ICD-10 Chapters Research Articles

Alcohol-Specific Inpatient Diagnoses in Germany: A Retrospective Cross-Sectional Analysis of Primary and Secondary Diagnoses from 2012 to 2021.

Our study aimed to a) describe the distribution of hospital discharges with primary and secondary alcohol-specific diagnoses by sex and age group, and b) describe how the number of hospital discharges with primary and secondary alcohol-specific diagnoses have changed across different diagnostic groups (categorized by primary International Classification of Diseases, 10th Revision [ICD-10] diagnosis) over time. Retrospective cross-sectional analysis. German hospital settings between 2012 and 2021. All persons aged 15-69 admitted to hospitals as registered in a nationwide data set. We counted a) the number of all hospital discharges and b) the number of hospital discharges with at least one alcohol-specific secondary diagnosis (secondary alcohol-specific diagnosis) by year, sex, age group, and diagnostic group. One diagnostic group included all primary alcohol-specific diagnoses, while 13 additional groups aligned with ICD-10 chapters (e.g., neoplasms). Alcohol-involvement was defined as either a primary or secondary alcohol-specific diagnosis. Of 95 417 204 recorded hospital discharges between 2012 and 2021, 3 828 917 discharges (4.0%; 2 913 903 men (6.4%); 915 014 women (1.8%)) involved either a primary or at least one secondary diagnosis related to alcohol. Of all alcohol-involved hospital discharges, 56.8% (1 654 736 discharges) had no primary but only a secondary alcohol-specific diagnosis. Secondary alcohol-specific diagnoses were particularly prevalent in hospital discharges due to injuries. With rising age, alcohol-involvement in hospital discharges due to digestive or cardiovascular diseases increased. Between 2012 and 2021, the rate of alcohol-involved hospital discharges has decreased more in younger as compared with older adults (average change between 2012 and 2021: 15-24: -55%; 25-34: -41%; 35-44: -23%; 45-54: -31%; 55-64: -21%; 65-69: -8%). The number of alcohol-involved hospital discharges in Germany from 2012 to 2021 more than doubles (from 1 654 736 to 3 828 917) when including secondary alcohol-specific diagnoses. More pronounced declines among younger adults may be attributed to unequal changes in alcohol consumption patterns across the population and to the hazardous effects of long-term alcohol use.

#772 Causes of non-elective hospitalisations among adult patients with chronic kidney disease in England: Clinical Practice Research Datalink 2010-2019

Abstract Background and Aims Patients with chronic kidney disease (CKD) are at higher risk of non-elective hospitalisation compared to the general population, which is associated with an increased risk of death and accounts for disproportionate resource utilisation. There are limited population-level estimates of the causes of non-elective hospitalisation for patients with CKD in England. Therefore, a population-based study was implemented to start to address this shortfall. Method This non-interventional, observational study utilised data from primary care electronic health records from the Clinical Practice Research Datalink (CPRD) AURUM and Hospital Episode Statistics (HES) admitted patient care (APC). Patients aged ≥18 years registered in CPRD with eligible linkage to HES between January 1, 2010-December 31, 2019 with at least two eGFR measurements during that period were identified. CKD was defined by an eGFR <60 ml/min/1.73 m2 and/or presence of a uACR measurement ≥3 mg/mmol, both confirmed by a second measurement 90-365 days later. Start of follow-up (index) was set to the earliest date during the study period where CKD was confirmed. Non-elective admissions were defined as hospitalisations not planned in advance. Follow-up for hospitalisations ended at the earliest of death, administrative censoring, or December 31, 2019. Patients with end stage kidney disease at index were excluded. Causes of hospitalisation during follow-up were based on three character-level ICD codes in the primary position. Where the same ICD-10 code was coded more than once within a hospitalisation, it was only counted once. Results From a total population of 6.1 million adult patients meeting study inclusion criteria, 743.945 adults with CKD were identified (12.2%) with a median follow-up of 3.62 years. The mean age (SD) was 76.1 (11.5) years, 55.2% were female, and 89.8% were White. The majority (60.9%) of patients had stage 3a CKD (eGFR 45-59 ml/min/1.732 m2) and 34.3% and 17.1% had a history of type 2 diabetes and heart failure at time of CKD confirmation, respectively. There were 1.45 million non-elective hospitalisations observed, with 449.128 (60%) of patients experiencing ≥1 non-elective hospitalisation during follow-up. The most frequent ICD-10 chapter indicated as primary cause of all non-elective hospitalisation was diseases of the circulatory system (19.4%), including heart failure (4.9%), ischaemic heart disease (myocardial infarction and angina) (3.5%), stroke (2.2%) and atrial fibrillation/flutter (1.9%). Infection was also a frequent cause of non-elective hospitalisation, including pneumonia of unspecified organism (7.8%), unspecified acute lower respiratory tract (2.5%), and other sepsis (2.7%). Frequent hospitalisation also occurred in patients with CKD due to fractures (3.5%) and injuries to the head (1.7%). Conclusion Non-elective hospitalisations are frequent among patients with CKD. Diseases of the circulatory and respiratory systems are overall most common causes, with pneumonia, ischaemic heart disease, and heart failure the most frequent modifiable reasons for admission. Ensuring that current shortfalls in primary and secondary prevention for patients with CKD through optimization of strategies such as vaccination and evidence based cardiovascular disease management will reduce rates of non-elective hospitalisation and other clinical outcomes and ensure best use of health care resources for patients with CKD.

Physical health conditions in young children with profound intellectual and multiple disabilities: The prevalence and associations between these conditions.

It is thought that physical health conditions start at a young age in people with profound intellectual and multiple disabilities (PIMD). Knowledge regarding the prevalence, associations and development of these physical health conditions could be used for purposes of prevention as well as appropriate care and support but is currently lacking. The aim of this study is to gain insight into the prevalence of physical health conditions and associations between these conditions in young children with PIMD. The study used cross-sectional data related to the physical health conditions of children with PIMD (n= 51, aged between 12 and 61 months). Data were collected in Belgium and in the Netherlands through a checklist filled in by primary caregiver(s). Physical health conditions were classified into categories by the 10th revision of the International Classification of Diseases and Related Health Problems (ICD-10) system. The number of physical health conditions and associations between them were analysed. The analysis focused on prevalence rates and associations represented by odds ratios (p< 0.05). A graphical model was estimated to represent dependencies and conditional dependencies between physical health conditions. We found a mean of 3.8 (range 1-8, SD 1.9) physical health conditions per child. Most of the physical health conditions were found in the ICD-10 chapter 'Nervous System', with hypotonia as the most frequent at 70.6%. Five significant large associations were found between spasticity-contractures (OR 9.54); circulatory system-contractures (OR 7.50); scoliosis-contractures (OR 10.25); hearing impairments-skin problems (OR 58.20) and obstipation-hypotonia (OR 19.98). This study shows that at a young age, multiple physical health conditions are present in children with PIMD. In addition, we found five associations between physical health conditions.

Topic modeling on clinical social work notes for exploring social determinants of health factors.

Existing research on social determinants of health (SDoH) predominantly focuses on physician notes and structured data within electronic medical records. This study posits that social work notes are an untapped, potentially rich source for SDoH information. We hypothesize that clinical notes recorded by social workers, whose role is to ameliorate social and economic factors, might provide a complementary information source of data on SDoH compared to physician notes, which primarily concentrate on medical diagnoses and treatments. We aimed to use word frequency analysis and topic modeling to identify prevalent terms and robust topics of discussion within a large cohort of social work notes including both outpatient and in-patient consultations. We retrieved a diverse, deidentified corpus of 0.95 million clinical social work notes from 181 644 patients at the University of California, San Francisco. We conducted word frequency analysis related to ICD-10 chapters to identify prevalent terms within the notes. We then applied Latent Dirichlet Allocation (LDA) topic modeling analysis to characterize this corpus and identify potential topics of discussion, which was further stratified by note types and disease groups. Word frequency analysis primarily identified medical-related terms associated with specific ICD10 chapters, though it also detected some subtle SDoH terms. In contrast, the LDA topic modeling analysis extracted 11 topics explicitly related to social determinants of health risk factors, such as financial status, abuse history, social support, risk of death, and mental health. The topic modeling approach effectively demonstrated variations between different types of social work notes and across patients with different types of diseases or conditions. Our findings highlight LDA topic modeling's effectiveness in extracting SDoH-related themes and capturing variations in social work notes, demonstrating its potential for informing targeted interventions for at-risk populations. Social work notes offer a wealth of unique and valuable information on an individual's SDoH. These notes present consistent and meaningful topics of discussion that can be effectively analyzed and utilized to improve patient care and inform targeted interventions for at-risk populations.

Real-Time Classification of Causes of Death Using AI: Sensitivity Analysis.

In 2021, the European Union reported >270,000 excess deaths, including >16,000 in Portugal. The Portuguese Directorate-General of Health developed a deep neural network, AUTOCOD, which determines the primary causes of death by analyzing the free text of physicians' death certificates (DCs). Although AUTOCOD's performance has been established, it remains unclear whether its performance remains consistent over time, particularly during periods of excess mortality. This study aims to assess the sensitivity and other performance metrics of AUTOCOD in classifying underlying causes of death compared with manual coding to identify specific causes of death during periods of excess mortality. We included all DCs between 2016 and 2019. AUTOCOD's performance was evaluated by calculating various performance metrics, such as sensitivity, specificity, positive predictive value (PPV), and F1-score, using a confusion matrix. This compared International Statistical Classification of Diseases and Health-Related Problems, 10th Revision (ICD-10), classifications of DCs by AUTOCOD with those by human coders at the Directorate-General of Health (gold standard). Subsequently, we compared periods without excess mortality with periods of excess, severe, and extreme excess mortality. We defined excess mortality as 2 consecutive days with a Z score above the 95% baseline limit, severe excess mortality as 2 consecutive days with a Z score >4 SDs, and extreme excess mortality as 2 consecutive days with a Z score >6 SDs. Finally, we repeated the analyses for the 3 most common ICD-10 chapters focusing on block-level classification. We analyzed a large data set comprising 330,098 DCs classified by both human coders and AUTOCOD. AUTOCOD demonstrated high sensitivity (≥0.75) for 10 ICD-10 chapters examined, with values surpassing 0.90 for the more prevalent chapters (chapter II-"Neoplasms," chapter IX-"Diseases of the circulatory system," and chapter X-"Diseases of the respiratory system"), accounting for 67.69% (223,459/330,098) of all human-coded causes of death. No substantial differences were observed in these high-sensitivity values when comparing periods without excess mortality with periods of excess, severe, and extreme excess mortality. The same holds for specificity, which exceeded 0.96 for all chapters examined, and for PPV, which surpassed 0.75 in 9 chapters, including the more prevalent ones. When considering block classification within the 3 most common ICD-10 chapters, AUTOCOD maintained a high performance, demonstrating high sensitivity (≥0.75) for 13 ICD-10 blocks, high PPV for 9 blocks, and specificity of >0.98 in all blocks, with no significant differences between periods without excess mortality and those with excess mortality. Our findings indicate that, during periods of excess and extreme excess mortality, AUTOCOD's performance remains unaffected by potential text quality degradation because of pressure on health services. Consequently, AUTOCOD can be dependably used for real-time cause-specific mortality surveillance even in extreme excess mortality situations.

Hospital admissions for physical health and psychosocial adversity among people experiencing homelessness in England: a population-based retrospective cross-sectional study

BackgroundHomeless health care is often characterised by physical health, mental health, and substance use problems, resulting in high use of emergency care, poor outcomes, and extreme social inequities. We assessed health needs as prevention opportunities for hospitalised people experiencing homelessness (PEH) in England. MethodsThis population-based retrospective cross-sectional study used anonymised national Hospital Episodes Statistics Admitted Patient Care data. PEH were identified as having at least one homeless code (“no fixed abode”, “registered with a homeless-exclusive GP practice”, “clinical diagnosis of homelessness”) from April 1, 2017, to March 31, 2018. We analysed admissions for PEH and for housed people. We estimated the prevalence of demographic and admission characteristics and diagnoses by 10th International Classification of Disease (ICD-10) chapter. We developed novel diagnostic phenotypes for physical health (internal disease processes) and psychosocial adversity (mental health, substance use, violence, and social factors). We compared admissions between PEH and housed people using sex-stratified logistic regression adjusted for age and ethnicity. FindingsThere were 15 566 010 admissions (51 643 PEH and 15 514 367 housed people). Compared with housed people, proportionately more PEH were younger (PEH aged 26–45 years, n=24 224 [46·9%], housed people n=3 323 951 [21·4%]), male (PEH n=37 662 [72·9%], housed people n=6 819 157 [44·0%]), and not White British (PEH n=14 605 [28·3%], housed people n=3 447 183 [22·2%]). Emergency admissions were more common among PEH (PEH male n=30 958 [82·2%], housed people male n=5 321 428 [34·3%], adjusted odds ratio [aOR] 8·76, 95% CI 8·53–9·00). The most common primary diagnoses by ICD-10 chapter for PEH were mental and behavioural conditions (PEH male n=7118 admissions [18·9%], housed people male n=155 144 [1·0%], 12·97, 12·61–13·34). Admissions for the psychosocial adversity phenotype were higher in PEH, particularly for women (PEH female n=3922 [28·1%], housed people female n=155 644 [1·79%], 18·18, 17·50–18·88). Physical health phenotype admissions were less common in PEH (PEH male n=7510 [19·9%], housed people male n=1 821 397 [26·7%], 0·91, 0·89–0·94), but specific infections, cancers, respiratory, and cardiovascular diseases were more common among PEH for both men and women. InterpretationThese results support targeting of preventative interventions for PEH before, during and after admission to hospital, highlighting psychosocial needs. Future research should aim to produce reliable estimates of the size of the national homeless population to enable calculation of admission rates for psychosocial and physical health diagnoses. FundingNational Institute for Health and Care Research (NIHR).

Emergency admissions’ diagnoses and risk of in-hospital death according to the primary ICD-10 chapter assigned at discharge and the National Early Warning Score on admission

Background: The relationship between diagnosis, illness severity, and mortality risk for unselected emergency admissions is poorly defined. Aim: To define primary ICD-10 diagnostic chapters at discharge, admission illness severity by the National Early Warning Score, and in-hospital mortality for all unselected emergency admissions. Method: Retrospective, observational, cohort study of 122,259 unselected, adult emergency admissions to Salford Royal Hospital between 2014 and 2022. Results: In-hospital mortality was 4.3% but most patients had an ICD-10 chapter associated with a lower risk of death. 60% of in-hospital deaths were in four chapters, infections, circulatory and respiratory diseases, or neoplasms. An admission NEWS ≥3 was associated with earlier mortality and an eight-fold increased risk of in-hospital mortality. 45% of all in-hospital deaths occurred in patients with an admission NEWS &lt;3. Conclusion: Mortality in emergency hospital admissions is associated with illness severity and four diagnostic chapters. NEWS should not be the only arbiter of hospital admission, as for certain diagnostic chapters the risk of death is high even if vital signs on presentation are normal.

Diagnostic groups of hospital stays and outpatient visits during 10 years before Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) is a major determinant of healthcare costs and increase in the healthcare service use occur already before the AD diagnosis. However, little is known how the different diagnosis categories contribute to this increase in healthcare use. We investigated how the hospitalizations and specialized healthcare outpatient visits from different diagnosis categories, based on the International Classification of Diseases (ICD-10) chapters, contribute to increased specialized healthcare service use during ten-year period preceding AD diagnosis.MethodsA register-based nationwide cohort of 42,934 community-dwelling persons who received clinically verified AD diagnosis in between 2008 and 2011 in Finland and 1:1 age, sex and hospital district- matched comparison cohort were included. Hospitalizations and specialized healthcare visits were categorized by the main diagnosis, according to the ICD-10 chapters. AD and dementia were separated to their own category. The number of persons with visits and stays was calculated for every 6 months, irrespective of the frequency of visits/stays individual had during that time window. Furthermore, the relative distribution of the diagnosis categories was computed.ResultsAD cohort was more likely to have visits and stays during the 10-year period (OR 1.19, 95% CI 1.17–1.21). The number of persons with visits and stays peaked in AD cohort from 1.5 years before the diagnosis when the differences in relative distribution of different diagnosis categories also became evident. The largest differences were observed for visits/stays with cognitive disorders, symptoms of unspecified diseases and psychiatric disorders diagnoses, and those with missing diagnosis codes in the last time window before AD diagnosis.Conclusions and implicationsIncreased healthcare service use before AD diagnosis does not seem to arise from differences in specific diagnosis categories of ICD-10 such as diseases of the circulatory system, but from the higher frequency of visits and stays among persons with AD across diagnosis categories. Based on the relative distribution of diagnosis categories, the steep increase in healthcare service use just before and during the diagnostic process is likely due to prodromal symptoms and visits related to cognition.

Significance of musculoskeletal and connective tissue parameters as health indicators in Federal Fire-Fighting Service officers of the State Fire-Fighting Service of the EMERCOM of Russia

Relevance. The job of Federal Fire-Fighting Service (FFS) officers of the State Fire-Fighting Service of the EMERCOM of Russia is among the global top 10 occupations with evident risk of health functional reserves depletion, prevalence of early occupational diseases, injuries and even death. Traditionally, investigators focus on circulatory diseases and how they affect firefighters’ occupational health.The objective is to provide research-based evidence showing that musculoskeletal and connective tissue parameters provide a reliable estimate of the health status in Russian Federal Fire-Fighting Service officers.Methodology. The authors analyzed the research papers included in the Russian Science Citation Index mostly within the last 10 years and the studies carried out at the Nikiforov Russian Center of Emergency and Radiation Medicine and at the All-Russian Research Institute for Fire Protection of the EMERCOM of Russia. Morbidity was calculated in ppm (‰), industrial injury and primary disability rates were estimated per 10,000 (×104), mortality (deaths) – per 100,000 (×105) people. The indicators dynamics was estimated based on dynamic sets of data applying the 2nd order polynomial trend; the Pearson correlation coefficient was utilized to verify consistency of the trends.Results and analysis. In 2003–2015 the average annual incidence rate of cases with labor losses (across all ICD-10 chapters of diseases) among the EMERCOM Federal Fire Service officers was (407.0 ± 30.4) ‰ which was statistically significantly lower than among the Russian armed forces officers (508.5 ± 35.6) ‰ (p &lt; 0.05); the number of lost workdays was higher, i.e. (5139 ± 402) and (4174 ± 123) ‰ respectively (p &lt; 0.05). Consistency in the dynamics of case number, rate of lost workdays, and day/incident ratio among firefighters and military officers is low and negative, potentially due to the impact of different factors on lost workdays rate. Assuming the macrosocial factors are identical, organisational and/or occupational factors could be the key contributors to labor losses. Rates of injuries, poisoning and other external impacts (chapter XIX in ICD-10), as well as musculoskeletal and connective tissue diseases (chapter XIII) play the leading role in morbidity dynamics among firefighters. The mortality rate among the Russian EMERCOM FFS officers with chapter XIX injuries was 8.5 times lower than that among the Russian male population, although the population cohort was 2.5 times more numerous. Occupational injury rate of (14.66 ± 2.01) • 10–4 of injuries/(firefighter • year) and firefighter fatalities (8.53 ± 0.83) • 10–5 deaths/(firefighter • year) in 2006–2020 were statistically significantly lower than among economically active working male population in Russia: (22.73 ± 2.8) • 10–4 (p &lt; 0.01) and (13.23 ± 1.12) • 10–5 (p &lt; 0.05) respectively. Considering the work schedule of firefighters, the annual amount of work in extreme environments was carried out within 6 months; whereas the level of industrial traumatism due to fire extinguishing and elimination of other emergency situations calculated for 12 months should be doubled, to say the least. The level of primary disability among Russian Federal Fire Service employees was (15.98 ± 0.99) • 10–4, i.e. statistically reliably lower (p &lt; 0.001) than among the working population of Russia aged 18–44 years (25.51 ± 1.19) • 10–4. On the one hand, the data demonstrates efficient labor set-up and labor protection of the EMERCOM FFS employees, whereas disability rate among the adult population of Russia stays at a high level, on the other hand.Conclusion. Although not entirely eliminated, negative occupational impacts (i.e. diseases, injuries) can be reduced to minimal rates. Preventing the early onset of occupational diseases, especially traumas and musculoskeletal diseases, has a huge health sparing potential to ensure professional longevity of the EMERCOM FFS employees.

The impact of disease changes and mental health illness on readapted return to work after repeated sick leaves among Brazilian public university employees.

Health affects work absenteeism and productivity of workers, making it a relevant marker of an individual's professional development. The aims of this article were to investigate whether changes in the main cause of the sick leaves and the presence of mental health illnesses are associated with return to work with readaptation. A historical cohort study was carried out with non-work-related illnesses suffered by statutory workers of university campuses in a medium-sized city in the state of São Paulo, Brazil. Two exposures were measured: (a) changes, throughout medical examinations, in the International Classification of Diseases (ICD-10) chapter regarding the main condition for the sick leave; and (b) having at least one episode of sick leave due to mental illness, with or without change in the ICD-10 chapter over the follow-up period. The outcome was defined as return to work with adapted conditions. The causal model was established a priori and tested using a multiple logistic regression (MLR) model considering the effects of several confounding factors, and then compared with the same estimators obtained using Targeted Machine Learning. Among workers in adapted conditions, 64% were health professionals, 34% had had changes in the ICD-10 chapter throughout the series of sick leaves, and 62% had diagnoses of mental health issues. In addition, they worked for less time at the university and were absent for longer periods. Having had a change in the illness condition reduced the chance of returning to work in another function by more than 30%, whereas having had at least one absence because of a cause related to mental and behavioral disorders more than doubled the chance of not returning to work in the same activity as before. These results were independent of the analysis technique used, which allows concluding that there were no advantages in the use of targeted maximum likelihood estimation (TMLE), given its difficulties in access, use, and assumptions.

Polygenic Liability to Alzheimer's Disease Is Associated with a Wide Range of Chronic Diseases: A Cohort Study of 312,305 Participants.

Alzheimer's disease (AD) patients rank among the highest levels of comorbidities compared to persons with other diseases. However, it is unclear whether the conditions are caused by shared pathophysiology due to the genetic pleiotropy for AD risk genes. To figure out the genetic pleiotropy for AD risk genes in a wide range of diseases. We estimated the polygenic risk score (PRS) for AD and tested the association between PRS and 16 ICD10 main chapters, 136 ICD10 level-1 chapters, and 377 diseases with cases more than 1,000 in 312,305 individuals without AD diagnosis from the UK Biobank. After correction for multiple testing, AD PRS was associated with two main ICD10 chapters: Chapter IV (endocrine, nutritional and metabolic diseases) and Chapter VII (eye and adnexa disorders). When narrowing the definition of the phenotypes, positive associations were observed between AD PRS and other types of dementia (OR = 1.39, 95% CI [1.34, 1.45], p = 1.96E-59) and other degenerative diseases of the nervous system (OR = 1.18, 95% CI [1.13, 1.24], p = 7.74E-10). In contrast, we detected negative associations between AD PRS and diabetes mellitus, obesity, chronic bronchitis, other retinal disorders, pancreas diseases, and cholecystitis without cholelithiasis (ORs range from 0.94 to 0.97, FDR < 0.05). Our study confirms several associations reported previously and finds some novel results, which extends the knowledge of genetic pleiotropy for AD in a range of diseases. Further mechanistic studies are necessary to illustrate the molecular mechanisms behind these associations.

Diagnoses and mortality among prehospital emergency patients calling 112 with unclear problems: a population-based cohort study from Denmark

BackgroundPatients calling for an emergency ambulance and assessed as presenting with ‘unclear problem’ account for a considerable part of all emergency calls. Previous studies have demonstrated that these patients are at increased risk for unfavourable outcomes. A deeper insight into the underlying diagnoses and outcomes is essential to improve prehospital treatment. We aimed to investigate which of these diagnoses contributed most to the total burden of diseases in terms of numbers of deaths together with 1- and 30-day mortality.MethodsA historic regional population-based observational cohort study from the years 2016 to 2018. Diagnoses were classified according to the World Health Organisation ICD-10 System (International Statistical Classification of Diseases and Related Health Problems, 10th edition). The ICD-10 chapters, R (‘symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified)’ and Z (‘factors influencing health status and contact with health services”) were combined and designated “non-specific diagnoses”.Poisson regression with robust variance estimation was used to estimate proportions of mortality in percentages with 95% confidence intervals, crude and adjusted for age, sex and comorbidities.ResultsDiagnoses were widespread among the ICD-10 chapters, and the most were ‘non-specific diagnoses’ (40.4%), ‘circulatory diseases’ (9.6%), ‘injuries and poisonings’ (9.4%) and ‘respiratory diseases’ (6.9%). The diagnoses contributing most to the total burden of deaths (n = 554) within 30 days were ‘circulatory diseases’ (n = 148, 26%) followed by ‘non-specific diagnoses’ (n = 88, 16%) ‘respiratory diseases’ (n = 85, 15%), ‘infections’ (n = 54, 10%) and ‘digestive disease’ (n = 39, 7%). Overall mortality was 2.3% (1-day) and 7.1% (30-days). The risk of mortality was highly associated with age.ConclusionThis study found that almost half of the patients brought to the hospital after calling 112 with an ‘unclear problem’ were discharged with a ‘non-specific diagnosis’ which might seem trivial but should be explored more as these contributed the second-highest to the total number of deaths after 30 days only exceeded by ‘circulatory diseases’.

OP15 Improving The Osteoporosis Care Trajectory By Collaboration Between Clinicians, Patients And Health Insurers Within the Appropriate Care Program

IntroductionThe cyclic appropriate care program of the National Health Care Institute aims at enhancing quality of care in the Netherlands. A full cycle consists of four phases: (i) screening each ICD-10 chapter and selecting a care trajectory, (ii) in-depth analysis of the care trajectory and formulating actions for improvement, (iii) implementation, and (iv) evaluation. Collaboration with and between relevant parties from the field is key to its success. We describe the 2nd and 3th phase of this cycle, aimed at osteoporosis.MethodsFirst, nine clinicians, one nurse practitioner, two physiotherapists and one pharmacist representing scientific organizations, two patient representatives and one health insurer, defined research questions. Second, by in-depth analysis on declaration data of health care activities, and comparing the results to the guidelines, research questions were addressed. Last, results were discussed among all parties and actions for making wiser choices and improving the appropriateness of care were formulated. For each action, the parties defined who would take the lead and who would be involved.ResultsThe analyses showed that only 26 percent of Dutch fracture patients 50 years of age and above underwent dexa-scanning, as opposed to more than 80 percent in the guideline. All parties underlined this percentage should be increased. Possible actions were defined: to describe the care trajectory in the update of the multidisciplinary guideline; to better inform fracture patients about the importance of dexa-scanning; and to make adjustments to the hospital electronic system in order to facilitate the ordering of dexa-scans. For these actions, medical specialists were in the lead. Other data-analyses showed that half of osteoporosis patients stopped using medication within two years. For the jointly defined actions aimed at raising medication adherence, such as better patient education, the general practitioner and pharmacist were in the lead. Currently, the National Health Care Institute facilitates implementation and monitors improvement.ConclusionsClose collaboration with relevant parties led to well-considered actions on improvement of osteoporosis care.

Tobacco smoking and risks of more than 470 diseases in China: a prospective cohort study

Tobacco smoking is estimated to account for more than 1 million annual deaths in China, and the epidemic continues to increase in men. Large nationwide prospective studies linked to different health records can help to periodically assess disease burden attributed to smoking. We aimed to examine associations of smoking with incidence of and mortality from an extensive range of diseases in China. We analysed data from the prospective China Kadoorie Biobank, which recruited 512 726 adults aged 30-79 years, of whom 210 201 were men and 302 525 were women. Participants who had no major disabilities were identified through local residential records in 100-150 administrative units, which were randomly selected by use of multistage cluster sampling, from each of the ten diverse study areas of China. They were invited and recruited between June 25, 2004, and July 15, 2008. Upon study entry, trained health workers administered a questionnaire assessing detailed smoking behaviours and other key characteristics (eg, sociodemographics, lifestyle, and medical history). Participants were followed up via electronic record linkages to death and disease registries and health insurance databases, from baseline to Jan 1, 2018. During a median 11-year follow-up (IQR 10-12), 285 542 (55·7%) participants were ever hospitalised, 48 869 (9·5%) died, and 5252 (1·0%) were lost to follow-up during the age-at-risk of 35-84 years. Cox regression yielded hazard ratios (HRs) associating smoking with disease incidence and mortality, adjusting for multiple testing. At baseline, 74·3% of men and 3·2% of women (overall 32·4%) ever smoked regularly. During follow-up, 1 137 603 International Classification of Diseases, 10th revision (ICD-10)-coded incident events occurred, involving 476 distinct conditions and 85 causes of death, each with at least 100 cases. Compared with never-regular smokers, ever-regular smokers had significantly higher risks for nine of 18 ICD-10 chapters examined at age-at-risk of 35-84 years. For individual conditions, smokers had significantly higher risks of 56 diseases (50 for men and 24 for women) and 22 causes of death (17 for men and nine for women). Among men, ever-regular smokers had an HR of 1·09 (95% CI 1·08-1·11) for any disease incidence when compared with never-regular smokers, and significantly more episodes and longer duration of hospitalisation, particularly those due to cancer and respiratory diseases. For overall mortality, the HRs were greater in men from urban areas than in men from rural areas (1·50 [1·42-1·58] vs 1·25 [1·20-1·30]). Among men from urban areas who began smoking at younger than 18 years, the HRs were 2·06 (1·89-2·24) for overall mortality and 1·32 (1·27-1·37) for any disease incidence. In this population, 19·6% of male (24·3% of men residing in urban settings and 16·2% of men residing in rural settings) and 2·8% of female deaths were attributed to ever-regular smoking. Among Chinese adults, smoking was associated with higher risks of morbidity and mortality from a wide range of diseases. Among men, the future smoking-attributed disease burden will increase further, highlighting a pressing need for reducing consumption through widespread cessation and uptake prevention. British Heart Foundation, Cancer Research UK, Chinese Ministry of Science and Technology, Kadoorie Charitable Foundation, UK Medical Research Council, National Natural Science Foundation of China, Wellcome Trust.

Non-COVID activity in French emergency department during COVID-19 pandemic (March 2020 to March 2022)

Abstract Background The COVID-19 epidemic and mitigation actions had major impacts on health and healthcare use by the French population. Since 2004, the French public health agency daily collects individual data of visits in the emergency departments (ED) OSCOUR® network (94% of national visits in 2022). We aimed to analyse the evolution of non-Covid ED visits from 2020 to March 2022, in order to identify potential indirect impact of the epidemic. Methods The main medical diagnosis (MD) coded in ICD-10 from each ED visit from 2017 to March 2022 was classified into 17 ICD-10 chapters and in 95 disjoint subgroups of pathologies. The observed numbers of ED visits by age group and by chapters/subgroups were compared to expected numbers, estimated using an overdispersed Poisson regression model based on 2017-2019 data. Results The observed numbers of ED visits for all chapters and for a large part of subgroups were significantly lower than the expected numbers during the three lockdowns in all age groups and progressively returned to the expected level in 2021. A change in the pattern of a limited list of subgroups was observed: ED visits for purpura, chronic blood diseases and neurologic disorders in children decreased during the first lockdown and remained under the expected level until March 2022. Inversely the number of ED visits for mental health and wheezing in children, for pulmonary embolism in adults and for neoplams in the elderly increased and remained over the expected values until 2022. Conclusions Syndromic ED system was a pillar of the French reactive surveillance of direct and indirect impacts of COVID-19 epidemic. The changes observed for different subgroups of pathologies may reflect a negative impact of the epidemic, a positive effect of protective measures on the spread of other infectious diseases, a modification in the organization or in the use of health care in specific domains. Further studies using hospitalization data could explore these hypotheses. Key messages • Existing syndromic surveillance system implemented before the emergence of SARS-COV2 enabled to monitor non-Covid-19 visits to emergency departments and assess changes in patterns of pathologies. • An increase in the number of emergency department visits during the COVID-19 epidemic was observed for mental health in children, for pulmonary embolism in adults and for neoplams in the elderly.

Health of singletons born after frozen embryo transfer until early adulthood: a Finnish register study.

Is the health of singletons born after frozen embryo transfer (FET) comparable to that of singletons born after fresh embryo transfer (ET) until early adulthood? The health of singletons born after FET does not differ from that of singletons born after fresh ET. The differences in perinatal outcomes of children born after FET and fresh ET are well known. FET is associated with an increased risk of large-for-gestational-age but diminished risks of preterm birth (PTB), small-for-gestational-age and decreased perinatal mortality compared to fresh ET. However, knowledge on the long-term health after FET is scarce. This retrospective register-based cohort study compares singletons born after FET (n = 1825) between the years 1995 and 2006 to those born after fresh ET (n = 2933) and natural conception (NC, n = 31 136) with a mean follow-up time of 18-20 years. Singletons born after FET were compared to those born after fresh ET and NC regarding the frequencies of diagnoses in the main ICD-10 chapters (International Statistical Classification of Diseases and Related Health Problems, 10th revision), the number of outpatient visits and hospital admissions, and mortality. Adjustments were made for PTB, maternal age, parity, socioeconomic status based on mother's occupation and offspring sex. The study combines data from the Finnish Medical Birth Register, the Finnish Care Register for Health Care (CRHC) and the Cause-of-Death Register at Statistics Finland. The Student's T-test was used for continuous variables, and the Chi-square test was used for categorical variables. Cox regression was used to estimate crude and adjusted hazard ratios (HRs and aHRs, respectively). A general linear model was used to compare the means of outpatient visits, hospital admissions and lengths of hospital stays per person. No significant differences between the FET and fresh ET groups were found in the frequency of diagnoses in any of the ICD-10 chapters or in the parameters describing the need for hospital care. However, compared to the NC group, higher proportions in the FET group had outpatient visits in the hospital (93.5% vs 92.2%, aHR 1.23, 95% CI 1.17, 1.30) or hospital admissions (48% vs 46.5%, aHR 1.28, 95% CI 1.19, 1.37). Compared to the NC group, the FET group had elevated adjusted risks of diagnoses of infectious and parasitic diseases (aHR 1.24; 95% CI 1.11, 1.38), neoplasms (aHR 1.68; 95% CI 1.48, 1.91), diseases of the eye and adnexa, the ear or mastoid process (aHR 1.11; 95% CI 1.01, 1.21), the respiratory system (aHR 1.15; 95% CI 1.06, 1.23), the digestive system (aHR 1.17; 95% CI 1.05, 1.32), the skin or subcutaneous tissue (aHR 1.28; 95% CI 1.14, 1.43) and the genitourinary system (aHR 1.27; 95% CI 1.11, 1.45), as well as congenital malformations or chromosomal abnormalities (aHR 1.31; 95% CI 1.14, 1.50) and symptoms, signs or abnormal clinical or laboratory findings (aHR 1.25, 95% CI 1.16, 1.34). Only hospital-based inpatient and outpatient care is covered by the CRHC register, excluding milder cases diagnosed elsewhere. We were not able to study the effect of ART treatments and subfertility separately in our setting. In addition, although our cohort is reasonably sized, even larger cohorts would be needed to reliably study rare outcomes, such as cancer. For many ICD-10 chapters, we present the first published data on the long-term outcome of singletons born after FET. The results on FET versus fresh ET are reassuring, whereas the results on FET versus NC warrant further investigation. Finnish government research funding was obtained for this study. Funding was also obtained from the Finnish Medical Society Duodecim, the Päivikki and Sakari Sohlberg Foundation, Orion Research Foundation, Finnish Society of Obstetrics and Gynaecology (research grants to A.M.T.) and Finnish government research funding. The funding sources were not involved in the planning or execution of the study. The authors have no competing interests to declare. N/A.

Diagnosis-specific Cumulative Incidence of Return-to-work, Resignation, and Death Among Long-term Sick-listed Employees: Findings From the Japan Epidemiology Collaboration on Occupational Health Study.

BackgroundWhile it is essential to understand how long is sufficient for return-to-work when designing paid sick-leave systems, little attempt has been done to collect cause-specific information on when and how many of sickness absentees returned to work, became unemployed, or passed away.MethodsWe studied the first sick-leave episode of ≥30 consecutive days in those ≤55 years of age during 2012–2013 among employees of 11 Japanese private companies (n = 1,209), which were followed until 2017. Overall and disease-specific cumulative incidences of return-to-work, resignations, and deaths were estimated using competing risk analysis.ResultsDuring the 3.5-year period (follow-up rate: 99.9%), 1,014 returned to work, 167 became unemployed, and 27 died. Overall, return-to-work occurred within 1 year in 74.9% of all absentees and in 89.3% of those who successfully returned to work. Resignation occurred within 1 year in 8.7% of all absentees and in 62.9% of all subjects who resigned. According to ICD-10 chapters, the cumulative incidence of return-to-work ranged from 82.1% for mental disorders (F00–F99) to 95.3% for circulatory diseases (I00–I99). The cumulative incidence of return-to-work due to mental disorders ranged from 66.7% in schizophrenia (F20) to 95.8% in bipolar affective disorders (F31). Death was rarely observed except for cases of neoplasms (C00–D48), of which the cumulative incidence of death reached 14.2% by 1.5 years.ConclusionReturn-to-work and resignations occurred commonly within 1 year of sick leave among long-term sickness absentees in the Japanese private companies. Our findings may assist occupational physicians and employers in developing effective social protection schemes.

Readability of English, German, and Russian Disease-Related Wikipedia Pages: Automated Computational Analysis.

BackgroundWikipedia is a popular encyclopedia for health- and disease-related information in which patients seek advice and guidance on the web. Yet, Wikipedia articles can be unsuitable as patient education materials, as investigated in previous studies that analyzed specific diseases or medical topics with a comparatively small sample size. Currently, no data are available on the average readability levels of all disease-related Wikipedia pages for the different localizations of this particular encyclopedia.ObjectiveThis study aimed to analyze disease-related Wikipedia pages written in English, German, and Russian using well-established readability metrics for each language.MethodsWikipedia database snapshots and Wikidata metadata were chosen as resources for data collection. Disease-related articles were retrieved separately for English, German, and Russian starting with the main concept of Human Diseases and Disorders (German: Krankheit; Russian: Заболевания человека). In the case of existence, the corresponding International Classification of Diseases, Tenth Revision (ICD-10), codes were retrieved for each article. Next, the raw texts were extracted and readability metrics were computed.ResultsThe number of articles included in this study for English, German, and Russian Wikipedia was n=6127, n=6024, and n=3314, respectively. Most disease-related articles had a Flesch Reading Ease (FRE) score <50.00, signaling difficult or very difficult educational material (English: 5937/6125, 96.93%; German: 6004/6022, 99.7%; Russian: 2647/3313, 79.9%). In total, 70% (7/10) of the analyzed articles could be assigned an ICD-10 code with certainty (English: 4235/6127, 69.12%; German: 4625/6024, 76.78%; Russian: 2316/3314, 69.89%). For articles with ICD-10 codes, the mean FRE scores were 28.69 (SD 11.00), 20.33 (SD 9.98), and 38.54 (SD 13.51) for English, German, and Russian, respectively. A total of 9 English ICD-10 chapters (11 German and 10 Russian) showed significant differences: chapter F (FRE 23.88, SD 9.95; P<.001), chapter E (FRE 25.14, SD 9.88; P<.001), chapter H (FRE 30.04, SD 10.57; P=.049), chapter I (FRE 30.05, SD 9.07; P=.04), chapter M (FRE 31.17, 11.94; P<.001), chapter T (FRE 32.06, SD 10.51; P=.001), chapter A (FRE 32.63, SD 9.25; P<.001), chapter B (FRE 33.24, SD 9.07; P<.001), and chapter S (FRE 39.02, SD 8.22; P<.001).ConclusionsDisease-related English, German, and Russian Wikipedia articles cannot be recommended as patient education materials because a major fraction is difficult or very difficult to read. The authors of Wikipedia pages should carefully revise existing text materials for readers with a specific interest in a disease or its associated symptoms. Special attention should be given to articles on mental, behavioral, and neurodevelopmental disorders (ICD-10 chapter F) because these articles were most difficult to read in comparison with other ICD-10 chapters. Wikipedia readers should be supported by editors providing a short and easy-to-read summary for each article.

Diagnoses and mortality for patients with unclear problems calling for an ambulance

Danish patients calling the Emergency Medical Services (EMS) with unclear problems are assigned a Danish Index for Emergency Care (DI) criteria called ‘unclear problem’. Previous Danish studies found ‘unclear problem’ in 17% and 19% of all emergency calls. In the Emergency Departments, unclear problems identified as non-specific symptoms are well documented. We investigated EMS patients given an ‘unclear problem’ DI-criteria prehospitally, their hospital discharge diagnoses and 1-day and 30-day mortality rates.&#x0D; Population-based observational cohort study investigating 7,935 EMS patients who received the DI-criteria ‘unclear problem’ upon an emergency call and who were brought to hospital in the North Denmark Region during January 1st, 2016 – December 31st, 2018. Outcome variables were; number of emergency ambulances dispatched, ‘unclear problem’ DI-criteria, and vital status (dead or alive) 30 days after hospital contact. We evaluated the association between ICD-10 diagnosis chapters and mortality adjusted for age, gender, and comorbidity. ICD-10 chapters 18: “Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified” and 21: “Factors influencing health status and contact with health services” were defined as ‘non-specific diagnoses’.All ICD-10 chapters were represented in the discharge diagnoses. The majority (40.4%) were non-specific diagnoses. Common discharge diagnoses were circulatory (9.6%), injuries and poisoning (9.4%), and respiratory diseases (6.9%). Overall mortality rates were for 1-day and 30-day 2.3% (n=181) and 7.1% (n=566), respectively. Day 1 mortality rates were highest for circulatory diseases (8.6%), infections (5.4%), and respiratory diseases (4.0%). Mortality on day 30 was 2.6% and 4.1% for non-specific diagnoses, whereas circulatory, respiratory diagnoses and infections exhibted highest mortality rates. Risk of mortality was associated with age and comorbidities and when adjusted for these confounders, mortality rates decreased for all diagnoses.&#x0D; EMS patients assigned ‘unclear problem’ and brought to the hospital received diagnoses from all ICD-10 chapters, the majority with non-specific diagnoses, followed by injuries and poisoning, circulatory and respiratory diseases. The latter two groups exhibited the highest crude mortality rates, decreasing substantially when adjusted for age and comorbidity. Mortality rates among patients with unclear problems were associated with age and comorbidities rather than the unclear emergency medical call and following discharge diagnoses.

A Comparative Analysis of In-Hospital Mortality per Disease Groups in Germany Before and During the COVID-19 Pandemic From 2016 to 2020

Throughout the ongoing SARS-CoV-2 pandemic, it has been critical to understand not only the viral disease itself but also its implications for the overall health care system. Reports about excess mortality in this regard have mostly focused on overall death counts during specific pandemic phases. To investigate hospitalization rates and compare in-hospital mortality rates with absolute mortality incidences across a broad spectrum of diseases, comparing 2020 data with those of prepandemic years. Retrospective, cross-sectional, multicentric analysis of administrative data from 5 821 757 inpatients admitted from January 1, 2016, to December 31, 2020, to 87 German Helios primary to tertiary care hospitals. Exposure to SARS-CoV-2. Administrative data were analyzed from January 1, 2016, to March 31, 2021, as a consecutive sample for all inpatients. Disease groups were defined according to International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10; German modification) encoded main discharge diagnoses. Incidence rate ratios (IRRs) for hospital admissions and hospital mortality counts, as well as relative mortality risks (RMRs) comparing 2016-2019 with 2020 (exposure to the SARS-CoV-2 pandemic), were calculated with Poisson regression with log-link function. Data were examined for 5 821 757 inpatients (mean [SD] age, 56.4 [25.3] years; 51.5% women), including 125 807 in-hospital deaths. Incidence rate ratios for hospital admissions were associated with a significant reduction for all investigated disease groups (IRR, 0.82; 95% CI, 0.79-0.86; P < .001). After adjusting for age, sex, the Elixhauser Comorbidity Index score, and SARS-CoV-2 infections, RMRs were associated with an increase in infectious diseases (RMR, 1.28; 95% CI, 1.21-1.34; P < .001), musculoskeletal diseases (RMR, 1.19; 95% CI, 1.04-1.36; P = .009), and respiratory diseases (RMR, 1.09; 95% CI, 1.05-1.14; P < .001) but not for the total cohort (RMR, 1.00; 95% CI, 0.99-1.02; P = .66). Regarding in-hospital mortality, IRR was associated with an increase within the ICD-10 chapter of respiratory diseases (IRR, 1.28; 95% CI, 1.13-1.46; P < .001) in comparing 2020 with 2016-2019, in contrast to being associated with a reduction in IRRs for the overall cohort and several other subgroups. After exclusion of patients with SARS-CoV-2 infections, IRRs were associated with a reduction in absolute in-hospital mortality for the overall cohort (IRR, 0.78; 95% CI, 0.72-0.84; P < .001) and the subgroup of respiratory diseases (IRR, 0.83; 95% CI, 0.74-0.92; P < .001). This cross-sectional study of inpatients from a multicentric German database suggests that absolute in-hospital mortality for 2020 across disease groups was not higher compared with previous years. Higher IRRs of in-hospital deaths observed in patients with respiratory diseases were likely associated with individuals with SARS-CoV-2 infections.