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临床试验/NCT04474444
NCT04474444已完成不适用

Ambulance Calls for Substance Use and Alcohol in a Pandemic (ASAP): Exploring Attendance at Incidents Involving Substance and/or Alcohol Use During COVID-19 Pandemic

University of Lincoln1 个研究点 分布在 1 个国家目标入组 55,000 人开始时间: 2019年3月23日最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
入组人数
55,000
试验地点
1
主要终点
Attendances for alcohol and drug use

研究概览

简要总结

The Primary objective is to explore ambulance service attendance at incidents involving alcohol and/or substance use over the period of the pandemic lockdown, and the following months. This will be to determine prevalence and explore factors such as patient gender, age, ethnicity or location. Analysis will examine the calls over the course of the year prior to the lockdown, and then compare this to the period of lockdown and following months.

详细描述

The Primary objective is to explore ambulance service attendance at incidents involving alcohol and/or substance use over the period of the pandemic lockdown, and the following months. This will be to determine prevalence and explore factors such as patient gender, age, ethnicity or location. Analysis will examine the calls over the course of the year prior to the lockdown, and then compare this to the period of lockdown and following months.

A time series analysis will be conducted to examine the calls over the course of the year prior to the lockdown, and then compare this to the period of lockdown and following months. This will use the 'Interrupted Time Series' (ITS) approach. To explore this regression models will be built that examine the causal models for attendance prior to the pandemic and compared to the lockdown time frame.

A multivariable regression model will be built. Initially a Directed Acyclic Graph (DAG) will allow the identification of confounders and exposures relevant to the model. A logistic regression model will be used to calculate the relative risk of call during lockdown compared to the data prior to lockdown. The model will be fit using p<0.05 as the definition of statistical significance.

Descriptive statistics, trend analysis and predictive analysis will be conducted on the data set to determine trends across time, factors that predict patients requiring ambulance attendance, and factors that predict treatment outcomes. Missing data will be examined for systematic bias, and where found to be missing at random will be excluded from analysis. Where not missing at random, sensitivity analysis will be conducted.

Analysis will examine covariates. Age will be defined as single year continuous variable and examined in categories such as 5-year age groups. Ethnicity will be categorised as groups, such as black, Asian, other minority and mixed ethnic groups will be explored. Census data such as the deprivation, rurality, income, employment, disability and education will look at the decile as defined.

研究设计

研究类型
Observational
观察模型
Case Only
时间视角
Retrospective

入排标准

性别
All
接受健康志愿者

入选标准

  • Patient of any age
  • Patient requested ambulance attendance between 23rd March 2019 and 22nd March 2021
  • The patient record is held by East Midlands Ambulance Service
  • Patient records that have recorded a clinical impression related to alcohol and substance use will be included in the data set alongside a word search in the free text response box for the following words/phrases: narcotic, spice, mamba, alcohol, substance use, drug use, illicit drug, overdose, intoxication, intoxicated, drunk, high.

排除标准

  • The patient record was outside of the indicated date range.
  • The patient record is not accessible via EMAS

结局指标

主要结局

Attendances for alcohol and drug use

时间窗: Full data set 23/03/2019 compared to 22/03/2021 to look at interruption (lockdown) in the time series.

Counts of attendances for alcohol and drug use by the East Midland's Ambulance Service over the time period. This will be a number per day of people attended.

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Sponsor

研究点 (1)

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