Pub Date : 2024-06-06DOI: 10.1101/2024.06.06.24308537
Wanxin Li, Yining Hua, Peilin Zhou, Li Zhou, Xin Xu, Jie Yang
Objective: Harnessing drug-related data posted on social media in real time can offer insights into how the pandemic impacts drug use and monitor misinformation. This study developed a natural language processing (NLP) pipeline tailored for the analysis of social media discourse on COVID-19 related drugs. Methods: This study constructed a full pipeline for COVID-19 related drug tweet analysis, utilizing pre-trained language model-based NLP techniques as the backbone. This pipeline is architecturally composed of four core modules: named entity recognition (NER) and normalization to identify medical entities from relevant tweets and standardize them to uniform medication names, target sentiment analysis (TSA) to reveal sentiment polarities associated with the entities, topic modeling to understand underlying themes discussed by the population, and drug network analysis to potential adverse drug reactions (ADR) and drug-drug interactions (DDI). The pipeline was deployed to analyze tweets related to COVID-19 and drug therapies between February 1, 2020, and April 30, 2022. Results: From a dataset comprising 2,124,757 relevant tweets sourced from 1,800,372 unique users, our NER model identified the top five most-discussed drugs: Ivermectin, Hydroxychloroquine, Remdesivir, Zinc, and Vitamin D. Sentiment and topic analysis revealed that public perception was predominantly shaped by celebrity endorsements, media hotspots, and governmental directives rather than empirical evidence of drug efficacy. Co-occurrence matrices and complex network analysis further identified emerging patterns of DDI and ADR that could be critical for public health surveillance like better safeguarding public safety in medicines use. Conclusion: This study evidences that an NLP-based pipeline can be a robust tool for large-scale public health monitoring and can offer valuable supplementary data for traditional epidemiological studies concerning DDI and ADR. The framework presented here aspires to serve as a cornerstone for future social media-based public health analytics.
{"title":"Characterizing Public Sentiments and Drug Interactions during COVID-19: A Pretrained Language Model and Network Analysis of Social Media Discourse","authors":"Wanxin Li, Yining Hua, Peilin Zhou, Li Zhou, Xin Xu, Jie Yang","doi":"10.1101/2024.06.06.24308537","DOIUrl":"https://doi.org/10.1101/2024.06.06.24308537","url":null,"abstract":"Objective: Harnessing drug-related data posted on social media in real time can offer insights into how the pandemic impacts drug use and monitor misinformation. This study developed a natural language processing (NLP) pipeline tailored for the analysis of social media discourse on COVID-19 related drugs. Methods: This study constructed a full pipeline for COVID-19 related drug tweet analysis, utilizing pre-trained language model-based NLP techniques as the backbone. This pipeline is architecturally composed of four core modules: named entity recognition (NER) and normalization to identify medical entities from relevant tweets and standardize them to uniform medication names, target sentiment analysis (TSA) to reveal sentiment polarities associated with the entities, topic modeling to understand underlying themes discussed by the population, and drug network analysis to potential adverse drug reactions (ADR) and drug-drug interactions (DDI). The pipeline was deployed to analyze tweets related to COVID-19 and drug therapies between February 1, 2020, and April 30, 2022. Results: From a dataset comprising 2,124,757 relevant tweets sourced from 1,800,372 unique users, our NER model identified the top five most-discussed drugs: Ivermectin, Hydroxychloroquine, Remdesivir, Zinc, and Vitamin D. Sentiment and topic analysis revealed that public perception was predominantly shaped by celebrity endorsements, media hotspots, and governmental directives rather than empirical evidence of drug efficacy. Co-occurrence matrices and complex network analysis further identified emerging patterns of DDI and ADR that could be critical for public health surveillance like better safeguarding public safety in medicines use. Conclusion: This study evidences that an NLP-based pipeline can be a robust tool for large-scale public health monitoring and can offer valuable supplementary data for traditional epidemiological studies concerning DDI and ADR. The framework presented here aspires to serve as a cornerstone for future social media-based public health analytics.","PeriodicalId":506788,"journal":{"name":"medRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141265180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-05DOI: 10.1101/2024.06.01.24308209
Z. Su, R. Xue, W. Liu, D. Wu, L. Wu, Y. Cheng, Q. Wan
Abstract Background: Kidney diseases, including membranous nephropathy (MN), IgA nephropathy (IgAN), and chronic kidney disease (CKD), pose significant global health challenges due to their high prevalence and severe outcomes. There is still an urgent need to discover new targets for treating kidney diseases. Mendelian randomization (MR) has been widely used to repurpose licensed drugs and discover novel therapeutic targets. Thus, we aimed to identify novel therapeutic targets for Kidney diseases and analyze their pathophysiological mechanisms and potential side effects. Methods: Integrated with currently available druggable genes, Summary-data-based MR (SMR) analysis was conducted to estimate the causal effects of blood expression quantitative trait loci (eQTLs) on kidney diseases. A study was replicated using distinct blood eQTL and diseases genome-wide association study (GWAS) data sources to validate the identified genes. The eQTL data was obtained from eQTLGen and GTEx v8.0, with sample sizes of 31,684 and 15,201, respectively. The data on kidney diseases was sourced from the Kiryluk Lab, CKDgen, and the Finngen consortium, with sample sizes ranging from 7,979 to 412,181. Subsequently, reverse two-sample MR and colocalization analysis were employed for further validation. Finally, the potential side effects of the identified key genes in treating kidney diseases were assessed using phenome-wide MR and mediation MR. Results: After correcting for the false discovery rate, a total of 20, 23, and 6 unique potential genes were found to have causal relationships with MN, IgAN, and CKD, respectively. Among them, MN showed validated associations with one gene (HCG18), IgAN demonstrated associations with four genes (AFF3, CYP21A2, DPH3, HLA-DRB5), and chronic kidney disease (CKD) displayed an association with one gene (HLA-DQB1-AS1). Several of these key genes are druggable genes. Further phenome-wide MR analysis revealed that certain genes may be associated with diabetes, fat metabolism, and infectious diseases, suggesting that these factors could potentially serve as mediators. Conclusions: This study presents genetic evidence that supports the potential therapeutic benefits of targeting these key genes for treating kidney diseases. This is significant in prioritizing the development of drugs for kidney diseases.
{"title":"Comprehensive Druggable Genome-Wide Mendelian Randomization Reveals Therapeutic Targets for Kidney Diseases","authors":"Z. Su, R. Xue, W. Liu, D. Wu, L. Wu, Y. Cheng, Q. Wan","doi":"10.1101/2024.06.01.24308209","DOIUrl":"https://doi.org/10.1101/2024.06.01.24308209","url":null,"abstract":"Abstract Background: Kidney diseases, including membranous nephropathy (MN), IgA nephropathy (IgAN), and chronic kidney disease (CKD), pose significant global health challenges due to their high prevalence and severe outcomes. There is still an urgent need to discover new targets for treating kidney diseases. Mendelian randomization (MR) has been widely used to repurpose licensed drugs and discover novel therapeutic targets. Thus, we aimed to identify novel therapeutic targets for Kidney diseases and analyze their pathophysiological mechanisms and potential side effects. Methods: Integrated with currently available druggable genes, Summary-data-based MR (SMR) analysis was conducted to estimate the causal effects of blood expression quantitative trait loci (eQTLs) on kidney diseases. A study was replicated using distinct blood eQTL and diseases genome-wide association study (GWAS) data sources to validate the identified genes. The eQTL data was obtained from eQTLGen and GTEx v8.0, with sample sizes of 31,684 and 15,201, respectively. The data on kidney diseases was sourced from the Kiryluk Lab, CKDgen, and the Finngen consortium, with sample sizes ranging from 7,979 to 412,181. Subsequently, reverse two-sample MR and colocalization analysis were employed for further validation. Finally, the potential side effects of the identified key genes in treating kidney diseases were assessed using phenome-wide MR and mediation MR. Results: After correcting for the false discovery rate, a total of 20, 23, and 6 unique potential genes were found to have causal relationships with MN, IgAN, and CKD, respectively. Among them, MN showed validated associations with one gene (HCG18), IgAN demonstrated associations with four genes (AFF3, CYP21A2, DPH3, HLA-DRB5), and chronic kidney disease (CKD) displayed an association with one gene (HLA-DQB1-AS1). Several of these key genes are druggable genes. Further phenome-wide MR analysis revealed that certain genes may be associated with diabetes, fat metabolism, and infectious diseases, suggesting that these factors could potentially serve as mediators. Conclusions: This study presents genetic evidence that supports the potential therapeutic benefits of targeting these key genes for treating kidney diseases. This is significant in prioritizing the development of drugs for kidney diseases.","PeriodicalId":506788,"journal":{"name":"medRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141265316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-05DOI: 10.1101/2024.06.05.24308127
Emilie T. Théberge MSc, Kate Durbano, Diane Demailly, Sophie Huby, Arezoo Mohajeri MSc, Canada Consortium, C. Karnebeek, G. A. Md, K. Usdin, MD Anna Lehman, MD Laura Cif, PhD Phillip A. Richmond
Background: Trinucleotide repeat expansions are an emerging class of genetic variants associated with several movement disorders. Unbiased genome-wide analyses can reveal novel genotype-phenotype associations and provide a diagnosis for patients and families. Objectives: To identify the genetic cause of a severe progressive movement disorder phenotype in two affected brothers. Methods: A family of two affected brothers and unaffected parents had extensive phenotyping and natural history followed since birth. Whole-genome and long-read sequencing methods were used to characterize genetic variants and methylation status. Results: We describe a CGG repeat expansion in the 5'-untranslated region of DIP2B in two affected male siblings presenting with a novel DIP2B phenotype including neurodevelopmental disability, dysmorphic traits, and a severe progressive movement disorder (prominent chorea, dystonia, and ataxia). Conclusions: This is the first report of a severe progressive movement disorder phenotype attributed to a CGG repeat expansion in the DIP2B 5'-UTR.
{"title":"DIP2B CGG repeat expansion in siblings with neurodevelopmental disability and progressive movement disorder","authors":"Emilie T. Théberge MSc, Kate Durbano, Diane Demailly, Sophie Huby, Arezoo Mohajeri MSc, Canada Consortium, C. Karnebeek, G. A. Md, K. Usdin, MD Anna Lehman, MD Laura Cif, PhD Phillip A. Richmond","doi":"10.1101/2024.06.05.24308127","DOIUrl":"https://doi.org/10.1101/2024.06.05.24308127","url":null,"abstract":"Background: Trinucleotide repeat expansions are an emerging class of genetic variants associated with several movement disorders. Unbiased genome-wide analyses can reveal novel genotype-phenotype associations and provide a diagnosis for patients and families. Objectives: To identify the genetic cause of a severe progressive movement disorder phenotype in two affected brothers. Methods: A family of two affected brothers and unaffected parents had extensive phenotyping and natural history followed since birth. Whole-genome and long-read sequencing methods were used to characterize genetic variants and methylation status. Results: We describe a CGG repeat expansion in the 5'-untranslated region of DIP2B in two affected male siblings presenting with a novel DIP2B phenotype including neurodevelopmental disability, dysmorphic traits, and a severe progressive movement disorder (prominent chorea, dystonia, and ataxia). Conclusions: This is the first report of a severe progressive movement disorder phenotype attributed to a CGG repeat expansion in the DIP2B 5'-UTR.","PeriodicalId":506788,"journal":{"name":"medRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141265655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-05DOI: 10.1101/2024.06.05.24308476
R. Kellerman, O. Nayshool, O. Barel, S. Paz, N. Amariglio, E. Klang, G. Rechavi
Most known pathogenic mutations occur in protein-coding regions of DNA and change the way proteins are made. Deciphering the protein structure therefore provides great insight into the molecular mechanisms underlying biological functions in human disease. While there have recently been major advances in the artificial intelligence-based prediction of protein structure, the determination of the biological and clinical relevance of specific mutations is not yet up to clinical standards. This challenge is of utmost medical importance when decisions, as critical as suggesting termination of pregnancy or recommending cancer-directed rational drugs, depend on the accuracy of prediction of the effect of the specific mutation. Currently, available tools are aiming to characterize the effect of a mutation on the unctionality of the protein according to biochemical criteria, independent of the biological context. A specific change in protein structure can result either in loss of function (LOF) or gain-of-function (GOF) and the ability to identify the directionality of effect needs to be taken into consideration when interpreting the biological outcome of the mutation. Here we describe Triple-modalities Variant Interpretation and Analysis (TriVIAI), a tool incorporating three complementing modalities for improved prediction of missense mutations pathogenicity: protein language model (pLM), graph neural network (GNN) and a tabular model incorporating physical properties from the protein structure. The TriVIAl ensemble's predictions compare favorably with the existing tools across various metrics, achieving an AUC-ROC of 0.887, a precision-recall curve (PRC) score of 0.68, and a Brier score of 0.16. The TriVIAI ensemble is also endowed with two major advantages compared to other available tools. The first is the incorporation of biological insights which allow to differentiate between GOF mutations that tend to cluster in specific hotspots and affect structure in a specific functional way versus LOF mutations that are usually dispersed and can cripple the protein in a variety of different ways. Importantly, the advantage over other available tools is more noticeable with GOF mutations as their effect on the protein structure is less disruptive and can be misinterpreted by current variant prioritization strategies. Until now available AI-based pathogenicity predicting algorithms were a black box for the users. The second significant advantage of TriVIAI is the explainability of the ensemble which contrasts the other available AI-based pathogenicity predicting algorithms which constitute a black box for the users. This explainability feature is of major importance considering the clinical responsibility of the medical decision-makers using AI-based pathogenicity predictors.
{"title":"Mutation Pathogenicity Prediction by a Biology Based Explainable AI Multi-Modal Algorithm","authors":"R. Kellerman, O. Nayshool, O. Barel, S. Paz, N. Amariglio, E. Klang, G. Rechavi","doi":"10.1101/2024.06.05.24308476","DOIUrl":"https://doi.org/10.1101/2024.06.05.24308476","url":null,"abstract":"Most known pathogenic mutations occur in protein-coding regions of DNA and change the way proteins are made. Deciphering the protein structure therefore provides great insight into the molecular mechanisms underlying biological functions in human disease. While there have recently been major advances in the artificial intelligence-based prediction of protein structure, the determination of the biological and clinical relevance of specific mutations is not yet up to clinical standards. This challenge is of utmost medical importance when decisions, as critical as suggesting termination of pregnancy or recommending cancer-directed rational drugs, depend on the accuracy of prediction of the effect of the specific mutation. Currently, available tools are aiming to characterize the effect of a mutation on the unctionality of the protein according to biochemical criteria, independent of the biological context. A specific change in protein structure can result either in loss of function (LOF) or gain-of-function (GOF) and the ability to identify the directionality of effect needs to be taken into consideration when interpreting the biological outcome of the mutation. Here we describe Triple-modalities Variant Interpretation and Analysis (TriVIAI), a tool incorporating three complementing modalities for improved prediction of missense mutations pathogenicity: protein language model (pLM), graph neural network (GNN) and a tabular model incorporating physical properties from the protein structure. The TriVIAl ensemble's predictions compare favorably with the existing tools across various metrics, achieving an AUC-ROC of 0.887, a precision-recall curve (PRC) score of 0.68, and a Brier score of 0.16. The TriVIAI ensemble is also endowed with two major advantages compared to other available tools. The first is the incorporation of biological insights which allow to differentiate between GOF mutations that tend to cluster in specific hotspots and affect structure in a specific functional way versus LOF mutations that are usually dispersed and can cripple the protein in a variety of different ways. Importantly, the advantage over other available tools is more noticeable with GOF mutations as their effect on the protein structure is less disruptive and can be misinterpreted by current variant prioritization strategies. Until now available AI-based pathogenicity predicting algorithms were a black box for the users. The second significant advantage of TriVIAI is the explainability of the ensemble which contrasts the other available AI-based pathogenicity predicting algorithms which constitute a black box for the users. This explainability feature is of major importance considering the clinical responsibility of the medical decision-makers using AI-based pathogenicity predictors.","PeriodicalId":506788,"journal":{"name":"medRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141265521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-05DOI: 10.1101/2024.06.04.24308149
A. Santarsieri, Emily Mitchell, My H. Pham, R. Sanghvi, Janina Jablonski, H. Lee-Six, K. Sturgess, Pauline Brice, T. Menne, Wendy Osborne, T. Creasey, K. Ardeshna, Joanna Baxter, S. Behan, K. Bhuller, Stephen Booth, N. Chavda, Graham P Collins, Dominic Culligan, K. Cwynarski, Andrew Davies, A. Downing, David Dutton, Michelle Furtado, E. Gallop‐Evans, Andrew Hodson, David Hopkins, H. Hsu, Sunil Iyengar, Stephen G. Jones, M. Karanth, K. Linton, O. C. Lomas, N. Martínez-Calle, Abhinav Mathur, Pamela McKay, S. Nagumantry, Elizabeth H. Phillips, Neil Phillips, John Frederick Rudge, Nimish K. Shah, G. Stafford, A. Sternberg, R. Trickey, B. Uttenthal, N. Wetherall, Xiao-Yin Zhang, Andrew K. McMillan, Nicholas Coleman, Michael R. Stratton, E. Laurenti, P. Borchmann, S. Borchmann, Peter J. Campbell, R. Rahbari, G. Follows
Background Procarbazine-containing chemotherapy regimens associate with cytopenias and infertility, suggesting stem cell toxicity. Procarbazine in eBEACOPP (escalated dose bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, prednisolone) is increasingly replaced with dacarbazine (eBEACOPDac) to reduce toxicity, although limited genomic and clinical data support this substitution. Methods To assess mutagenic and clinical consequences of dacarbazine-procarbazine substitutions, we compared mutational landscapes in haematopoietic stem and progenitor cells (HSPCs) from patients treated with different Hodgkin regimens and children, sperm and bowel tissue from procarbazine-treated patients. We compared efficacy and toxicity data of a multicentre eBEACOPDac-treated patient cohort, with eBEACOPP clinical trial and real-world datasets. Results eBEACOPP-treated patients exhibit a higher burden of point mutations, small insertions and deletions in HSPCs compared to eBEACOPDac and ABVD (doxorubicin, bleomycin, vinblastine, dacarbazine)-treated patients. Two novel mutational signatures, SBSA (SBS25-like) and SBSB were identified in HSPCs, neoplastic and normal colon from only procarbazine-treated patients. SBSB was also identified in germline DNA of three children conceived post-eBEACOPP and sperm of an eBEACOPP-treated male. The dacarbazine substitution did not appear to compromise efficacy; 3-year progression-free survival of 312 eBEACOPDac patients (93.3%; CI95=90.3-96.4%) mirrored that of 1945 HD18-trial eBEACOPP patients (93.3%; CI95=92.1-94.4%). eBEACOPDac-treated patients required fewer blood transfusions, demonstrated higher post-chemotherapy sperm concentrations, and experienced earlier resumption of menstrual periods. Conclusions Procarbazine induces a higher mutational burden and novel mutational signatures in eBEACOPP-treated patients and their germline DNA raising concerns for hereditary consequences. However, replacing procarbazine with dacarbazine appears to mitigate gonadal and stem cell toxicity while maintaining comparable clinical efficacy.
{"title":"Procarbazine-induced Genomic Toxicity in Hodgkin Lymphoma Survivors","authors":"A. Santarsieri, Emily Mitchell, My H. Pham, R. Sanghvi, Janina Jablonski, H. Lee-Six, K. Sturgess, Pauline Brice, T. Menne, Wendy Osborne, T. Creasey, K. Ardeshna, Joanna Baxter, S. Behan, K. Bhuller, Stephen Booth, N. Chavda, Graham P Collins, Dominic Culligan, K. Cwynarski, Andrew Davies, A. Downing, David Dutton, Michelle Furtado, E. Gallop‐Evans, Andrew Hodson, David Hopkins, H. Hsu, Sunil Iyengar, Stephen G. Jones, M. Karanth, K. Linton, O. C. Lomas, N. Martínez-Calle, Abhinav Mathur, Pamela McKay, S. Nagumantry, Elizabeth H. Phillips, Neil Phillips, John Frederick Rudge, Nimish K. Shah, G. Stafford, A. Sternberg, R. Trickey, B. Uttenthal, N. Wetherall, Xiao-Yin Zhang, Andrew K. McMillan, Nicholas Coleman, Michael R. Stratton, E. Laurenti, P. Borchmann, S. Borchmann, Peter J. Campbell, R. Rahbari, G. Follows","doi":"10.1101/2024.06.04.24308149","DOIUrl":"https://doi.org/10.1101/2024.06.04.24308149","url":null,"abstract":"Background Procarbazine-containing chemotherapy regimens associate with cytopenias and infertility, suggesting stem cell toxicity. Procarbazine in eBEACOPP (escalated dose bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, prednisolone) is increasingly replaced with dacarbazine (eBEACOPDac) to reduce toxicity, although limited genomic and clinical data support this substitution. Methods To assess mutagenic and clinical consequences of dacarbazine-procarbazine substitutions, we compared mutational landscapes in haematopoietic stem and progenitor cells (HSPCs) from patients treated with different Hodgkin regimens and children, sperm and bowel tissue from procarbazine-treated patients. We compared efficacy and toxicity data of a multicentre eBEACOPDac-treated patient cohort, with eBEACOPP clinical trial and real-world datasets. Results eBEACOPP-treated patients exhibit a higher burden of point mutations, small insertions and deletions in HSPCs compared to eBEACOPDac and ABVD (doxorubicin, bleomycin, vinblastine, dacarbazine)-treated patients. Two novel mutational signatures, SBSA (SBS25-like) and SBSB were identified in HSPCs, neoplastic and normal colon from only procarbazine-treated patients. SBSB was also identified in germline DNA of three children conceived post-eBEACOPP and sperm of an eBEACOPP-treated male. The dacarbazine substitution did not appear to compromise efficacy; 3-year progression-free survival of 312 eBEACOPDac patients (93.3%; CI95=90.3-96.4%) mirrored that of 1945 HD18-trial eBEACOPP patients (93.3%; CI95=92.1-94.4%). eBEACOPDac-treated patients required fewer blood transfusions, demonstrated higher post-chemotherapy sperm concentrations, and experienced earlier resumption of menstrual periods. Conclusions Procarbazine induces a higher mutational burden and novel mutational signatures in eBEACOPP-treated patients and their germline DNA raising concerns for hereditary consequences. However, replacing procarbazine with dacarbazine appears to mitigate gonadal and stem cell toxicity while maintaining comparable clinical efficacy.","PeriodicalId":506788,"journal":{"name":"medRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141265503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-05DOI: 10.1101/2024.06.05.24308493
Hilary Coon, Andrey Shabalin, Emily DiBlasi, Eric T. Monson, Seonggyun Han, Erin A Kaufman, MS DanliChen, Brent Kious, Nicolette Molina, MS ZheYu, Michael Staley, David K Crockett, BA SarahM.Colbert, Niamh Mullins, A. Bakian, Anna R. Docherty, Brooks Keeshin
Nonfatal suicidality is the most robust predictor of suicide death. However, only ~10% of those who survive an attempt go on to die by suicide. Moreover, ~50% of suicide deaths occur in the absence of prior known attempts, suggesting risks other than nonfatal suicide attempt need to be identified. We studied data from 4,000 population-ascertained suicide deaths and 26,191 population controls to improve understanding of risks leading to suicide death. This study included 2,253 suicide deaths and 3,375 controls with evidence of nonfatal suicidality (SUI_SI/SB and CTL_SI/SB) from diagnostic codes and natural language processing of electronic health records notes. Characteristics of these groups were compared to 1,669 suicides with no prior nonfatal SI/SB (SUI_None) and 22,816 controls with no lifetime suicidality (CTL_None). The SUI_None and CTL_None groups had fewer diagnoses and were older than SUI_SI/SB and CTL_SI/SB. Mental health diagnoses were far less common in both the SUI_None and CTL_None groups; mental health problems were less associated with suicide death than with presence of SI/SB. Physical health diagnoses were conversely more often associated with risk of suicide death than with presence of SI/SB. Pending replication, results indicate highly significant clinical differences among suicide deaths with versus without prior nonfatal SI/SB.
{"title":"Absence of nonfatal suicidal behavior preceding suicide death reveals differences in clinical risks","authors":"Hilary Coon, Andrey Shabalin, Emily DiBlasi, Eric T. Monson, Seonggyun Han, Erin A Kaufman, MS DanliChen, Brent Kious, Nicolette Molina, MS ZheYu, Michael Staley, David K Crockett, BA SarahM.Colbert, Niamh Mullins, A. Bakian, Anna R. Docherty, Brooks Keeshin","doi":"10.1101/2024.06.05.24308493","DOIUrl":"https://doi.org/10.1101/2024.06.05.24308493","url":null,"abstract":"Nonfatal suicidality is the most robust predictor of suicide death. However, only ~10% of those who survive an attempt go on to die by suicide. Moreover, ~50% of suicide deaths occur in the absence of prior known attempts, suggesting risks other than nonfatal suicide attempt need to be identified. We studied data from 4,000 population-ascertained suicide deaths and 26,191 population controls to improve understanding of risks leading to suicide death. This study included 2,253 suicide deaths and 3,375 controls with evidence of nonfatal suicidality (SUI_SI/SB and CTL_SI/SB) from diagnostic codes and natural language processing of electronic health records notes. Characteristics of these groups were compared to 1,669 suicides with no prior nonfatal SI/SB (SUI_None) and 22,816 controls with no lifetime suicidality (CTL_None). The SUI_None and CTL_None groups had fewer diagnoses and were older than SUI_SI/SB and CTL_SI/SB. Mental health diagnoses were far less common in both the SUI_None and CTL_None groups; mental health problems were less associated with suicide death than with presence of SI/SB. Physical health diagnoses were conversely more often associated with risk of suicide death than with presence of SI/SB. Pending replication, results indicate highly significant clinical differences among suicide deaths with versus without prior nonfatal SI/SB.","PeriodicalId":506788,"journal":{"name":"medRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141265626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-05DOI: 10.1101/2024.06.04.24308434
Divyanshu Tak, Biniam A. Garomsa, A. Zapaishchykova, Zezhong Ye, Sri Vajapeyam, Maryam Mahootiha, Juan Carlos, Climent Pardo, Ceilidh Smith, Ariana M. Familiar, Kevin X. Liu, Sanjay Prabhu, P. Bandopadhayay, A. Nabavizadeh, Sabine Mueller, Hugo, Jwl Aerts, Daphne A Haas-Kogan, T. Poussaint, Benjamin H. Kann
Pediatric glioma recurrence following surgery causes morbidity and mortality, and thus, children undergo frequent longitudinal magnetic resonance (MR) surveillance postoperatively to inform management. However, the pattern and severity of pediatric glioma recurrences are highly variable and challenging to predict with current clinical and genomic stratifications. Quantitative imaging analyses have shown promise for cancer risk prediction, and longitudinal analysis of glioma MR may improve the ability to predict future recurrence. Here, we propose a novel self-supervised, deep learning approach to longitudinal brain MR analysis, temporal learning, that models the spatiotemporal information from a patients prior, longitudinal brain MRs to predict future recurrence. We apply temporal learning to pediatric glioma surveillance imaging for 715 patients (3,994 scans) from four distinct clinical settings. We find that longitudinal imaging analysis with temporal learning improves recurrence prediction performance by up to 41% compared to training from scratch, with improvements in performance in both low- and high-grade glioma. We find that recurrence prediction accuracy increases incrementally with the number of historical scans available per patient. Temporal deep learning may enable point-of-care decision-support for pediatric glioma to personalize surveillance and postoperative therapy.
{"title":"Longitudinal risk prediction for pediatric glioma with temporal deep learning","authors":"Divyanshu Tak, Biniam A. Garomsa, A. Zapaishchykova, Zezhong Ye, Sri Vajapeyam, Maryam Mahootiha, Juan Carlos, Climent Pardo, Ceilidh Smith, Ariana M. Familiar, Kevin X. Liu, Sanjay Prabhu, P. Bandopadhayay, A. Nabavizadeh, Sabine Mueller, Hugo, Jwl Aerts, Daphne A Haas-Kogan, T. Poussaint, Benjamin H. Kann","doi":"10.1101/2024.06.04.24308434","DOIUrl":"https://doi.org/10.1101/2024.06.04.24308434","url":null,"abstract":"Pediatric glioma recurrence following surgery causes morbidity and mortality, and thus, children undergo frequent longitudinal magnetic resonance (MR) surveillance postoperatively to inform management. However, the pattern and severity of pediatric glioma recurrences are highly variable and challenging to predict with current clinical and genomic stratifications. Quantitative imaging analyses have shown promise for cancer risk prediction, and longitudinal analysis of glioma MR may improve the ability to predict future recurrence. Here, we propose a novel self-supervised, deep learning approach to longitudinal brain MR analysis, temporal learning, that models the spatiotemporal information from a patients prior, longitudinal brain MRs to predict future recurrence. We apply temporal learning to pediatric glioma surveillance imaging for 715 patients (3,994 scans) from four distinct clinical settings. We find that longitudinal imaging analysis with temporal learning improves recurrence prediction performance by up to 41% compared to training from scratch, with improvements in performance in both low- and high-grade glioma. We find that recurrence prediction accuracy increases incrementally with the number of historical scans available per patient. Temporal deep learning may enable point-of-care decision-support for pediatric glioma to personalize surveillance and postoperative therapy.","PeriodicalId":506788,"journal":{"name":"medRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141265336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-05DOI: 10.1101/2024.06.04.24308462
M. Koprivanac, K. Bauza, N. Smedira, G. B. Pettersson, S. Unai, P. Barrios, N. Oh, F. Stembal, V. Lara-Erazo, E. Soltesz, F. G. Baikaeen, H. Elgharably, M. Y. Desai, T. K. Ming Wang, P. Houghtaling, L. Svensson, A. Gillinov, K. McCurry, D. R. Johnston, E. Blackstone, A. Klein, M. Tong
Background: Pericardiectomy is definitive treatment for constrictive pericarditis. However, extent of resection (radical versus partial) and use of cardiopulmonary bypass (CPB) are debated. Objectives: To determine the association of extent of pericardial resection and use of CPB with outcomes. Methods: From January 2000 to January 2022, 565 patients with constrictive pericarditis underwent radical (n=445, 314 [71%] on CPB) or partial (n=120, 67 [56%] on CPB) pericardiectomy at Cleveland Clinic. Outcomes stratified by extent of pericardial resection and use of CPB were compared after propensity-score matching. Results: Both radical pericardiectomy and CPB use (67% [381/565]) increased over time. Among 88 propensity-matched pairs (73% of possible matches), immediate postoperative cardiac index increased (P<0.001) in both groups by a median of 1.0 L{middle dot}min-1{middle dot}m-2. There were no significant differences between radical versus partial resection groups in occurrence of reoperation for bleeding (2.3%, [2/88] vs. 0, P=.50). Median postoperative hospital length of stay was 10 versus 8.5 days (P=.02). Operative mortality was 9.1% (8/88) versus 6.8% (6/88) (P=.58). 10-year survival was 54% versus 41%, with a higher propensity-adjusted hazard ratio after partial resection (1.9, 95% CI 1.2-3.1). Conclusions: When surgical intervention is deemed necessary, radical - rather than partial - resection for constrictive pericarditis can be performed with low surgical mortality and morbidity. Radical pericardiectomy can be accomplished on CPB and results in better long-term survival.
{"title":"Radical Pericardiectomy and Use of Cardiopulmonary Bypass for Constrictive Pericarditis","authors":"M. Koprivanac, K. Bauza, N. Smedira, G. B. Pettersson, S. Unai, P. Barrios, N. Oh, F. Stembal, V. Lara-Erazo, E. Soltesz, F. G. Baikaeen, H. Elgharably, M. Y. Desai, T. K. Ming Wang, P. Houghtaling, L. Svensson, A. Gillinov, K. McCurry, D. R. Johnston, E. Blackstone, A. Klein, M. Tong","doi":"10.1101/2024.06.04.24308462","DOIUrl":"https://doi.org/10.1101/2024.06.04.24308462","url":null,"abstract":"Background: Pericardiectomy is definitive treatment for constrictive pericarditis. However, extent of resection (radical versus partial) and use of cardiopulmonary bypass (CPB) are debated. Objectives: To determine the association of extent of pericardial resection and use of CPB with outcomes. Methods: From January 2000 to January 2022, 565 patients with constrictive pericarditis underwent radical (n=445, 314 [71%] on CPB) or partial (n=120, 67 [56%] on CPB) pericardiectomy at Cleveland Clinic. Outcomes stratified by extent of pericardial resection and use of CPB were compared after propensity-score matching. Results: Both radical pericardiectomy and CPB use (67% [381/565]) increased over time. Among 88 propensity-matched pairs (73% of possible matches), immediate postoperative cardiac index increased (P<0.001) in both groups by a median of 1.0 L{middle dot}min-1{middle dot}m-2. There were no significant differences between radical versus partial resection groups in occurrence of reoperation for bleeding (2.3%, [2/88] vs. 0, P=.50). Median postoperative hospital length of stay was 10 versus 8.5 days (P=.02). Operative mortality was 9.1% (8/88) versus 6.8% (6/88) (P=.58). 10-year survival was 54% versus 41%, with a higher propensity-adjusted hazard ratio after partial resection (1.9, 95% CI 1.2-3.1). Conclusions: When surgical intervention is deemed necessary, radical - rather than partial - resection for constrictive pericarditis can be performed with low surgical mortality and morbidity. Radical pericardiectomy can be accomplished on CPB and results in better long-term survival.","PeriodicalId":506788,"journal":{"name":"medRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141265449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-05DOI: 10.1101/2024.06.04.24308470
Kevin C. Ma, D. Surie, A. Lauring, Mph Emily T. Martin PhD, Aleda M Leis, Leigh Papalambros Mph, Manjusha Gaglani Mbbs, Christie Columbus, Robert L Gottlieb, S. Ghamande, MSc Ithan D. Peltan MD, Samuel M. Brown, A. Ginde, Nicholas M. Mohr, K. Gibbs, David N. Hager, Safa Saeed Mbbs, M. Prekker, M. Gong, Amira Mohamed, N. Johnson, Vasisht Srinivasan, Jay S. Steingrub, Akram Khan Mbbs, Catherine L. Hough, Abhijit Duggal, Jennifer G. Wilson, N. Qadir, PhD Steven Y. Chang MD, Christopher Mallow, Msci Jennie H. Kwon DO, Bijal Parikh, Mph Ivana A. Vaughn PhD, Mayur Ramesh, MSc Basmah Safdar MD, J. Mosier, Estelle S. Harris, Nathan I. Shapiro, Mph Jamie Felzer MD, Yuwei Zhu, Mph Carlos G Grijalva MD, Natasha Halasa, James D. Chappell, K. Womack, J. Rhoads, A. Baughman, S. Swan, 27 Mph, MS CassandraA.Johnson, MSc Todd W. Rice MD, Jonathan D. Casey, Mhs Paul W. Blair MD, MSc Jin H. Han MD, Sascha Ellington, Nathaniel M Lewis, Natalie Thornburg, Clinton R. Paden, PhD Lydia J. Atherton DVM, Mph Wesley H. Self MD, F.
Background: Assessing COVID-19 vaccine effectiveness (VE) and severity of SARS-CoV-2 variants can inform public health risk assessments and decisions about vaccine composition. BA.2.86 and its descendants, including JN.1 (referred to collectively as "JN lineages"), emerged in late 2023 and exhibited substantial genomic divergence from co-circulating XBB lineages. Methods: We analyzed patients hospitalized with COVID-19-like illness at 26 hospitals in 20 U.S. states admitted October 18, 2023-March 9, 2024. Using a test-negative, case-control design, we estimated the effectiveness of an updated 2023-2024 (Monovalent XBB.1.5) COVID-19 vaccine dose against sequence-confirmed XBB and JN lineage hospitalization using logistic regression. Odds of severe outcomes, including intensive care unit (ICU) admission and invasive mechanical ventilation (IMV) or death, were compared for JN versus XBB lineage hospitalizations using logistic regression. Results: 585 case-patients with XBB lineages, 397 case-patients with JN lineages, and 4,580 control-patients were included. VE in the first 7-89 days after receipt of an updated dose was 54.2% (95% CI = 36.1%-67.1%) against XBB lineage hospitalization and 32.7% (95% CI = 1.9%-53.8%) against JN lineage hospitalization. Odds of ICU admission (adjusted odds ratio [aOR] 0.80; 95% CI = 0.46-1.38) and IMV or death (aOR 0.69; 95% CI = 0.34-1.40) were not significantly different among JN compared to XBB lineage hospitalizations. Conclusions: Updated 2023-2024 COVID-19 vaccination provided protection against both XBB and JN lineage hospitalization, but protection against the latter may be attenuated by immune escape. Clinical severity of JN lineage hospitalizations was not higher relative to XBB lineage hospitalizations.
{"title":"Effectiveness of Updated 2023-2024 (Monovalent XBB.1.5) COVID-19 Vaccination Against SARS-CoV-2 Omicron XBB and BA.2.86/JN.1 Lineage Hospitalization and a Comparison of Clinical Severity -- IVY Network, 26 Hospitals, October 18, 2023-March 9, 2024","authors":"Kevin C. Ma, D. Surie, A. Lauring, Mph Emily T. Martin PhD, Aleda M Leis, Leigh Papalambros Mph, Manjusha Gaglani Mbbs, Christie Columbus, Robert L Gottlieb, S. Ghamande, MSc Ithan D. Peltan MD, Samuel M. Brown, A. Ginde, Nicholas M. Mohr, K. Gibbs, David N. Hager, Safa Saeed Mbbs, M. Prekker, M. Gong, Amira Mohamed, N. Johnson, Vasisht Srinivasan, Jay S. Steingrub, Akram Khan Mbbs, Catherine L. Hough, Abhijit Duggal, Jennifer G. Wilson, N. Qadir, PhD Steven Y. Chang MD, Christopher Mallow, Msci Jennie H. Kwon DO, Bijal Parikh, Mph Ivana A. Vaughn PhD, Mayur Ramesh, MSc Basmah Safdar MD, J. Mosier, Estelle S. Harris, Nathan I. Shapiro, Mph Jamie Felzer MD, Yuwei Zhu, Mph Carlos G Grijalva MD, Natasha Halasa, James D. Chappell, K. Womack, J. Rhoads, A. Baughman, S. Swan, 27 Mph, MS CassandraA.Johnson, MSc Todd W. Rice MD, Jonathan D. Casey, Mhs Paul W. Blair MD, MSc Jin H. Han MD, Sascha Ellington, Nathaniel M Lewis, Natalie Thornburg, Clinton R. Paden, PhD Lydia J. Atherton DVM, Mph Wesley H. Self MD, F. ","doi":"10.1101/2024.06.04.24308470","DOIUrl":"https://doi.org/10.1101/2024.06.04.24308470","url":null,"abstract":"Background: Assessing COVID-19 vaccine effectiveness (VE) and severity of SARS-CoV-2 variants can inform public health risk assessments and decisions about vaccine composition. BA.2.86 and its descendants, including JN.1 (referred to collectively as \"JN lineages\"), emerged in late 2023 and exhibited substantial genomic divergence from co-circulating XBB lineages. Methods: We analyzed patients hospitalized with COVID-19-like illness at 26 hospitals in 20 U.S. states admitted October 18, 2023-March 9, 2024. Using a test-negative, case-control design, we estimated the effectiveness of an updated 2023-2024 (Monovalent XBB.1.5) COVID-19 vaccine dose against sequence-confirmed XBB and JN lineage hospitalization using logistic regression. Odds of severe outcomes, including intensive care unit (ICU) admission and invasive mechanical ventilation (IMV) or death, were compared for JN versus XBB lineage hospitalizations using logistic regression. Results: 585 case-patients with XBB lineages, 397 case-patients with JN lineages, and 4,580 control-patients were included. VE in the first 7-89 days after receipt of an updated dose was 54.2% (95% CI = 36.1%-67.1%) against XBB lineage hospitalization and 32.7% (95% CI = 1.9%-53.8%) against JN lineage hospitalization. Odds of ICU admission (adjusted odds ratio [aOR] 0.80; 95% CI = 0.46-1.38) and IMV or death (aOR 0.69; 95% CI = 0.34-1.40) were not significantly different among JN compared to XBB lineage hospitalizations. Conclusions: Updated 2023-2024 COVID-19 vaccination provided protection against both XBB and JN lineage hospitalization, but protection against the latter may be attenuated by immune escape. Clinical severity of JN lineage hospitalizations was not higher relative to XBB lineage hospitalizations.","PeriodicalId":506788,"journal":{"name":"medRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141265356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-05DOI: 10.1101/2024.06.04.24308425
M. Birken, A. Kular, P. Nyikavaranda, J. Parkinson, L. Mitchell, K. Fraser, V. C. White, J. Seale, J. Hardy, C. Stone, M. K. Holden, T. Elliot, Z. Li, H. Mbeah-Bankas, L. Wood, F. Lobban, B. Lloyd-Evans, S. Johnson
Purpose: This study, co-produced by a team of academics, lived experience researchers and clinicians, explores the views and experiences of people who have been compulsorily detained in hospital under the Mental Health Act (1983) (MHA) in England, to understand how and why, from their perspective, compulsory detentions occur, and what might help prevent them. Methods: Semi-structured qualitative interviews were conducted with 20 people (55% male, 40% Black/Black British, 30% White British) who had been compulsory detained in hospital within the past 5 years. Lived experience researchers with relevant personal experience carried out interviews via telephone or videoconference, and participated in analysis of data via a template approach. Results: We derived three over-arching themes from interviews. The first theme was individual factors increasing or reducing likelihood of being detained and it encompassed factors related to peoples own lives and attitudes, including life stressors, not taking medication, the risk individuals may pose to themselves or others, and their attitude to and management of their mental health. The second theme was family and support network which reflects how attitudes and support from family, friends and support network may contribute to compulsory detentions or support people to stay well. The third theme was need for improvement in service responses which identified limitations of services that contribute to detention, including lack of collaborative care and choice, poor quality of professional support, and discriminatory attitudes from staff. Each theme also included potential approaches to addressing these limitations and reducing compulsory detentions. Conclusion: Findings suggest multiple interacting factors may lead to people being detained in hospital under the MHA, and that improvements to services, such as increasing collaborative care and service user-led family involvement, could prevent further detentions.
{"title":"Exploring pathways to compulsory detention in psychiatric hospital and ways to prevent repeat detentions; Service user perspectives","authors":"M. Birken, A. Kular, P. Nyikavaranda, J. Parkinson, L. Mitchell, K. Fraser, V. C. White, J. Seale, J. Hardy, C. Stone, M. K. Holden, T. Elliot, Z. Li, H. Mbeah-Bankas, L. Wood, F. Lobban, B. Lloyd-Evans, S. Johnson","doi":"10.1101/2024.06.04.24308425","DOIUrl":"https://doi.org/10.1101/2024.06.04.24308425","url":null,"abstract":"Purpose: This study, co-produced by a team of academics, lived experience researchers and clinicians, explores the views and experiences of people who have been compulsorily detained in hospital under the Mental Health Act (1983) (MHA) in England, to understand how and why, from their perspective, compulsory detentions occur, and what might help prevent them. Methods: Semi-structured qualitative interviews were conducted with 20 people (55% male, 40% Black/Black British, 30% White British) who had been compulsory detained in hospital within the past 5 years. Lived experience researchers with relevant personal experience carried out interviews via telephone or videoconference, and participated in analysis of data via a template approach. Results: We derived three over-arching themes from interviews. The first theme was individual factors increasing or reducing likelihood of being detained and it encompassed factors related to peoples own lives and attitudes, including life stressors, not taking medication, the risk individuals may pose to themselves or others, and their attitude to and management of their mental health. The second theme was family and support network which reflects how attitudes and support from family, friends and support network may contribute to compulsory detentions or support people to stay well. The third theme was need for improvement in service responses which identified limitations of services that contribute to detention, including lack of collaborative care and choice, poor quality of professional support, and discriminatory attitudes from staff. Each theme also included potential approaches to addressing these limitations and reducing compulsory detentions. Conclusion: Findings suggest multiple interacting factors may lead to people being detained in hospital under the MHA, and that improvements to services, such as increasing collaborative care and service user-led family involvement, could prevent further detentions.","PeriodicalId":506788,"journal":{"name":"medRxiv","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141265733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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