The Role of Medications in Predicting Suicide-Related Outcomes and Unintended Death in Older Veterans
药物在预测老年退伍军人自杀相关结果和意外死亡中的作用
基本信息
- 批准号:10595501
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-07-01 至 2024-03-31
- 项目状态:已结题
- 来源:
- 关键词:Accidental InjuryAccidentsAgeAntidepressive AgentsAntiepileptic AgentsAwardBenzodiazepinesCategoriesCentral Nervous SystemCessation of lifeChronicClinicalCodeComplexDataDatabasesDiagnosisDiagnosticDistressDoseDrug PrescriptionsEarly InterventionElderlyEmotionalEthnic OriginEventFirearmsGenderGoalsHomelessnessIntegrated Health Care SystemsInvestigationKnowledgeLinkMedicalMedicareMental disordersMilitary PersonnelMinorityMissionMonitorMusculoskeletalOpioidOutcomeOverdosePathway interactionsPatientsPatternPharmaceutical PreparationsPharmaceutical ServicesPharmacy facilityPolypharmacyPositioning AttributePost-Traumatic Stress DisordersPredictive ValuePrevention programPrognosisPrognostic FactorPsyche structurePsychiatric DiagnosisRaceResearchRiskRisk AssessmentRisk FactorsRisk MarkerRoleServicesSeveritiesSleep DisordersSuicideSuicide attemptSuicide preventionTraumatic Brain InjuryUnited States Centers for Medicare and Medicaid ServicesUnited States Department of Veterans AffairsUpdateVeteransVeterans Health AdministrationVietnamVulnerable Populationsabsorptionchronic painclinical carecohortcombatcomorbiditydata managementdemographicsdisabilityexperiencehealth care servicehigh riskhypnoticmilitary veteranoutcome predictionpharmacy benefitprognostic valueprospectivepsychiatric symptomrisk predictionscreeningsedativesuicidal morbiditysuicidal risktool
项目摘要
Little is known about the role of medications in predicting suicide-related outcomes and unintended death in
older Veterans. Veterans 50 years and older have the highest number of lives lost to suicide, make up the
majority (> 70%) of the Veteran population, and are highly likely to experience conditions (e.g., chronic pain,
sleep disorders, musculoskeletal) associated with commonly prescribed medications that are potential markers
for suicide risk (hereafter referred to as “high-risk” drug categories, including benzodiazepines, sedative-
hypnotics, opioids, antidepressants, and antiepileptics). The role of these medications in relationship to risk of
suicide and unintended death in older Veterans is likely complex and, yet, extremely informative. Simply
access to “high-risk” medications, similar to access to firearms, may increase risk. Moreover, medications may
be causally linked where central nervous system-acting medications increase vulnerability to risk of attempting
suicide. In addition, the type and amount of medication use can serve as a valuable marker of the presence
and severity of psychiatric symptoms and associated emotional and mental distress, in ways that diagnostic
codes alone are unable to capture. It is also likely that polypharmacy is an important indicator of a complex of
comorbidities that increases risk of suicide. All-in-all there are multiple potential pathways where medications
may be strongly associated with suicide risk in ways not fully captured by other predictors. Thus, information
on medication use could substantially enhance our ability to identify older Veterans at high risk of suicide,
above and beyond known risk factors such as the presence of psychiatric diagnoses. This could provide
extremely valuable products by giving us tools to better identify high-risk Veterans, who could then be targeted
for enhanced screening and early intervention to prevent suicide. With mounting concern regarding
misclassification of suicides as accidental deaths by drug overdose, better understanding the impact of
medications on death by unintentional injury is also important to informing suicide prevention efforts.
Furthermore, examining associations by such factors as age, gender, race/ethnicity, homelessness, Vietnam
Veteran status, service connected disability, posttraumatic stress disorder, and traumatic brain injury supports
the Department of Veterans Affairs' mission to meet the needs of these vulnerable groups. To this end, the
primary goal of our study is to determine the role of medications as prognostic factors, above and beyond other
factors, in predicting risk of suicide and unintended death in older Veterans. We propose in this current
application to add new questions on medication prescribing and use to an existing CSR&D Merit Award project
(CX001119; PI: Byers), which has formed a unique cohort for late-life suicide research. This cohort includes all
Veterans (~5,000,000) who used VA health care services, were initially 50 years and older in fiscal year 2012-
2013, and followed to present. This cohort includes information on all psychiatric and medical diagnoses and
death by suicide and unintentional injury and suicide attempt. We propose linking multiple National Pharmacy
databases (i.e., VA and Medicare) to this cohort – to study medications as a prognostic factor in predicting
suicide-related outcomes and unintended death. In doing this, we will characterize the use of “high-risk”
medications and polypharmacy prior to suicide-related outcomes and unintended death among older Veterans
(Aim 1), determine whether use, and certain patterns of use, of “high-risk” medications (Aim 2) and
polypharmacy (Aim 3) provide additional prognostic value above and beyond other predictors, and assess
differences of associations by vulnerable groups (Aim 4). If this hypothesis is true that certain medications and
patterns of use can identify older Veterans at increased risk of suicide and unintended death, it has important
implications for clinical care. The use and initiation of medications could be utilized to target risk assessments
and prevention programs for older Veterans at high risk. This is something the VA is uniquely positioned to do.
关于药物在预测自杀相关结局和非预期死亡中的作用,
老退伍军人50岁及以上的退伍军人因自杀而丧生的人数最多,
大多数(> 70%)退伍军人,并且极有可能经历疾病(例如,慢性疼痛,
睡眠障碍、肌肉骨骼)与作为潜在标志物的常用处方药相关
自杀风险(以下称为“高风险”药物类别,包括苯二氮卓类、镇静剂-
催眠药、阿片类药物、抗抑郁药和抗癫痫药)。这些药物在风险关系中的作用
老年退伍军人的自杀和意外死亡可能是复杂的,然而,信息量非常大。简单
获得“高风险”药物与获得枪支类似,可能会增加风险。此外,药物可能
在中枢神经系统作用药物增加尝试的风险的脆弱性的情况下,
自杀此外,药物使用的类型和数量可以作为存在的有价值的标记
精神症状的严重程度以及相关的情绪和精神困扰,
单靠密码是无法捕捉的多药治疗也可能是一种复杂的药物治疗的重要指标。
增加自杀风险的合并症。总而言之,有多种潜在的途径,
可能与自杀风险密切相关,而其他预测因素并没有完全捕捉到这一点。因此,信息
药物使用可以大大提高我们识别自杀风险高的老年退伍军人的能力,
超出已知的风险因素,如精神病诊断的存在。这可以提供
通过为我们提供工具来更好地识别高风险退伍军人,从而成为攻击目标,从而提供极具价值的产品
加强筛选和早期干预,以防止自杀。越来越多的人担心
将自杀错误地归类为药物过量造成的意外死亡,更好地了解
关于意外伤害死亡的药物治疗对于指导自杀预防工作也很重要。
此外,通过年龄、性别、种族/民族、无家可归者、越南人等因素来研究相关性,
退伍军人身份,服务连接残疾,创伤后应激障碍和创伤性脑损伤支持
退伍军人事务部满足这些弱势群体需求的使命。为此中央
我们研究的主要目的是确定药物作为预后因素的作用,
因素,在预测老年退伍军人自杀和意外死亡的风险。我们建议在当前
申请在现有CSR&D Merit Award项目中添加有关药物处方和使用的新问题
(CX 001119; PI:Byers),它已经形成了一个独特的晚年自杀研究队列。这一群体包括所有
使用VA医疗保健服务的退伍军人(约5,000,000人)最初在2012财年年满50岁,
2013年,从现在到现在。该队列包括所有精神病和医学诊断的信息,
自杀、意外伤害和自杀未遂造成的死亡。我们建议将多个国家药房
数据库(即,VA和医疗保险),以研究药物作为预测
自杀相关的结果和意外死亡。在这样做时,我们将使用“高风险”
老年退伍军人中自杀相关结局和意外死亡之前的药物和多种药物
(Aim 1),确定是否使用和某些使用模式,“高风险”药物(目标2),
多药治疗(目标3)提供了额外的预后价值高于其他预测因素,并评估
弱势群体的协会差异(目标4)。如果这个假设是正确的,
使用模式可以识别老年退伍军人的自杀和意外死亡的风险增加,它具有重要的
对临床护理的影响。可以利用药物的使用和启动来进行针对性的风险评估
和预防计划,为老年退伍军人在高风险。这是VA唯一能够做的事情。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Amy Lynn Byers其他文献
Amy Lynn Byers的其他文献
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{{ truncateString('Amy Lynn Byers', 18)}}的其他基金
Long-term Neuropsychiatric Sequelae of SARS-CoV-2 Infection in Late Life
晚年 SARS-CoV-2 感染的长期神经精神后遗症
- 批准号:
10586560 - 财政年份:2023
- 资助金额:
-- - 项目类别:
The Role of Medications in Predicting Suicide-Related Outcomes and Unintended Death in Older Veterans
药物在预测老年退伍军人自杀相关结果和意外死亡中的作用
- 批准号:
10041713 - 财政年份:2015
- 资助金额:
-- - 项目类别:
The Role of Medications in Predicting Suicide-Related Outcomes and Unintended Death in Older Veterans
药物在预测老年退伍军人自杀相关结果和意外死亡中的作用
- 批准号:
10295160 - 财政年份:2015
- 资助金额:
-- - 项目类别:
Epidemiology of Suicidal Behavior in Racially/Ethnically Diverse Older Americans
不同种族/民族的美国老年人自杀行为的流行病学
- 批准号:
8734507 - 财政年份:2012
- 资助金额:
-- - 项目类别:
Epidemiology of Suicidal Behavior in Racially/Ethnically Diverse Older Americans
不同种族/民族的美国老年人自杀行为的流行病学
- 批准号:
8448612 - 财政年份:2012
- 资助金额:
-- - 项目类别:
Epidemiology of Suicidal Behavior in Racially/Ethnically Diverse Older Americans
不同种族/民族的美国老年人自杀行为的流行病学
- 批准号:
8281153 - 财政年份:2012
- 资助金额:
-- - 项目类别:
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