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神经重症监护中的风险调整(RAIN)——前瞻性验证用于评估神经重症监护最佳位置和比较成本的成人急性创伤性脑损伤风险预测模型:一项队列研究。

Risk Adjustment In Neurocritical care (RAIN)--prospective validation of risk prediction models for adult patients with acute traumatic brain injury to use to evaluate the optimum location and comparative costs of neurocritical care: a cohort study.

机构信息

Intensive Care National Audit and Research Centre, London, UK.

出版信息

Health Technol Assess. 2013 Jun;17(23):vii-viii, 1-350. doi: 10.3310/hta17230.

Abstract

OBJECTIVES

To validate risk prediction models for acute traumatic brain injury (TBI) and to use the best model to evaluate the optimum location and comparative costs of neurocritical care in the NHS.

DESIGN

Cohort study.

SETTING

Sixty-seven adult critical care units.

PARTICIPANTS

Adult patients admitted to critical care following actual/suspected TBI with a Glasgow Coma Scale (GCS) score of < 15.

INTERVENTIONS

Critical care delivered in a dedicated neurocritical care unit, a combined neuro/general critical care unit within a neuroscience centre or a general critical care unit outside a neuroscience centre.

MAIN OUTCOME MEASURES

Mortality, Glasgow Outcome Scale - Extended (GOSE) questionnaire and European Quality of Life-5 Dimensions, 3-level version (EQ-5D-3L) questionnaire at 6 months following TBI.

RESULTS

The final Risk Adjustment In Neurocritical care (RAIN) study data set contained 3626 admissions. After exclusions, 3210 patients with acute TBI were included. Overall follow-up rate at 6 months was 81%. Of 3210 patients, 101 (3.1%) had no GCS score recorded and 134 (4.2%) had a last pre-sedation GCS score of 15, resulting in 2975 patients for analysis. The most common causes of TBI were road traffic accidents (RTAs) (33%), falls (47%) and assault (12%). Patients were predominantly young (mean age 45 years overall) and male (76% overall). Six-month mortality was 22% for RTAs, 32% for falls and 17% for assault. Of survivors at 6 months with a known GOSE category, 44% had severe disability, 30% moderate disability and 26% made a good recovery. Overall, 61% of patients with known outcome had an unfavourable outcome (death or severe disability) at 6 months. Between 35% and 70% of survivors reported problems across the five domains of the EQ-5D-3L. Of the 10 risk models selected for validation, the best discrimination overall was from the International Mission for Prognosis and Analysis of Clinical Trials in TBI Lab model (IMPACT) (c-index 0.779 for mortality, 0.713 for unfavourable outcome). The model was well calibrated for 6-month mortality but substantially underpredicted the risk of unfavourable outcome at 6 months. Baseline patient characteristics were similar between dedicated neurocritical care units and combined neuro/general critical care units. In lifetime cost-effectiveness analysis, dedicated neurocritical care units had higher mean lifetime quality-adjusted life-years (QALYs) at small additional mean costs with an incremental cost-effectiveness ratio (ICER) of £14,000 per QALY and incremental net monetary benefit (INB) of £17,000. The cost-effectiveness acceptability curve suggested that the probability that dedicated compared with combined neurocritical care units are cost-effective is around 60%. There were substantial differences in case mix between the 'early' (within 18 hours of presentation) and 'no or late' (after 24 hours) transfer groups. After adjustment, the 'early' transfer group reported higher lifetime QALYs at an additional cost with an ICER of £11,000 and INB of £17,000.

CONCLUSIONS

The risk models demonstrated sufficient statistical performance to support their use in research but fell below the level required to guide individual patient decision-making. The results suggest that management in a dedicated neurocritical care unit may be cost-effective compared with a combined neuro/general critical care unit (although there is considerable statistical uncertainty) and support current recommendations that all patients with severe TBI would benefit from transfer to a neurosciences centre, regardless of the need for surgery. We recommend further research to improve risk prediction models; consider alternative approaches for handling unobserved confounding; better understand long-term outcomes and alternative pathways of care; and explore equity of access to postcritical care support for patients following acute TBI.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

摘要

目的

验证急性创伤性脑损伤(TBI)的风险预测模型,并使用最佳模型来评估 NHS 中神经重症监护的最佳位置和比较成本。

设计

队列研究。

设置

67 个成人重症监护病房。

参与者

格拉斯哥昏迷量表(GCS)评分<15 的实际/疑似 TBI 后入住重症监护病房的成年患者。

干预措施

在专门的神经重症监护病房、神经/一般重症监护病房内的神经科学中心或神经科学中心外的一般重症监护病房中提供重症监护。

主要观察指标

死亡率、格拉斯哥结局量表-扩展(GOSE)问卷和欧洲生活质量-5 维度,3 级版(EQ-5D-3L)问卷在 TBI 后 6 个月的结果。

结果

最终的风险调整神经重症监护(RAIN)研究数据集包含 3626 例入院患者。排除后,共纳入 3210 例急性 TBI 患者。6 个月时的总体随访率为 81%。在 3210 例患者中,101 例(3.1%)未记录 GCS 评分,134 例(4.2%)最后一次镇静前 GCS 评分为 15,因此有 2975 例患者进行分析。TBI 最常见的原因是道路交通碰撞(RTA)(33%)、跌倒(47%)和袭击(12%)。患者主要为年轻人(平均年龄为 45 岁)和男性(总体占 76%)。6 个月时的死亡率为 RTA 为 22%,跌倒为 32%,袭击为 17%。6 个月时存活且已知 GOSE 类别的患者中,44%有严重残疾,30%有中度残疾,26%有良好的恢复。总体而言,6 个月时已知结局的患者中,61%有不良结局(死亡或严重残疾)。在已知结局的幸存者中,5 个 EQ-5D-3L 维度中有 35%至 70%的患者报告存在问题。在 10 个选定用于验证的风险模型中,总体上最佳的判别是来自国际创伤性脑损伤预后分析和临床试验实验室模型(IMPACT)(死亡率的 C 指数为 0.779,不良结局的 C 指数为 0.713)。该模型对 6 个月的死亡率预测良好,但对 6 个月的不良结局风险预测不足。专用神经重症监护病房和神经/一般重症监护病房之间的基线患者特征相似。在终生成本效益分析中,专用神经重症监护病房在小的额外平均成本下具有更高的平均终生质量调整生命年(QALY),增量成本效益比(ICER)为每 QALY 14000 英镑,增量净货币收益(INB)为 17000 英镑。成本效益可接受性曲线表明,与联合神经重症监护病房相比,专用神经重症监护病房具有成本效益的概率约为 60%。“早期”(发病后 18 小时内)和“无或晚期”(24 小时后)转移组之间的病例组合存在较大差异。调整后,“早期”转移组在额外的成本下报告了更高的终生 QALY,增量成本效益比为 11000 英镑,增量净货币收益为 17000 英镑。

结论

风险模型表现出足够的统计性能,足以支持在研究中使用,但低于指导个别患者决策所需的水平。结果表明,与神经/一般重症监护病房(尽管存在相当大的统计不确定性)相比,在专用神经重症监护病房中进行管理可能具有成本效益,并支持目前的建议,即所有严重 TBI 患者都将受益于转至神经科学中心,无论是否需要手术。我们建议进一步研究以改善风险预测模型;考虑处理未观察到的混杂因素的替代方法;更好地了解长期结果和替代治疗途径;并探索急性 TBI 后接受重症监护支持的患者的获得途径。

资金

英国国家卫生研究院卫生技术评估计划。

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