scholarly journals Fatal opioid overdoses during and shortly after hospital admissions in England: A case-crossover study

PLoS Medicine ◽  
2021 ◽  
Vol 18 (10) ◽  
pp. e1003759
Author(s):  
Dan Lewer ◽  
Brian Eastwood ◽  
Martin White ◽  
Thomas D. Brothers ◽  
Martin McCusker ◽  
...  
Keyword(s):  
Drug Use ◽  
Hospital Admission ◽  
Crossover Study ◽  
Hospital Admissions ◽  
Conditional Logistic Regression ◽  
Early Discharge ◽  
Odds Ratios ◽  
Drug Poisoning ◽  
Case Crossover ◽  
Increased Risk

Background Hospital patients who use illicit opioids such as heroin may use drugs during an admission or leave the hospital in order to use drugs. There have been reports of patients found dead from drug poisoning on the hospital premises or shortly after leaving the hospital. This study examines whether hospital admission and discharge are associated with increased risk of opioid-related death. Methods and findings We conducted a case-crossover study of opioid-related deaths in England. Our study included 13,609 deaths between January 1, 2010 and December 31, 2019 among individuals aged 18 to 64. For each death, we sampled 5 control days from the period 730 to 28 days before death. We used data from the national Hospital Episode Statistics database to determine the time proximity of deaths and control days to hospital admissions. We estimated the association between hospital admission and opioid-related death using conditional logistic regression, with a reference category of time neither admitted to the hospital nor within 14 days of discharge. A total of 236/13,609 deaths (1.7%) occurred following drug use while admitted to the hospital. The risk during hospital admissions was similar or lower than periods neither admitted to the hospital nor recently discharged, with odds ratios 1.03 (95% CI 0.87 to 1.21; p = 0.75) for the first 14 days of an admission and 0.41 (95% CI 0.30 to 0.56; p < 0.001) for days 15 onwards. 1,088/13,609 deaths (8.0%) occurred in the 14 days after discharge. The risk of opioid-related death increased in this period, with odds ratios of 4.39 (95% CI 3.75 to 5.14; p < 0.001) on days 1 to 2 after discharge and 2.09 (95% CI 1.92 to 2.28; p < 0.001) on days 3 to 14. 11,629/13,609 deaths (85.5%) did not occur close to a hospital admission, and the remaining 656/13,609 deaths (4.8%) occurred in hospital following admission due to drug poisoning. Risk was greater for patients discharged from psychiatric admissions, those who left the hospital against medical advice, and those leaving the hospital after admissions of 7 days or more. The main limitation of the method is that it does not control for time-varying health or drug use within individuals; therefore, hospital admissions coinciding with high-risk periods may in part explain the results. Conclusions Discharge from the hospital is associated with an acute increase in the risk of opioid-related death, and 1 in 14 opioid-related deaths in England happens in the 2 weeks after the hospital discharge. This supports interventions that prevent early discharge and improve linkage with community drug treatment and harm reduction services.

scholarly journals The Role of Stroke as a Trigger for Incident Venous Thromboembolism: Results from a Population-based Case-Crossover Study

TH Open ◽  
2019 ◽  
Vol 03 (01) ◽  
pp. e50-e57
Author(s):  
Vânia Morelli ◽  
Joakim Sejrup ◽  
Birgit Småbrekke ◽  
Ludvig Rinde ◽  
Gro Grimnes ◽  
...  
Keyword(s):  
Venous Thromboembolism ◽  
Acute Stroke ◽  
Crossover Study ◽  
Conditional Logistic Regression ◽  
Population Based ◽  
Red Blood Cell Transfusion ◽  
Odds Ratios ◽  
Case Crossover ◽  
Increased Risk

AbstractStroke is associated with a short-term increased risk of subsequent venous thromboembolism (VTE). It is unclear to what extent this association is mediated by stroke-related complications that are potential triggers for VTE, such as immobilization and infection. We aimed to investigate the role of acute stroke as a trigger for incident VTE while taking other concomitant VTE triggers into account. We conducted a population-based case-crossover study with 707 VTE patients. Triggers were registered during the 90 days before a VTE event (hazard period) and in four preceding 90-day control periods. Conditional logistic regression was used to estimate odds ratios with 95% confidence intervals (CIs) for VTE according to triggers. Stroke was registered in 30 of the 707 (4.2%) hazard periods and in 6 of the 2,828 (0.2%) control periods, resulting in a high risk of VTE, with odds ratios of 20.0 (95% CI: 8.3–48.1). After adjustments for immobilization and infection, odds ratios for VTE conferred by stroke were attenuated to 6.0 (95% CI: 1.6–22.1), and further to 4.0 (95% CI: 1.1–14.2) when other triggers (major surgery, red blood cell transfusion, trauma, and central venous catheter) were added to the regression model. A mediation analysis revealed that 67.8% of the total effect of stroke on VTE risk could be mediated through immobilization and infection. Analyses restricted to ischemic stroke yielded similar results. In conclusion, acute stroke was a trigger for VTE, and the association between stroke and VTE risk appeared to be largely mediated by immobilization and infection.

scholarly journals Effect of ambient fine particulates (PM2.5) on hospital admissions for respiratory and cardiovascular diseases in Wuhan, China

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Zhan Ren ◽  
Xingyuan Liu ◽  
Tianyu Liu ◽  
Dieyi Chen ◽  
Kuizhuang Jiao ◽  
...  
Keyword(s):  
Air Pollution ◽  
Hospital Admission ◽  
Hospital Admissions ◽  
Conditional Logistic Regression ◽  
Warm Season ◽  
Central China ◽  
Air Pollution Control ◽  
Short Term ◽  
Short Term Exposure ◽  
Increased Risk

Abstract Background Positive associations between ambient PM2.5 and cardiorespiratory disease have been well demonstrated during the past decade. However, few studies have examined the adverse effects of PM2.5 based on an entire population of a megalopolis. In addition, most studies in China have used averaged data, which results in variations between monitoring and personal exposure values, creating an inherent and unavoidable type of measurement error. Methods This study was conducted in Wuhan, a megacity in central China with about 10.9 million people. Daily hospital admission records, from October 2016 to December 2018, were obtained from the Wuhan Information center of Health and Family Planning, which administrates all hospitals in Wuhan. Daily air pollution concentrations and weather variables in Wuhan during the study period were collected. We developed a land use regression model (LUR) to assess individual PM2.5 exposure. Time-stratified case-crossover design and conditional logistic regression models were adopted to estimate cardiorespiratory hospitalization risks associated with short-term exposure to PM2.5. We also conducted stratification analyses by age, sex, and season. Results A total of 2,806,115 hospital admissions records were collected during the study period, from which we identified 332,090 cardiovascular disease admissions and 159,365 respiratory disease admissions. Short-term exposure to PM2.5 was associated with an increased risk of a cardiorespiratory hospital admission. A 10 μg/m3 increase in PM2.5 (lag0–2 days) was associated with an increase in hospital admissions of 1.23% (95% CI 1.01–1.45%) and 1.95% (95% CI 1.63–2.27%) for cardiovascular and respiratory diseases, respectively. The elderly were at higher PM-induced risk. The associations appeared to be more evident in the cold season than in the warm season. Conclusions This study contributes evidence of short-term effects of PM2.5 on cardiorespiratory hospital admissions, which may be helpful for air pollution control and disease prevention in Wuhan.

Proton pump inhibitor-related headaches: A nationwide population-based case-crossover study in Taiwan

Cephalalgia ◽  
2014 ◽  
Vol 35 (3) ◽  
pp. 203-210 ◽  
Author(s):  
Jen-Feng Liang ◽  
Yung-Tai Chen ◽  
Jong-Ling Fuh ◽  
Szu-Yuan Li ◽  
Tzeng-Ji Chen ◽  
...  
Keyword(s):  
Proton Pump Inhibitor ◽  
Crossover Study ◽  
Proton Pump ◽  
Conditional Logistic Regression ◽  
Population Based ◽  
Female Patients ◽  
Case Crossover ◽  
Increased Risk ◽  
Tension Type Headaches ◽  
Acute Headache

Background Headaches resulting from proton pump inhibitor (PPI) use could cause discontinuation of PPI in as many as 40% of patients who experience such headaches. Previous studies focusing on acute headache risk from PPI use are rare and limited to clinical trials of a single PPI. Objectives To investigate the association between PPI use and headache with a nationwide population-based case-crossover study. Methods Records containing the first diagnosis of any headache, including migraine and tension-type headaches, were retrieved from Taiwan National Health Insurance Database (1998–2010). We compared the rates of PPI use for cases and controls during time windows of 7, 14, and 28 days. The adjusted self-matched odds ratios (ORs) and 95% confidence intervals (CIs) from a conditional logistic regression model were used to determine the association between PPI use and headache. Results Overall, 314,210 patients with an initial diagnosis of any headache during the study period were enrolled. The adjusted ORs for headache risk after PPI exposure were calculated for three time periods (within 7 days = 1.41, p = 0.002, 95% CI 1.14–1.74; within 14 days = 1.36, p < 0.001, 95% CI 1.16–1.59; within 28 days = 1.20, p = 0.002, 95% CI 1.07–1.35). Subgroup analyses showed female patients had an increased risk of headache. Among PPIs, lansoprazole and esomeprazole had the highest risks of headache incidence, which were similar to that of nitrates. Conclusion PPI usage is associated with an increased risk for acute headache. Female patients and use of lansoprazole or esomeprazole present the greatest risks of headache.

scholarly journals Effect of Ambient Fine Particulate (PM2.5) on Hospital Admissions for Respiratory and Cardiovascular Diseases in Wuhan, China

2020 ◽  
Author(s):  
Zhan Ren ◽  
Xingyuan Liu ◽  
Tianyu Liu ◽  
Dieyi Chen ◽  
Kuizhuang Jiao ◽  
...  
Keyword(s):  
Air Pollution ◽  
Cardiovascular Diseases ◽  
Hospital Admission ◽  
Respiratory Diseases ◽  
Hospital Admissions ◽  
Conditional Logistic Regression ◽  
Central China ◽  
Air Pollution Control ◽  
Short Term ◽  
Increased Risk

Abstract Background: The positive associations between ambient PM2.5 and cardiorespiratory disease have been well demonstrated during the past decade. However, few studies have examined the adverse effects of PM2.5 based on an entire population of megalopolis. In addition, due to the lack of accurate methods of assessing individual PM2.5 exposure, further studies are still necessary to be launched in China.Methods: The study was conducted in Wuhan, a megacity in central China with about 10.8929 million population. Daily hospital admission records, from October 2016 to December 2018, were obtained from Wuhan Information center of Health and Family Planning, which administrates all the hospitals in Wuhan. The daily air pollution concentration and weather variable in Wuhan during the study period were collected. We developed Land use regression model (LUR) to assess individual PM2.5 exposure. Time-stratified case-crossover design and conditional logistic regression models were adopted to estimate cardiorespiratory hospitalization risks associated with short-term exposures to PM2.5. We also conducted stratification analyses by age, sex and season.Results: A total of 2,806,115 hospital admissions records were collected during the study period, from which we identified 332,090 for total cardiovascular diseases and 159,365 for total respiratory diseases. We found short-term PM2.5 exposure was associated with increased risk of cardiorespiratory hospital admission in Wuhan. Per 10 μg/m3 increase of PM2.5 at lag0~2 days was associated with 1.23% (95%CI: 1.01–1.45%) and 1.95% (95%CI: 1.63–2.27%) elevated risk of admission from cardiovascular and respiratory diseases respectively. The elderly were at higher PM-induced risks. The associations appeared to be more evident in the cold season than in the warm season.Conclusions: This study contributed evidence to support the short-term effects of PM2.5 on cardiorespiratory hospital admission, which may be helpful for air pollution control and disease prevention in Wuhan.

scholarly journals Increased Risk of Hospital Admission for Asthma in Children From Short-Term Exposure to Air Pollution: Case-Crossover Evidence From Northern China

2021 ◽  
Vol 9 ◽  
Author(s):  
Yakun Zhao ◽  
Dehui Kong ◽  
Jia Fu ◽  
Yongqiao Zhang ◽  
Yuxiong Chen ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Hospital Admission ◽  
Hospital Admissions ◽  
Ambient Air ◽  
Short Term ◽  
High Quality ◽  
Case Crossover ◽  
Increased Risk ◽  
Asthma In Children

Background: Previous studies suggested that exposure to air pollution could increase risk of asthma attacks in children. The aim of this study is to investigate the short-term effects of exposure to ambient air pollution on asthma hospital admissions in children in Beijing, a city with serious air pollution and high-quality medical care at the same time.Methods: We collected hospital admission data of asthma patients aged ≤ 18 years old from 56 hospitals from 2013 to 2016 in Beijing, China. Time-stratified case-crossover design and conditional Poisson regression were applied to explore the association between risk of asthma admission in children and the daily concentration of six air pollutants [particulate matter ≤ 2.5 μm (PM2.5), particulate matter ≤ 10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3)], adjusting for meteorological factors and other pollutants. Additionally, stratified analyses were performed by age, gender, and season.Results: In the single-pollutant models, higher levels of PM2.5, SO2, and NO2 were significantly associated with increased risk of hospital admission for asthma in children. The strongest effect was observed in NO2 at lag06 (RR = 1.25, 95%CI: 1.06-1.48), followed by SO2 at lag05 (RR = 1.17, 95%CI: 1.05–1.31). The robustness of effects of SO2 and NO2 were shown in two-pollutant models. Stratified analyses further indicated that pre-school children (aged ≤ 6 years) were more susceptible to SO2. The effects of SO2 were stronger in the cold season, while the effects of NO2 were stronger in the warm season. No significant sex-specific differences were observed.Conclusions: These results suggested that high levels of air pollution had an adverse effect on childhood asthma, even in a region with high-quality healthcare. Therefore, it will be significant to decrease hospital admissions for asthma in children by controlling air pollution emission and avoiding exposure to air pollution.

scholarly journals Use of multiple antidiabetic medications in patients with diabetes and its association with hypoglycaemic events: a case-crossover study in Jordan

BMJ Open ◽  
2018 ◽  
Vol 8 (11) ◽  
pp. e024909 ◽  
Author(s):  
Abdallah Y Naser ◽  
Ian Chi Kei Wong ◽  
Cate Whittlesea ◽  
Maedeh Y Beykloo ◽  
Kenneth K C Man ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Crossover Study ◽  
Conditional Logistic Regression ◽  
Secondary Analysis ◽  
Blood Glucose Measurement ◽  
Glucose Measurement ◽  
Case Crossover ◽  
Increased Risk ◽  
Patients With Diabetes ◽  
Control Window

ObjectiveTo assess whether the use of multiple antidiabetic medications is associated with an increased risk of hypoglycaemia in patients with type 2 diabetes mellitus.DesignA case-crossover study.SettingCases were enrolled from the National Center for Diabetes, Endocrinology and Genetics in Amman, Jordan.ParticipantsPatients were those with diabetes mellitus and reported incident of a hypoglycaemic event in their medical records during the period January 2007 to July 2017. Patients with multiple antidiabetic medications were those with at least two antidiabetic medications.Primary outcomeHistory of antidiabetic medication use was extracted from the pharmacy records. The use of multiple antidiabetic medications during the risk window (before hypoglycaemia) was compared with a control window(s) (earlier time) of the same length after a washout period. Conditional logistic regression was applied to evaluate the OR of hypoglycaemia between the treatment groups. A secondary analysis was performed in patients with a blood glucose measurement of ≤70 mg/dL.Results182 patients (106 females, 58.2%) were included in the study with an average age of 59.9 years (SD=9.9). The patients’ average body mass index was 31.7 kg/m2 (SD=6.2). Compared with monotherapy, the OR of hypoglycaemic events for patients with multiple antidiabetic medications was 5.00 (95% CI 1.10 to 22.82). The OR was 6.00 (95% CI 0.72 to 49.84) for the secondary analysis patient group (n=94). Ten-fold increased risk was found in patients (n=155) with insulin and sulfonylurea-based combination therapy (OR 10.00;95% CI 1.28 to 78.12).ConclusionThis study shows that the use of multiple antidiabetic medications appears to increase the risk of hypoglycaemic events. Patients and healthcare professionals should be extra vigilant when patients are on multiple antidiabetic medications therapy, especially the combination of sulfonylurea and insulin.

scholarly journals Impact of Heat Waves on Hospitalisation and Mortality in Nursing Homes: A Case-Crossover Study

2021 ◽  
Vol 18 (20) ◽  
pp. 10697
Author(s):  
Ine Van den Wyngaert ◽  
Katrien De Troeyer ◽  
Bert Vaes ◽  
Mahmoud Alsaiqali ◽  
Bert Van Schaeybroeck ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Nursing Homes ◽  
Confidence Interval ◽  
Crossover Study ◽  
Heat Waves ◽  
Conditional Logistic Regression ◽  
Odds Ratios ◽  
Mortality And Morbidity ◽  
Case Crossover ◽  
The Impact

Climate change leads to more days with extremely hot temperatures. Previous analyses of heat waves have documented a short-term rise in mortality. The results on the relationship between high temperatures and hospitalisations, especially in vulnerable patients admitted to nursing homes, are inconsistent. The objective of this research was to examine the discrepancy between heat-related mortality and morbidity in nursing homes. A time-stratified case-crossover study about the impact of heat waves on mortality and hospitalisations between 1 January 2013 and 31 December 2017 was conducted in 10 nursing homes over 5 years in Flanders, Belgium. In this study, the events were deaths and hospitalisations. We selected our control days during the same month as the events and matched them by day of the week. Heat waves were the exposure. Conditional logistic regression models were applied. The associations were reported as odds ratios at lag 0, 1, 2, and 3 and their 95% confidence intervals. In the investigated time period, 3048 hospitalisations took place and 1888 residents died. The conditional logistic regression showed that odds ratios of mortality and hospitalisations during heat waves were 1.61 (95% confidence interval 1.10–2.37) and 0.96 (95% confidence interval 0.67–1.36), respectively, at lag 0. Therefore, the increase in mortality during heat waves was statistically significant, but no significant changes in hospitalisations were obtained. Our result suggests that heat waves have an adverse effect on mortality in Flemish nursing homes but have no significant effect on the number of hospitalisations.

scholarly journals A novel weighting method to remove bias from within-subject exposure dependency in case-crossover studies

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kiyoshi Kubota ◽  
Thu-Lan Kelly ◽  
Tsugumichi Sato ◽  
Nicole Pratt ◽  
Elizabeth Roughead ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Crossover Study ◽  
Odds Ratio ◽  
Time Trends ◽  
Rate Ratio ◽  
Conditional Logistic Regression ◽  
Time Varying ◽  
Weighting Method ◽  
Case Crossover ◽  
Crossover Studies

Abstract Background Case-crossover studies have been widely used in various fields including pharmacoepidemiology. Vines and Farrington indicated in 2001 that when within-subject exposure dependency exists, conditional logistic regression can be biased. However, this bias has not been well studied. Methods We have extended findings by Vines and Farrington to develop a weighting method for the case-crossover study which removes bias from within-subject exposure dependency. Our method calculates the exposure probability at the case period in the case-crossover study which is used to weight the likelihood formulae presented by Greenland in 1999. We simulated data for the population with a disease where most patients receive a cyclic treatment pattern with within-subject exposure dependency but no time trends while some patients stop and start treatment. Finally, the method was applied to real-world data from Japan to study the association between celecoxib and peripheral edema and to study the association between selective serotonin reuptake inhibitor (SSRI) and hip fracture in Australia. Results When the simulated rate ratio of the outcome was 4.0 in a case-crossover study with no time-varying confounder, the proposed weighting method and the Mantel-Haenszel odds ratio reproduced the true rate ratio. When a time-varying confounder existed, the Mantel-Haenszel method was biased but the weighting method was not. When more than one control period was used, standard conditional logistic regression was biased either with or without time-varying confounding and the bias increased (up to 8.7) when the study period was extended. In real-world analysis with a binary exposure variable in Japan and Australia, the point estimate of the odds ratio (around 2.5 for the association between celecoxib and peripheral edema and around 1.6 between SSRI and hip fracture) by our weighting method was equal to the Mantel-Haenszel odds ratio and stable compared with standard conditional logistic regression. Conclusion Case-crossover studies may be biased from within-subject exposure dependency, even without exposure time trends. This bias can be identified by comparing the odds ratio by the Mantel-Haenszel method and that by standard conditional logistic regression. We recommend using our proposed method which removes bias from within-subject exposure dependency and can account for time-varying confounders.

scholarly journals Ambient Air Pollution and Hospital Admissions for Peptic Ulcers in Taipei: A Time-Stratified Case-Crossover Study

2019 ◽  
Vol 16 (11) ◽  
pp. 1916 ◽  
Author(s):  
Shang-Shyue Tsai ◽  
Hui-Fen Chiu ◽  
Chun-Yuh Yang
Keyword(s):  
Air Pollution ◽  
Peptic Ulcer ◽  
Crossover Study ◽  
Air Pollutants ◽  
Hospital Admissions ◽  
Ambient Air ◽  
Air Pollutant ◽  
Ambient Air Pollution ◽  
Research Database ◽  
Case Crossover

Very few studies have been performed to determine whether there is a relationship between air pollution and increases in hospitalizations for peptic ulcer, and for those that have occurred, their results may not be completely relevant to Taiwan, where the mixture of ambient air pollutants differ. We performed a time-stratified case-crossover study to investigate the possible association between air pollutant levels and hospital admissions for peptic ulcer in Taipei, Taiwan. To do this, we collected air pollution data from Taiwan's Environmental Protection Agency and hospital admissions for peptic ulcer data for the years 2009–2013 from Taiwan's National Health Insurance's research database. We used conditional logistic regression to analyze the possible association between the two, taking temperature and relative humidity into account. Risk was expressed as odds ratios and significance was expressed with 95% confidence intervals. In our single pollutant model, peptic ulcer admissions were significantly associated with all pollutants (PM10, PM2.5, SO2, NO2, CO, and O3) on warm days (>23 °C). On cool days (<23 °C), peptic ulcer admissions were significantly associated with PM10, NO2, and O3. In our two-pollutant models, peptic ulcer admissions were significantly associated NO2 and O3 when combined with each of the other pollutants on warm days, and with PM10, NO2, and O3 on cool days. It was concluded that the likelihood of peptic ulcer hospitalizations in Taipei rose significantly with increases in air pollutants during the study period.

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