{"title":"Letter to the Editor Concerning \"Glucagon-Like Peptide Agonists for Weight Management in Antipsychotic-Induced Weight Gain: A Systematic Review and Meta-Analysis\".","authors":"Anders Fink-Jensen, Christoph U Correll","doi":"10.1111/acps.13772","DOIUrl":"https://doi.org/10.1111/acps.13772","url":null,"abstract":"","PeriodicalId":108,"journal":{"name":"Acta Psychiatrica Scandinavica","volume":" ","pages":""},"PeriodicalIF":5.3,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142612924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tessa F Blanken, Rob Kok, Jasmien Obbels, Simon Lambrichts, Pascal Sienaert, Esmée Verwijk
Objective: While electroconvulsive therapy (ECT) for the treatment of major depressive disorder is effective, individual response is variable and difficult to predict. These difficulties may in part result from heterogeneity at the symptom level. We aim to predict remission using baseline depression symptoms, taking the associations among symptoms into account, by using a network analysis approach.
Method: We combined individual patient data from two randomized controlled trials (total N = 161) and estimated a Mixed Graphical Model to estimate which baseline depression symptoms (corresponding to HRSD-17 items) uniquely predicted remission (defined as either HRSD≤7 or MADRS<10). We included study as moderator to evaluate study heterogeneity. For symptoms directly predictive of remission we computed odds ratios.
Results: Three baseline symptoms were uniquely predictive of remission: suicidality negatively predicted remission (OR = 0.75; bootstrapped confidence interval (bCI) = 0.44-1.00) whereas retardation (OR = 1.21; bCI = 1.00-2.02) and hypochondriasis (OR = 1.31; bCI = 1.00-2.25) positively predicted remission. The estimated effects did not differ across trials as no moderation effects were found.
Conclusion: By using a network analysis approach this study identified that the presence of suicidal ideation predicts an overall worse treatment outcome. Psychomotor retardation and hypochondriasis, on the other hand, seem to be associated with a better outcome.
{"title":"Prediction of electroconvulsive therapy outcome: A network analysis approach.","authors":"Tessa F Blanken, Rob Kok, Jasmien Obbels, Simon Lambrichts, Pascal Sienaert, Esmée Verwijk","doi":"10.1111/acps.13770","DOIUrl":"https://doi.org/10.1111/acps.13770","url":null,"abstract":"<p><strong>Objective: </strong>While electroconvulsive therapy (ECT) for the treatment of major depressive disorder is effective, individual response is variable and difficult to predict. These difficulties may in part result from heterogeneity at the symptom level. We aim to predict remission using baseline depression symptoms, taking the associations among symptoms into account, by using a network analysis approach.</p><p><strong>Method: </strong>We combined individual patient data from two randomized controlled trials (total N = 161) and estimated a Mixed Graphical Model to estimate which baseline depression symptoms (corresponding to HRSD-17 items) uniquely predicted remission (defined as either HRSD≤7 or MADRS<10). We included study as moderator to evaluate study heterogeneity. For symptoms directly predictive of remission we computed odds ratios.</p><p><strong>Results: </strong>Three baseline symptoms were uniquely predictive of remission: suicidality negatively predicted remission (OR = 0.75; bootstrapped confidence interval (bCI) = 0.44-1.00) whereas retardation (OR = 1.21; bCI = 1.00-2.02) and hypochondriasis (OR = 1.31; bCI = 1.00-2.25) positively predicted remission. The estimated effects did not differ across trials as no moderation effects were found.</p><p><strong>Conclusion: </strong>By using a network analysis approach this study identified that the presence of suicidal ideation predicts an overall worse treatment outcome. Psychomotor retardation and hypochondriasis, on the other hand, seem to be associated with a better outcome.</p>","PeriodicalId":108,"journal":{"name":"Acta Psychiatrica Scandinavica","volume":" ","pages":""},"PeriodicalIF":5.3,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142612925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>Patients with mental disorders have a significantly reduced lifespan,<span><sup>1</sup></span> with overweight/obesity and cardiometabolic-related death being the biggest contributors. Both the underlying mental illness and treatments, especially antipsychotics, contribute to this increased cardiometabolic risk, creating a dilemma between efficacy and desired safety. As a point in fact, clozapine is a second-generation antipsychotic with proven antipsychotic efficacy in otherwise treatment-resistant patients with a diagnosis of schizophrenia. However, clozapine is also linked to a substantial increase in body weight and carries a high risk for metabolic disturbances,<span><sup>2</sup></span> making clinicians, patients, and caretakers reluctant against its use. Additionally, sedentary lifestyle and unhealthy food intake have become a public health issue for populations in the Western world in general. However, they are an even bigger problem among people with severe mental disorders, such as schizophrenia and bipolar disorder. Also, the use of antipsychotics has expanded beyond schizophrenia and bipolar disorder, being used frequently on-label for unipolar depression, but also off-label for impulsive behaviors, insomnia, and anxiety among other conditions.<span><sup>3</sup></span></p><p>Over the last decade, more focus has been paid to monitoring body weight and uncovering potential dysmetabolism by blood sample analysis in people treated with antipsychotics, which are important steps in the right direction. However, clear, and well-established strategies for an effective treatment against overweight/obesity and dysmetabolism in people with mental illness and, especially, those receiving antipsychotics or being mentally ill, remain underdeveloped or, at least, underutilized.<span><sup>4</sup></span></p><p>The most effective strategy for preventing antipsychotic-induced weight gain and dysmetabolism is using these medications only when needed or starting with the antipsychotic with the lowest weight gain potential.<span><sup>4</sup></span> When weight gain and metabolic adverse effects occur, secondary preventive efforts include switching to an antipsychotic linked to less weight gain and dysmetabolism, although the desired weight loss may be limited.<span><sup>5</sup></span> Moreover, in the case of clozapine, which is used in otherwise partial or complete treatment-resistant patients, switching to a less effective antipsychotic, even if it may impose fewer dysmetabolic problems and less increase in body weight, may not be an applicable strategy.<span><sup>6</sup></span> Nonpharmacological interventions such as lifestyle changes against overweight and dysmetabolism are well-known strategies<span><sup>7</sup></span> but-as for the background population-are difficult to implement broadly.</p><p>Traditionally, the adjunctive pharmacological interventions against antipsychotic-associated weight gain have included topiramate and metformin. However,
{"title":"How to treat antipsychotic-related weight gain and metabolic disturbances: Is there a role for GLP-1 receptor agonists?","authors":"Anders Fink-Jensen, Christoph U. Correll","doi":"10.1111/acps.13769","DOIUrl":"10.1111/acps.13769","url":null,"abstract":"<p>Patients with mental disorders have a significantly reduced lifespan,<span><sup>1</sup></span> with overweight/obesity and cardiometabolic-related death being the biggest contributors. Both the underlying mental illness and treatments, especially antipsychotics, contribute to this increased cardiometabolic risk, creating a dilemma between efficacy and desired safety. As a point in fact, clozapine is a second-generation antipsychotic with proven antipsychotic efficacy in otherwise treatment-resistant patients with a diagnosis of schizophrenia. However, clozapine is also linked to a substantial increase in body weight and carries a high risk for metabolic disturbances,<span><sup>2</sup></span> making clinicians, patients, and caretakers reluctant against its use. Additionally, sedentary lifestyle and unhealthy food intake have become a public health issue for populations in the Western world in general. However, they are an even bigger problem among people with severe mental disorders, such as schizophrenia and bipolar disorder. Also, the use of antipsychotics has expanded beyond schizophrenia and bipolar disorder, being used frequently on-label for unipolar depression, but also off-label for impulsive behaviors, insomnia, and anxiety among other conditions.<span><sup>3</sup></span></p><p>Over the last decade, more focus has been paid to monitoring body weight and uncovering potential dysmetabolism by blood sample analysis in people treated with antipsychotics, which are important steps in the right direction. However, clear, and well-established strategies for an effective treatment against overweight/obesity and dysmetabolism in people with mental illness and, especially, those receiving antipsychotics or being mentally ill, remain underdeveloped or, at least, underutilized.<span><sup>4</sup></span></p><p>The most effective strategy for preventing antipsychotic-induced weight gain and dysmetabolism is using these medications only when needed or starting with the antipsychotic with the lowest weight gain potential.<span><sup>4</sup></span> When weight gain and metabolic adverse effects occur, secondary preventive efforts include switching to an antipsychotic linked to less weight gain and dysmetabolism, although the desired weight loss may be limited.<span><sup>5</sup></span> Moreover, in the case of clozapine, which is used in otherwise partial or complete treatment-resistant patients, switching to a less effective antipsychotic, even if it may impose fewer dysmetabolic problems and less increase in body weight, may not be an applicable strategy.<span><sup>6</sup></span> Nonpharmacological interventions such as lifestyle changes against overweight and dysmetabolism are well-known strategies<span><sup>7</sup></span> but-as for the background population-are difficult to implement broadly.</p><p>Traditionally, the adjunctive pharmacological interventions against antipsychotic-associated weight gain have included topiramate and metformin. However,","PeriodicalId":108,"journal":{"name":"Acta Psychiatrica Scandinavica","volume":"151 1","pages":"3-5"},"PeriodicalIF":5.3,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/acps.13769","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142602461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Giuseppe D'Andrea, Diego Quattrone, Giada Tripoli, Edoardo Spinazzola, Charlotte Gayer-Anderson, Hannah E Jongsma, Lucia Sideli, Simona A Stilo, Caterina La Cascia, Laura Ferraro, Daniele La Barbera, Andrea Tortelli, Eva Velthorst, Lieuwe de Haan, Pierre-Michel Llorca, Jose Luis Santos, Manuel Arrojo, Julio Bobes, Julio Sanjuán, Miguel Bernardo, Celso Arango, James B Kirkbride, Peter B Jones, Bart P Rutten, Franck Schürhoff, Andrei Szöke, Jim van Os, Evangelos Vassos, Jean-Paul Selten, Craig Morgan, Marta Di Forti, Ilaria Tarricone, Robin M Murray
Background: Urbanicity is a well-established risk factor for psychosis. Our recent multi-national study found an association between urbanicity and clinical psychosis in Northern Europe but not in Southern Europe. In this study, we hypothesized that the effect of current urbanicity on variation of schizotypy would be greater in North-western Europe countries than in Southern Europe ones.
Methods: We recruited 1080 individuals representative of the populations aged 18-64 of 14 different sites within 5 countries, classified as either North-western Europe (England, France, and The Netherlands) with Southern Europe (Spain and Italy). Our main outcome was schizotypy, assessed through the Structured Interview for Schizotypy-Revised. Our main exposure was current urbanicity, operationalized as local population density. A priori confounders were age, sex, ethnic minority status, childhood maltreatment, and social capital. Schizotypy variation was assessed using multi-level regression analysis. To test the differential effect of urbanicity between North-western and Southern European, we added an interaction term between population density and region of recruitment.
Results: Population density was associated with schizotypy (β = 0.248,95%CI = 0.122-0.375;p < 0.001). The addition of the interaction term improved the model fit (likelihood test ratio:χ2 = 6.85; p = 0.009). The effect of urbanicity on schizotypy was substantially stronger in North-western Europe (β = 0.620,95%CI = 0.362-0.877;p < 0.001) compared with Southern Europe (β = 0.190,95%CI = 0.083-0.297;p = 0.001).
Conclusions: The association between urbanicity and both subclinical schizotypy and clinical psychosis, rather than being universal, is context-specific. Considering that urbanization is a rapid and global process, further research is needed to disentangle the specific factors underlying this relationship.
{"title":"Variation of subclinical psychosis as a function of population density across different European settings: Findings from the multi-national EU-GEI study.","authors":"Giuseppe D'Andrea, Diego Quattrone, Giada Tripoli, Edoardo Spinazzola, Charlotte Gayer-Anderson, Hannah E Jongsma, Lucia Sideli, Simona A Stilo, Caterina La Cascia, Laura Ferraro, Daniele La Barbera, Andrea Tortelli, Eva Velthorst, Lieuwe de Haan, Pierre-Michel Llorca, Jose Luis Santos, Manuel Arrojo, Julio Bobes, Julio Sanjuán, Miguel Bernardo, Celso Arango, James B Kirkbride, Peter B Jones, Bart P Rutten, Franck Schürhoff, Andrei Szöke, Jim van Os, Evangelos Vassos, Jean-Paul Selten, Craig Morgan, Marta Di Forti, Ilaria Tarricone, Robin M Murray","doi":"10.1111/acps.13767","DOIUrl":"https://doi.org/10.1111/acps.13767","url":null,"abstract":"<p><strong>Background: </strong>Urbanicity is a well-established risk factor for psychosis. Our recent multi-national study found an association between urbanicity and clinical psychosis in Northern Europe but not in Southern Europe. In this study, we hypothesized that the effect of current urbanicity on variation of schizotypy would be greater in North-western Europe countries than in Southern Europe ones.</p><p><strong>Methods: </strong>We recruited 1080 individuals representative of the populations aged 18-64 of 14 different sites within 5 countries, classified as either North-western Europe (England, France, and The Netherlands) with Southern Europe (Spain and Italy). Our main outcome was schizotypy, assessed through the Structured Interview for Schizotypy-Revised. Our main exposure was current urbanicity, operationalized as local population density. A priori confounders were age, sex, ethnic minority status, childhood maltreatment, and social capital. Schizotypy variation was assessed using multi-level regression analysis. To test the differential effect of urbanicity between North-western and Southern European, we added an interaction term between population density and region of recruitment.</p><p><strong>Results: </strong>Population density was associated with schizotypy (β = 0.248,95%CI = 0.122-0.375;p < 0.001). The addition of the interaction term improved the model fit (likelihood test ratio:χ<sup>2</sup> = 6.85; p = 0.009). The effect of urbanicity on schizotypy was substantially stronger in North-western Europe (β = 0.620,95%CI = 0.362-0.877;p < 0.001) compared with Southern Europe (β = 0.190,95%CI = 0.083-0.297;p = 0.001).</p><p><strong>Conclusions: </strong>The association between urbanicity and both subclinical schizotypy and clinical psychosis, rather than being universal, is context-specific. Considering that urbanization is a rapid and global process, further research is needed to disentangle the specific factors underlying this relationship.</p>","PeriodicalId":108,"journal":{"name":"Acta Psychiatrica Scandinavica","volume":" ","pages":""},"PeriodicalIF":5.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142556702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sofie Egsgaard, Mette Bliddal, Lars Christian Lund, Simone N. Vigod, Trine Munk-Olsen
Background
Parents of twins appear to be at increased risk of postpartum depression (PPD), yet little is known about the magnitude and timing of onset in the postpartum period compared to singleton parents.
Methods
We conducted a cohort study using the Danish nationwide health registers. We defined a study population of parents that is, mothers and fathers of all twin and singleton livebirths between 1997 and 2019. Postpartum depression was defined as incident depression diagnosis or a redeemed antidepressant prescription from childbirth through 365 days postpartum. We performed a parametric time-to-event analysis based on Poisson regression. The time scale was time since birth, modeled using restricted cubic splines. From this we estimated the hazard ratio (HR) representing the momentary risk, and the cumulative risk ratio (RR) over the first year postpartum, in twin compared to singleton parents.
Results
The study population was based on 27,095 twin and 1,350,046 singleton births. In adjusted analyses, the HR of twins compared to singletons was highest around 2 months postpartum (HR 1.28, 95% CI 1.10–1.49) for mothers, and around 6 months (1.20, 95% CI 1.02–1.42) for fathers. The 6 months adjusted cumulative RR of PPD in twins compared to singletons was 1.24 (95% CI 1.10–1.40) for mothers and 1.11 (95% CI 0.95–1.30) for fathers.
Conclusions
Twin mothers had increased risk of PPD compared to singleton mothers, which was driven by an immediate increase after childbirth. The risk among twin fathers was not increased immediately after childbirth, but we found slightly elevated risk around 6 months postpartum. This could suggest diverse patterns of PPD symptomatology in twin parents compared to singleton parents and between mothers and fathers. Our findings underline parents of twins as a potentially vulnerable group to PPD and emphasize the need for increased awareness of their mental health.
背景：双胞胎父母患产后抑郁症（PPD）的风险似乎更高，但与单胎父母相比，人们对双胞胎父母产后抑郁症的程度和发病时间知之甚少：我们利用丹麦全国健康登记册进行了一项队列研究。方法：我们利用丹麦全国健康登记册进行了一项队列研究。我们定义了一个父母研究人群，即 1997 年至 2019 年间所有双胞胎和单胎活产婴儿的母亲和父亲。产后抑郁症的定义是：从分娩到产后 365 天内，诊断出抑郁症或开具过抗抑郁药处方。我们在泊松回归的基础上进行了参数时间事件分析。时间尺度为出生后的时间，使用受限立方样条进行建模。由此，我们估算出了双胎父母与单胎父母相比，代表瞬间风险的危险比（HR）和产后第一年的累积风险比（RR）：研究对象包括 27,095 名双胞胎和 1,350,046 名单胎。在调整分析中，双胞胎与单胎相比，母亲在产后 2 个月左右的 HR 最高（HR 1.28，95% CI 1.10-1.49），父亲在产后 6 个月左右的 HR 最高（1.20，95% CI 1.02-1.42）。双胞胎与单胎相比，母亲患 PPD 的 6 个月调整累积 RR 为 1.24（95% CI 1.10-1.40），父亲为 1.11（95% CI 0.95-1.30）：与单胎母亲相比，双胞胎母亲罹患PPD的风险更高，这主要是由于分娩后罹患PPD的风险立即增加。双胞胎父亲的风险在产后没有立即增加，但我们发现在产后6个月左右风险略有增加。这可能表明，与单胎父母相比，双胞胎父母以及母亲和父亲之间的 PPD 症状模式各不相同。我们的研究结果强调了双胞胎父母是潜在的 PPD 易感人群，并强调需要提高对他们心理健康的认识。
{"title":"Risk and timing of postpartum depression in parents of twins compared to parents of singletons","authors":"Sofie Egsgaard, Mette Bliddal, Lars Christian Lund, Simone N. Vigod, Trine Munk-Olsen","doi":"10.1111/acps.13766","DOIUrl":"10.1111/acps.13766","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Parents of twins appear to be at increased risk of postpartum depression (PPD), yet little is known about the magnitude and timing of onset in the postpartum period compared to singleton parents.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted a cohort study using the Danish nationwide health registers. We defined a study population of parents that is, mothers and fathers of all twin and singleton livebirths between 1997 and 2019. Postpartum depression was defined as incident depression diagnosis or a redeemed antidepressant prescription from childbirth through 365 days postpartum. We performed a parametric time-to-event analysis based on Poisson regression. The time scale was time since birth, modeled using restricted cubic splines. From this we estimated the hazard ratio (HR) representing the momentary risk, and the cumulative risk ratio (RR) over the first year postpartum, in twin compared to singleton parents.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The study population was based on 27,095 twin and 1,350,046 singleton births. In adjusted analyses, the HR of twins compared to singletons was highest around 2 months postpartum (HR 1.28, 95% CI 1.10–1.49) for mothers, and around 6 months (1.20, 95% CI 1.02–1.42) for fathers. The 6 months adjusted cumulative RR of PPD in twins compared to singletons was 1.24 (95% CI 1.10–1.40) for mothers and 1.11 (95% CI 0.95–1.30) for fathers.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Twin mothers had increased risk of PPD compared to singleton mothers, which was driven by an immediate increase after childbirth. The risk among twin fathers was not increased immediately after childbirth, but we found slightly elevated risk around 6 months postpartum. This could suggest diverse patterns of PPD symptomatology in twin parents compared to singleton parents and between mothers and fathers. Our findings underline parents of twins as a potentially vulnerable group to PPD and emphasize the need for increased awareness of their mental health.</p>\u0000 </section>\u0000 </div>","PeriodicalId":108,"journal":{"name":"Acta Psychiatrica Scandinavica","volume":"151 2","pages":"163-172"},"PeriodicalIF":5.3,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11695093/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142491352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jessica M. Lipschitz, Sidian Lin, Soroush Saghafian, Chelsea K. Pike, Katherine E. Burdick
Background
Effective treatment of bipolar disorder (BD) requires prompt response to mood episodes. Preliminary studies suggest that predictions based on passive sensor data from personal digital devices can accurately detect mood episodes (e.g., between routine care appointments), but studies to date do not use methods designed for broad application. This study evaluated whether a novel, personalized machine learning approach, trained entirely on passive Fitbit data, with limited data filtering could accurately detect mood symptomatology in BD patients.
Methods
We analyzed data from 54 adults with BD, who wore Fitbits and completed bi-weekly self-report measures for 9 months. We applied machine learning (ML) models to Fitbit data aggregated over two-week observation windows to detect occurrences of depressive and (hypo)manic symptomatology, which were defined as two-week windows with scores above established clinical cutoffs for the Patient Health Questionnaire-8 (PHQ-8) and Altman Self-Rating Mania Scale (ASRM) respectively.
Results
As hypothesized, among several ML algorithms, Binary Mixed Model (BiMM) forest achieved the highest area under the receiver operating curve (ROC-AUC) in the validation process. In the testing set, the ROC-AUC was 86.0% for depression and 85.2% for (hypo)mania. Using optimized thresholds calculated with Youden's J statistic, predictive accuracy was 80.1% for depression (sensitivity of 71.2% and specificity of 85.6%) and 89.1% for (hypo)mania (sensitivity of 80.0% and specificity of 90.1%).
Conclusion
We achieved sound performance in detecting mood symptomatology in BD patients using methods designed for broad application. Findings expand upon evidence that Fitbit data can produce accurate mood symptomatology predictions. Additionally, to the best of our knowledge, this represents the first application of BiMM forest for mood symptomatology prediction. Overall, results move the field a step toward personalized algorithms suitable for the full population of patients, rather than only those with high compliance, access to specialized devices, or willingness to share invasive data.
{"title":"Digital phenotyping in bipolar disorder: Using longitudinal Fitbit data and personalized machine learning to predict mood symptomatology","authors":"Jessica M. Lipschitz, Sidian Lin, Soroush Saghafian, Chelsea K. Pike, Katherine E. Burdick","doi":"10.1111/acps.13765","DOIUrl":"10.1111/acps.13765","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Effective treatment of bipolar disorder (BD) requires prompt response to mood episodes. Preliminary studies suggest that predictions based on passive sensor data from personal digital devices can accurately detect mood episodes (e.g., between routine care appointments), but studies to date do not use methods designed for broad application. This study evaluated whether a novel, personalized machine learning approach, trained entirely on passive Fitbit data, with limited data filtering could accurately detect mood symptomatology in BD patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We analyzed data from 54 adults with BD, who wore Fitbits and completed bi-weekly self-report measures for 9 months. We applied machine learning (ML) models to Fitbit data aggregated over two-week observation windows to detect occurrences of depressive and (hypo)manic symptomatology, which were defined as two-week windows with scores above established clinical cutoffs for the Patient Health Questionnaire-8 (PHQ-8) and Altman Self-Rating Mania Scale (ASRM) respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>As hypothesized, among several ML algorithms, Binary Mixed Model (BiMM) forest achieved the highest area under the receiver operating curve (ROC-AUC) in the validation process. In the testing set, the ROC-AUC was 86.0% for depression and 85.2% for (hypo)mania. Using optimized thresholds calculated with Youden's J statistic, predictive accuracy was 80.1% for depression (sensitivity of 71.2% and specificity of 85.6%) and 89.1% for (hypo)mania (sensitivity of 80.0% and specificity of 90.1%).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>We achieved sound performance in detecting mood symptomatology in BD patients using methods designed for broad application. Findings expand upon evidence that Fitbit data can produce accurate mood symptomatology predictions. Additionally, to the best of our knowledge, this represents the first application of BiMM forest for mood symptomatology prediction. Overall, results move the field a step toward personalized algorithms suitable for the full population of patients, rather than only those with high compliance, access to specialized devices, or willingness to share invasive data.</p>\u0000 </section>\u0000 </div>","PeriodicalId":108,"journal":{"name":"Acta Psychiatrica Scandinavica","volume":"151 3","pages":"434-447"},"PeriodicalIF":5.3,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142453750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nanna M. Madsen, Marc A. Sørensen, Andreas A. Danielsen, Mikkel Højlund, Christopher Rohde, Ole Köhler-Forsberg
Background
Antipsychotics increase the risk of developing diabetes, but clinical trials are not generalizable with short follow-up, while observational studies often lack important information, particularly hemoglobin A1c (HbA1c).
Methods
We followed two Danish cohorts with schizophrenia. First, using Danish nationwide registers, we identified all individuals diagnosed with first-episode schizophrenia (FES) between 1999 and 2019 (n = 31,856). Exposure was a redeemed prescription for an antipsychotic, and the outcome was diabetes, defined via hospital-based diagnosis and redeemed prescriptions for glucose-lowering drugs. Adjusted Cox regression calculated hazard rate ratios (HRR). Second, using data from the Central Denmark Region, we identified all individuals diagnosed with FES from October 2016 to September 2022 (n = 2671). Using a within-subject design, we analyzed the change in HbA1c during the 2 years after initiation of specific antipsychotics compared to the 2 years before.
Results
In the nationwide cohort, 2543 (8.0%) individuals developed diabetes (incidence rate = 9.39 [95% CI = 9.03–9.76] per 1000 person-years). Antipsychotics, compared to periods without, were associated with an increased risk of developing diabetes (HRR = 2.04, 95% CI = 1.75–2.38). We found a dose–response association, particularly for second-generation antipsychotics, and different risk rates for specific antipsychotics. In the Central Denmark Region cohort, a total of 9.2% developed diabetes but mean HbA1c levels remained stable at 37 mmol/mol during the 2 years after initiation of antipsychotic medication.
Conclusion
This comprehensive real-world two-cohort study emphasizes that diabetes affects almost 10% of patients with FES. Antipsychotics increase this risk, while HbA1c deterioration requires longer treatment. These findings are important for clinicians and young patients with FES.
{"title":"The risk of diabetes and HbA1c deterioration during antipsychotic drug treatment: A Danish two-cohort study among patients with first-episode schizophrenia","authors":"Nanna M. Madsen, Marc A. Sørensen, Andreas A. Danielsen, Mikkel Højlund, Christopher Rohde, Ole Köhler-Forsberg","doi":"10.1111/acps.13760","DOIUrl":"10.1111/acps.13760","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Antipsychotics increase the risk of developing diabetes, but clinical trials are not generalizable with short follow-up, while observational studies often lack important information, particularly hemoglobin A1c (HbA1c).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We followed two Danish cohorts with schizophrenia. First, using Danish nationwide registers, we identified all individuals diagnosed with first-episode schizophrenia (FES) between 1999 and 2019 (<i>n</i> = 31,856). Exposure was a redeemed prescription for an antipsychotic, and the outcome was diabetes, defined via hospital-based diagnosis and redeemed prescriptions for glucose-lowering drugs. Adjusted Cox regression calculated hazard rate ratios (HRR). Second, using data from the Central Denmark Region, we identified all individuals diagnosed with FES from October 2016 to September 2022 (<i>n</i> = 2671). Using a within-subject design, we analyzed the change in HbA1c during the 2 years after initiation of specific antipsychotics compared to the 2 years before.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In the nationwide cohort, 2543 (8.0%) individuals developed diabetes (incidence rate = 9.39 [95% CI = 9.03–9.76] per 1000 person-years). Antipsychotics, compared to periods without, were associated with an increased risk of developing diabetes (HRR = 2.04, 95% CI = 1.75–2.38). We found a dose–response association, particularly for second-generation antipsychotics, and different risk rates for specific antipsychotics. In the Central Denmark Region cohort, a total of 9.2% developed diabetes but mean HbA1c levels remained stable at 37 mmol/mol during the 2 years after initiation of antipsychotic medication.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>This comprehensive real-world two-cohort study emphasizes that diabetes affects almost 10% of patients with FES. Antipsychotics increase this risk, while HbA1c deterioration requires longer treatment. These findings are important for clinicians and young patients with FES.</p>\u0000 </section>\u0000 </div>","PeriodicalId":108,"journal":{"name":"Acta Psychiatrica Scandinavica","volume":"151 1","pages":"69-80"},"PeriodicalIF":5.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/acps.13760","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142386491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There is a “traditional belief” that antidepressant side effect complaints improve with medication persistence; however, support for this theory has remained inconclusive. We aimed to examine if side effect complaints improved over time by modeling the relationship between side effect complaints and time at dropout for patients receiving citalopram during the first level of acute treatment in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial.
Methods
We categorized the 2833 patients into five patterns by week of dropout. We used pattern-mixture modeling to model change in side effect complaints (frequency, intensity, and burden) over the 12-week course of treatment, while accounting for attrition and depressive severity. Using post-hoc linear contrasts, we compared the attrition patterns with the completers' pattern for severity of side effect complaints at each respective last visit prior to dropout as well as averaged side effect complaints across the duration of treatment. We also reported frequencies and tolerability of side effects for nine organ/function systems over the course of treatment.
Results
Patients who dropped out early exhibited worsening side effect burden and patients who dropped out later showed improvements in side effect frequency and intensity. Treatment completers improved in all side effect complaints over the course of treatment. Early attrition patterns had more severe side effect complaints for both tests of post-hoc linear contrasts than later attrition patterns and completers.
Conclusions
Side effect complaints from antidepressant treatment improve over time, but only for some types of patients. As a precaution for early dropout, clinicians should monitor patients who exhibit worsening and more severe side effect complaints—especially in the first 6 weeks of antidepressant treatment. In addition, clinicians may want to consider changing the type of treatment early on for these patients, rather than encouraging them to persist with their current medication.
{"title":"Not all types of depressed patients who persist with their antidepressant treatment improve in side effect complaints: A comparison of treatment completers and dropouts in the STAR*D trial","authors":"Thomas T. Kim, Colin Xu","doi":"10.1111/acps.13764","DOIUrl":"10.1111/acps.13764","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>There is a “traditional belief” that antidepressant side effect complaints improve with medication persistence; however, support for this theory has remained inconclusive. We aimed to examine if side effect complaints improved over time by modeling the relationship between side effect complaints and time at dropout for patients receiving citalopram during the first level of acute treatment in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We categorized the 2833 patients into five patterns by week of dropout. We used pattern-mixture modeling to model change in side effect complaints (frequency, intensity, and burden) over the 12-week course of treatment, while accounting for attrition and depressive severity. Using post-hoc linear contrasts, we compared the attrition patterns with the completers' pattern for severity of side effect complaints at each respective last visit prior to dropout as well as averaged side effect complaints across the duration of treatment. We also reported frequencies and tolerability of side effects for nine organ/function systems over the course of treatment.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Patients who dropped out early exhibited worsening side effect burden and patients who dropped out later showed improvements in side effect frequency and intensity. Treatment completers improved in all side effect complaints over the course of treatment. Early attrition patterns had more severe side effect complaints for both tests of post-hoc linear contrasts than later attrition patterns and completers.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Side effect complaints from antidepressant treatment improve over time, but only for some types of patients. As a precaution for early dropout, clinicians should monitor patients who exhibit worsening and more severe side effect complaints—especially in the first 6 weeks of antidepressant treatment. In addition, clinicians may want to consider changing the type of treatment early on for these patients, rather than encouraging them to persist with their current medication.</p>\u0000 </section>\u0000 </div>","PeriodicalId":108,"journal":{"name":"Acta Psychiatrica Scandinavica","volume":"151 2","pages":"152-162"},"PeriodicalIF":5.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142370306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jonne Lintunen, Aleksi Hamina, Markku Lähteenvuo, Tapio Paljärvi, Antti Tanskanen, Jari Tiihonen, Heidi Taipale
Background
Finding effective treatment regimens for bipolar disorder is challenging, as many patients suffer from significant symptoms despite treatment. This study investigated the risk of relapse (psychiatric hospitalization) and treatment safety (non-psychiatric hospitalization) associated with different doses of antipsychotics and mood stabilizers in persons with bipolar disorder.
Methods
Individuals aged 15–65 with bipolar disorder were identified from Finnish national health registers in 1996–2018. Studied antipsychotics included olanzapine, risperidone, quetiapine, aripiprazole; mood stabilizers lithium, valproic acid, lamotrigine, and carbamazepine. Medication use was divided into three time-varying dose categories: low, standard, and high. The studied outcomes were risk of psychiatric hospitalization (relapse) and the risk of non-psychiatric hospitalization (treatment safety). Stratified Cox regression in within-individual design was used.
Results
The cohort included 60,045 individuals (mean age 41.7 years, SD 15.8; 56.4% female). Mean follow-up was 8.3 years (SD 5.8). Of antipsychotics, olanzapine and aripiprazole were associated with a decreased risk of relapse in low and standard doses, and risperidone in low dose. The lowest adjusted hazard ratio (aHR) was observed for standard dose aripiprazole (aHR 0.68, 95% CI 0.57–0.82). Quetiapine was not associated with a decreased risk of relapse at any dose. Mood stabilizers were associated with a decreased risk of relapse in low and standard doses; lowest aHR was observed for standard dose lithium (aHR 0.61, 95% CI 0.56–0.65). Apart from lithium, high doses of antipsychotics and mood stabilizers were associated with an increased risk of non-psychiatric hospitalization. Lithium was associated with a decreased risk of non-psychiatric hospitalization in low (aHR 0.88, 95% CI 0.84–0.93) and standard doses (aHR 0.81, 95% CI 0.74–0.88).
Conclusions
Standard doses of lithium and aripiprazole were associated with the lowest risk of relapse, and standard dose of lithium with the lowest risk of non-psychiatric hospitalization. Quetiapine was not associated with decreased risk of relapse at any dose.
背景：寻找双相情感障碍的有效治疗方案具有挑战性，因为许多患者尽管接受了治疗，但仍有明显的症状。本研究调查了与双相情感障碍患者不同剂量的抗精神病药物和情绪稳定剂相关的复发风险（精神病住院）和治疗安全性（非精神病住院）：方法：从1996年至2018年芬兰全国健康登记册中识别出15至65岁的躁郁症患者。研究的抗精神病药物包括奥氮平、利培酮、喹硫平、阿立哌唑；情绪稳定剂包括锂、丙戊酸、拉莫三嗪和卡马西平。药物使用分为三个随时间变化的剂量类别：低剂量、标准剂量和高剂量。研究结果包括精神病住院风险（复发）和非精神病住院风险（治疗安全性）。研究采用了个体内部设计的分层考克斯回归法：队列中包括 60,045 人（平均年龄 41.7 岁，SD 15.8；56.4% 为女性）。平均随访时间为 8.3 年（SD 5.8）。在抗精神病药物中，低剂量和标准剂量的奥氮平和阿立哌唑与降低复发风险有关，低剂量的利培酮与降低复发风险有关。标准剂量阿立哌唑的调整后危险比（aHR）最低（aHR 0.68，95% CI 0.57-0.82）。无论采用何种剂量，喹硫平都不会降低复发风险。低剂量和标准剂量的情绪稳定剂与复发风险降低有关；标准剂量锂的aHR最低（aHR 0.61，95% CI 0.56-0.65）。除了锂以外，高剂量的抗精神病药物和情绪稳定剂与非精神病住院风险的增加有关。低剂量（aHR 0.88，95% CI 0.84-0.93）和标准剂量（aHR 0.81，95% CI 0.74-0.88）的锂与非精神病住院风险的降低有关：结论：标准剂量的锂和阿立哌唑与最低的复发风险相关，标准剂量的锂与最低的非精神病住院风险相关。任何剂量的喹硫平都不会降低复发风险。
{"title":"Dosing levels of antipsychotics and mood stabilizers in bipolar disorder: A Nationwide cohort study on relapse risk and treatment safety","authors":"Jonne Lintunen, Aleksi Hamina, Markku Lähteenvuo, Tapio Paljärvi, Antti Tanskanen, Jari Tiihonen, Heidi Taipale","doi":"10.1111/acps.13762","DOIUrl":"10.1111/acps.13762","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Finding effective treatment regimens for bipolar disorder is challenging, as many patients suffer from significant symptoms despite treatment. This study investigated the risk of relapse (psychiatric hospitalization) and treatment safety (non-psychiatric hospitalization) associated with different doses of antipsychotics and mood stabilizers in persons with bipolar disorder.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Individuals aged 15–65 with bipolar disorder were identified from Finnish national health registers in 1996–2018. Studied antipsychotics included olanzapine, risperidone, quetiapine, aripiprazole; mood stabilizers lithium, valproic acid, lamotrigine, and carbamazepine. Medication use was divided into three time-varying dose categories: low, standard, and high. The studied outcomes were risk of psychiatric hospitalization (relapse) and the risk of non-psychiatric hospitalization (treatment safety). Stratified Cox regression in within-individual design was used.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The cohort included 60,045 individuals (mean age 41.7 years, SD 15.8; 56.4% female). Mean follow-up was 8.3 years (SD 5.8). Of antipsychotics, olanzapine and aripiprazole were associated with a decreased risk of relapse in low and standard doses, and risperidone in low dose. The lowest adjusted hazard ratio (aHR) was observed for standard dose aripiprazole (aHR 0.68, 95% CI 0.57–0.82). Quetiapine was not associated with a decreased risk of relapse at any dose. Mood stabilizers were associated with a decreased risk of relapse in low and standard doses; lowest aHR was observed for standard dose lithium (aHR 0.61, 95% CI 0.56–0.65). Apart from lithium, high doses of antipsychotics and mood stabilizers were associated with an increased risk of non-psychiatric hospitalization. Lithium was associated with a decreased risk of non-psychiatric hospitalization in low (aHR 0.88, 95% CI 0.84–0.93) and standard doses (aHR 0.81, 95% CI 0.74–0.88).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Standard doses of lithium and aripiprazole were associated with the lowest risk of relapse, and standard dose of lithium with the lowest risk of non-psychiatric hospitalization. Quetiapine was not associated with decreased risk of relapse at any dose.</p>\u0000 </section>\u0000 </div>","PeriodicalId":108,"journal":{"name":"Acta Psychiatrica Scandinavica","volume":"151 1","pages":"81-91"},"PeriodicalIF":5.3,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/acps.13762","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142360803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M Trott, S Suetani, U Arnautovska, S Kisely, M Kar Ray, T Theodoros, V Le, S Leske, M Lu, R Soole, N Warren, D Siskind
Introduction: People with severe mental illness (SMI) have a higher risk of suicide compared with the general population. However, variations in suicide methods between people with different SMIs have not been examined. The aim of this pre-registered (PROSPERO CRD42022351748) systematic review was to pool the odds of people with SMI who die by suicide versus those with no SMI, stratified by suicide method.
Methods: Searches were conducted on December 11, 2023 across PubMed, PsycInfo, CINAHL, and Embase. Eligible studies were those that reported suicide deaths stratified by SMI and suicide methods. Studies were pooled in a random-effects meta-analysis, and risk of bias was measured by the Joanna Briggs Institute checklist.
Results: After screening, 12 studies were eligible (n = 380,523). Compared with those with no SMI, people with schizophrenia had 3.38× higher odds of jumping from heights (95% CI: 2.08-5.50), 1.93× higher odds of drowning (95% CI: 1.50-2.48). People with bipolar disorder also had 3.2× higher odds of jumping from heights (95% CI: 2.70-3.78). Finally, people with major depression had 3.11× higher odds of drug overdose (95% CI: 1.53-6.31), 2.11× higher odds of jumping from heights (95% CI: 1.93-2.31), and 2.33× lower odds of dying by firearms (OR = 0.43, 95% CI: 0.33-0.56). No studies were classified as high risk of bias, and no outcomes had high levels of imprecision or indirectness.
Conclusion: These findings could inform lethal means counselling practices in this population. Additionally individual, clinical, community and public health interventions for people with SMI should prioritise, where feasible, means restriction including access to heights or drugs to overdose.
{"title":"Suicide methods and severe mental illness: A systematic review and meta-analysis.","authors":"M Trott, S Suetani, U Arnautovska, S Kisely, M Kar Ray, T Theodoros, V Le, S Leske, M Lu, R Soole, N Warren, D Siskind","doi":"10.1111/acps.13759","DOIUrl":"https://doi.org/10.1111/acps.13759","url":null,"abstract":"<p><strong>Introduction: </strong>People with severe mental illness (SMI) have a higher risk of suicide compared with the general population. However, variations in suicide methods between people with different SMIs have not been examined. The aim of this pre-registered (PROSPERO CRD42022351748) systematic review was to pool the odds of people with SMI who die by suicide versus those with no SMI, stratified by suicide method.</p><p><strong>Methods: </strong>Searches were conducted on December 11, 2023 across PubMed, PsycInfo, CINAHL, and Embase. Eligible studies were those that reported suicide deaths stratified by SMI and suicide methods. Studies were pooled in a random-effects meta-analysis, and risk of bias was measured by the Joanna Briggs Institute checklist.</p><p><strong>Results: </strong>After screening, 12 studies were eligible (n = 380,523). Compared with those with no SMI, people with schizophrenia had 3.38× higher odds of jumping from heights (95% CI: 2.08-5.50), 1.93× higher odds of drowning (95% CI: 1.50-2.48). People with bipolar disorder also had 3.2× higher odds of jumping from heights (95% CI: 2.70-3.78). Finally, people with major depression had 3.11× higher odds of drug overdose (95% CI: 1.53-6.31), 2.11× higher odds of jumping from heights (95% CI: 1.93-2.31), and 2.33× lower odds of dying by firearms (OR = 0.43, 95% CI: 0.33-0.56). No studies were classified as high risk of bias, and no outcomes had high levels of imprecision or indirectness.</p><p><strong>Conclusion: </strong>These findings could inform lethal means counselling practices in this population. Additionally individual, clinical, community and public health interventions for people with SMI should prioritise, where feasible, means restriction including access to heights or drugs to overdose.</p>","PeriodicalId":108,"journal":{"name":"Acta Psychiatrica Scandinavica","volume":" ","pages":""},"PeriodicalIF":5.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142337541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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