on sex into 104 younger (age range 18-64) and 104 older (age range 65-93) adults. An instrument is considered not to be age-neutral if a collective large level of differential item functioning (DIF) exists in a group of items of an instrument (i.e., 25% or more with DIF). We therefore set out to detect possible DIF in the following ICD-11 self-report measures: the Standardized Assessment of Severity of Personality Disorder (SASPD), the Personality Inventory for ICD-11 (PiCD), and the Borderline Pattern Scale (BPS). RESULTS: DIF analyses using a non-parametric odds ratio approach demonstrated that SASPD, PiCD, and BPS were age-neutral with less than 25% of items showing DIF. Yet, impact of DIF at scale level, examined by way of differential test functioning (DTF), indicated a DTF effect on the SASPD total score. CONCLUSIONS: These results of age-neutrality of the PiCD and BPS are promising for measuring ICD-11 traits and the borderline pattern. Yet, the age-neutral measurement of PD severity requires further research. With a rapidly aging population, its accurate assessment across the entire adult life span, including older age, is a prerequisite for an adequate detection of PDs.

Practical implications of ICD-11 personality disorder classifications.

Personality disorders (PDs) are associated with an inferior quality of life, poor health, and premature mortality, leading to heavy clinical, familial, and societal burdens. The International Classification of Diseases-11 (ICD-11) makes a thorough, dramatic paradigm shift from the categorical to dimensional diagnosis of PD and expands the application into adolescence. We have reviewed the recent literature on practical implications, and severity and trait measures of ICD-11 defined PDs, by comparing with the alternative model of personality disorders in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), by mentioning the relevance in forensic and social concerns, and by referencing the developmental implication of life span, especially in adolescence. Study results strongly support the dimensional utility of ICD-11 PD diagnosis and application in adolescence which warrants early detection and intervention. More evidence-based research is needed along the ICD-11 PD application, such as its social relevance, measurement simplification, and longitudinal design of lifespan observation and treatment.

Case identification of non-traumatic brain injury in youth using linked population data.

BACKGROUND: Population-level administrative data provides a cost-effective means of monitoring health outcomes and service needs of clinical populations. This study aimed to present a method for case identification of non-traumatic brain injury in population-level data and to examine the association with sociodemographic factors. METHODS: An estimated resident population of youth aged 0-24 years was constructed using population-level datasets within the New Zealand Integrated Data Infrastructure. A clinical consensus committee reviewed the International Classification of Diseases Ninth and Tenth Editions codes and Read codes for inclusion in a case definition. Cases were those with at least one non-traumatic brain injury code present in the five years up until 30 June 2018 in one of four databases in the Integrated Data Infrastructure. Rates of non-traumatic brain injury were examined, both including and excluding birth injury codes and across age, sex, ethnicity, and socioeconomic deprivation groups. RESULTS: Of the 1 579 089 youth aged 0-24 years on 30 June 2018, 8154 (0.52%) were identified as having one of the brain injury codes in the five-years to 30 June 2018. Rates of non-traumatic brain injury were higher in males, children aged 0-4 years, Maori and Pacific young people, and youth living with high levels of social deprivation. CONCLUSION: This study presents a comprehensive method for case identification of non-traumatic brain injury using national population-level administrative data.

Methodologies and key considerations for implementing the International Classification of Diseases-11th revision morbidity coding: insights from a national pilot study in China.

OBJECTIVE: The aim of this study was to disseminate insights from a nationwide pilot of the International Classification of Diseases-11th revision (ICD-11). MATERIALS AND METHODS: The strategies and methodologies employed to implement the ICD-11 morbidity coding in 59 hospitals in China are described. The key considerations for the ICD-11 implementation were summarized based on feedback obtained from the pilot hospitals. Coding accuracy and Krippendorff's alpha reliability were computed based on the coding results in the ICD-11 exam. RESULTS: Among the 59 pilot hospitals, 58 integrated ICD-11 Coding Software into their health information management systems and 56 implemented the ICD-11 in morbidity coding, resulting in 3 723 959 diagnoses for 873 425 patients being coded over a 2-month pilot coding phase. The key considerations in the transition to the ICD-11 in morbidity coding encompassed the enrichment of ICD-11 content, refinement of tools, provision of systematic and tailored training, improvement of clinical documentation, promotion of downstream data utilization, and the establishment of a national process and mechanism for implementation. The overall coding accuracy was 82.9% when considering the entire coding field (including postcoordination) and 92.2% when only one stem code was considered. Krippendorff's alpha was 0.792 (95% CI, 0.788-0.796) and 0.799 (95% CI, 0.795-0.803) with and without consideration of the code sequence, respectively. CONCLUSION: This nationwide pilot study has enhanced national technical readiness for the ICD-11 implementation in morbidity, elucidating key factors warranting careful consideration in future endeavors. The good accuracy and intercoder reliability of the ICD-11 coding achieved following a brief training program underscore the potential for the ICD-11 to reduce training costs and provide high-quality health data. Experiences and lessons learned from this study have contributed to WHO's work on the ICD-11 and can inform other countries when formulating their transition plan.

Administrative data ICD-10 diagnostic codes identifies most lab-confirmed SARS-CoV-2 admissions but misses many discharged from the Emergency Department.

We estimated the operating characteristics of ICD-10 code U07.1, introduced by the World Health Organization in 2020, to identify lab-confirmed SARS-CoV-2. CCEDRRN is a national research registry of adults (March 2020-August 2021) with suspected/confirmed SARS-CoV-2 identified in Canadian emergency departments (EDs) using chart review (symptoms, clinical information, and lab test results including SARS-CoV-2 polymerase chain reaction, PCR results). CCEDRRN data were linked to administrative hospitalization discharge and ED ICD-10 diagnostic codes (accessed centrally via the Canadian Institute for Health Information). We identified ICD-10 diagnostic codes in CCEDRRN participants. We defined lab-confirmed SARS-CoV-2 based on at least one positive PCR in the 0-14 days before the ED presentation and/or during hospitalization (in those admitted from ED). We performed separate analyses for CCEDRRN participants discharged from ED and those hospitalized from the ED. Additional analyses were stratified by province, sex, age, and (for hospitalized patients) timing of the first PCR test. The sensitivity of ICD-10 code U07.1 for a positive SARS-CoV-2 test was 93.6% (95% CI 93.0-94.1%) in those hospitalized from ED and 83.0% (95% CI 82.1-83.9%) in those discharged from the ED. Sensitivity was similar across provinces and demographics, but in each stratified analysis, values were higher in those hospitalized versus those discharged from ED. The ICD-10 diagnostic code for U07.1 within administrative data identified most lab-confirmed SARS-CoV-2 within persons hospitalized from ED, although a significant number of cases discharged from ED were missed. This should be considered when using administrative data for research and public health planning.

Comparison of injury severity scores derived from ICD-10-AM codes with trauma registry derived scores: A study from New Zealand.

INTRODUCTION: Various attempts at automation have been made to reduce the administrative burden of manually assigning Abbreviated Injury Severity (AIS) codes to derive Injury Severity Scores (ISS) in trauma registry data. The accuracy of the resulting measures remains unclear, especially in the New Zealand (NZ) context. The aim of this study was to compare ISS derived from hospital discharge International Classification of Diseases Australian Modification (ICD-10-AM) codes with ISS recorded in the NZ Trauma Registry (NZTR). METHODS: Individuals admitted to hospital and enrolled in the NZTR between 1 December 2016 and 30 November 2018 were included. ISS were calculated using a modified ICD to AIS mapping tool. The agreement between both methods for raw scores was assessed by the Intraclass Correlation Coefficient (ICC), and for categorical scores the Kappa and weighted Kappa index were used. Analysis was conducted by gender, age, ethnicity, and mechanism of injury. RESULTS: 3,156 patients fulfilled the inclusion criteria. The ICC for agreement between the methods was poor (0.40, 95 % CI: 0.37-0.43). The Kappa index indicated slight agreement between both methods when using a cut-off value of 12 (0.06; 95 % CI: 0.01-0.12) and 15 (0.13 6; 95 % CI: 0.09-0.17). CONCLUSION: Although the overall agreement between NZTR-ISS and ICD-ISS was slight, ICD-derived scores may be useful to describe injury patterns and for body region-specific estimations when manually coded ISS are not available.

[Posttraumatic stress disorder in children and adolescents: results of a cross-sectional study on the effects of the newly formulated PTSD and CPTSD diagnoses in the ICD-11]. / Posttraumatische Belastungsstörung bei Kindern und Jugendlichen: Ergebnisse einer Querschnittsstudie zu Auswirkungen der neu formulierten Diagnosen PTBS und kPTBS in der ICD-11.

BACKGROUND: ICD-11 presents narrowed criteria for posttraumatic stress disorder (PTSD) and introduces complex PTSD (CPTSD) with additional difficulties in self-organization (DSO). These changes can have significant effects on the frequency of the diagnosis. The aim of this study was to investigate which ICD-11 symptom clusters cause children and adolescents to miss the diagnosis and whether caregivers are more likely to attribute changes in DSO to developmental level or to the traumatic event, and how these attributions are in turn related to symptom severity. METHODS: N = 88 German-speaking children and adolescents (age: 7-17 years) after traumatic events and N = 79 caregivers participated between September 2019 and November 2020 in a survey on PTSD symptom severity (CATS-2) and attribution of DSO symptoms (caregiver questionnaire). RESULTS: The ICD-11 criteria (CATS­2 and a developmentally adapted version) showed lower frequency rates for PTSD as compared to DSM­5 and ICD-10. The ICD-11 clusters re-experiencing and hyperarousal were met the least often. Changes in DSO symptoms were predominantly rated as event-related. This attribution was associated with higher PTSD and DSO symptom severity in caregiver reports. The age-related attribution was associated with higher DSO-symptom severity, but not PTSD symptom severity in caregiver reports. DISCUSSION: In the context of the diagnostic process and the revision of diagnostic instruments for ICD-11 (C)PTSD, development-specific symptoms should be taken into account. The trauma-related differentiation of DSO symptom changes as compared to development-related fluctuations is challenging and therefore requires several sources of information.