Clinical Epidemiology最新文献

Purpose: Measures of disease burden using hospital administrative data are susceptible to over-inflation if the patient is transferred during their episode of care. We aimed to identify and compare measures of coronary heart disease (CHD) and myocardial infarction (MI) episodes using six algorithms that account for transfers.

Patient and methods: We used person-linked hospitalisations for CHD and MI for 2000-2016 in Western Australia based on the interval between discharge and subsequent admission (date, datetime algorithms), pathway (admission source, discharge destination) and any combination to generate machine learning models (random forest [RF], gradient boosting machine [GBM]). The date and datetime algorithms used deidentified patient identifiers to identify records belonging to the same individual. We calculated counts, age-standardised rates (ASR) and age-adjusted trends for CHD and MI for each algorithm.

Results: Counts of CHD increased from 11,733 in 2000 to 13,274 in 2016, while MI increased from 2605 to 4480 using the date algorithm. Correspondingly ASR for CHD decreased from 2086.2 to 1463.1 while MI increased from 468.2 to 498.1 per 100,000 person-years. ASR for CHD and MI for datetime algorithm were consistently 1-2% higher than the date algorithm. Differences in ASR of CHD and MI counts increased over time with the admission source, RF and GBM algorithms relative to the date algorithm. Age-adjusted trends in CHD and MI episode rates using RF and GBM differed significantly from all other algorithms. Only 86.7% and 87.6% of MI episodes identified by the date algorithm were identified by the admission source and discharge destination algorithms, respectively.

Conclusion: The date and datetime algorithms produced the most valid measures of CHD and MI episodes. Findings underscore the importance of identifying admission and discharge dates/times belonging to the same individual in enumerating these episodes.

Purpose: We developed a hybrid safety surveillance approach for a large, pragmatic clinical trial of a high-dose quadrivalent influenza vaccine (QIV-HD), using both active and passive data collection methods. Here, we present the methods and results for the passive register-based surveillance of serious adverse events (SAEs), which replaced conventional SAE reporting during the trial.

Patients and methods: The trial recruited over 33,000 older adults of whom 50% received the QIV-HD while the rest received a standard-dose vaccine (QIV-SD) as a control vaccine. We collected diagnoses related to all acute hospitalizations during the six months following vaccination from national registers. During the blinded phase of the trial, we utilized a cohort study design and compared the incidences of 1811 ICD10 diagnosis groups (SAE categories) between the trial population and older adults vaccinated with the QIV-SD outside the trial, either during the study or the previous influenza season. Based on a real-time probabilistic comparison, we flagged SAE categories with higher incidence in the trial population and then evaluated possible causal associations between each flagged category and the trial intervention.

Results: Our novel approach to safety surveillance provided information, which we could evaluate in real-time during the trial. The trial participants experienced 1217 hospitalizations related to any SAE categories, contributed by 941 patients. We flagged 10 SAE categories for further analysis during the study but based on further data review, none presented strong evidence of causality with vaccination.

Conclusion: Safety signals can be detected and evaluated in real-time during a pragmatic vaccine trial with register-based follow-up, utilizing passive data collection and population level comparison. Compared to conventional methods of safety follow-up, this method is likely to be more comprehensive, objective and resource effective.

Background: The increasing use of routinely collected health data for research puts great demands on data quality. The Danish National Patient Registry (DNPR) is renowned for its longitudinal data registration since 1977 and is a commonly used data source for cardiovascular epidemiology.

Objective: To provide an overview and examine determinants of the cardiovascular data quality in the DNPR.

Methods: We performed a systematic literature search of MEDLINE (PubMed) and the Danish Medical Journal, and identified papers validating cardiovascular variables in the DNPR during 1977-2024. We also included papers from reference lists, citations, journal e-mail notifications, and colleagues. Measures of data quality included the positive predictive value (PPV), negative predictive value, sensitivity, and specificity.

Results: We screened 2,049 papers to identify 63 relevant papers, including a total of 229 cardiovascular variables. Of these, 200 variables assessed diagnoses, 24 assessed treatments (10 surgeries and 14 other treatments), and 5 assessed examinations. The data quality varied substantially between variables. Overall, the PPV was ≥90% for 36% of variables, 80-89% for 26%, 70-79% for 16%, 60-69% for 7%, 50-59% for 4%, and <50% for 11% of variables. The predictive value was generally higher for treatments (PPV≥95% for 92%) and examinations (PPV≥95% for 100%) than for diagnoses (PPV≥80% for 71%). Moreover, the PPV varied for individual diagnoses depending on the algorithm used to identify them. Key determinants for validity were patient contact type (inpatient vs outpatient), diagnosis type (primary vs secondary), setting (university vs regional hospitals), and calendar year.

Conclusion: The validity of cardiovascular variables in the DNPR is high for treatments and examinations but varies considerably between individual diagnoses depending on the algorithm used to define them.

Purpose: To estimate the strength of association between use of antithrombotics (AT) drugs with survival after spontaneous intracerebral hemorrhage (s-ICH) comparing oral anticoagulant (OAC) or platelet antiaggregants (PA) with no AT use and in active comparator analyses OAC vs PA, direct oral anticoagulant (DOAC) vs vitamin K antagonist (VKA), and clopidogrel vs aspirin.

Patients and methods: We identified patients ≥55 years with a first-ever s-ICH between 2015 and 2018 in Southern Denmark (population 1.2 million). From this population, patients who had used an AT at the time of ICH were identified and classified as OAC or PA vs no AT (reference group), and for active comparator analyses as OAC vs PA (reference group), DOAC vs VKA (reference group), or clopidogrel vs aspirin (reference group). We calculated adjusted relative risks (aRRs) and corresponding [95% confidence intervals] for 90-day all-cause mortality with adjustments for potential confounders.

Results: Among 1043 patients who had s-ICH, 206 had used an OAC, 270 a PA, and 428 had no AT use. The adjusted 90-day mortality was higher in OAC- (aRR 1.68 [1.39-2.02]) and PA-users (aRR 1.21 [1.03-1.42]), compared with no AT. Mortality was higher in OAC- (aRR 1.19 [1.05-1.36]) vs PA-users. In analyses by antithrombotic drug type, 88 used a DOAC, 136 a VKA, 111 clopidogrel, and 177 aspirin. Mortality was lower among DOAC- vs VKA-users (aRR 0.82 [0.68-0.99]), but similar between clopidogrel vs aspirin users (aRR 1.04 [0.87-1.24]).

Conclusion: In this unselected cohort from a geographically defined Danish population, 90-day mortality after s-ICH was higher in patients with prior use of an OAC compared with no AT use or patients using a PA. Mortality was slightly lower for patients using a DOAC than a VKA. Mortality was also higher in PA- vs no AT-users, but there were no differences in mortality between clopidogrel vs aspirin.

Purpose: Myocardial perfusion imaging (MPI) procedures from single photon emission computed tomography and positron emission tomography imaging have been registered in the Western Denmark Heart Registry (WDHR) since 2017 as a sub-registry (WDHR-MPI). The aim was to review the content, quality, and research potential of the WDHR-MPI and assess the completeness and validity of its key variables.

Patients and methods: Using the Danish National Patient Registry (DNPR) as a reference, we calculated the completeness of procedure registration as the proportion of procedures registered in the WDHR-MPI from 2017 to 2021. We defined completeness of variable registration as the proportion of non-missing values for a given variable and examined it for 38 key variables. We assessed validity by estimating the positive predictive values (PPV) and negative predictive values (NPV) with 95% confidence intervals (CI) for 26 selected key variables using corresponding extracted information from 300 randomly selected patient records.

Results: We identified 19,084 procedures in 17,871 patients from all seven cardiac centers performing nuclear cardiology procedures in the WDHR uptake area. The registry accumulated 4000-6000 procedures each year from 2019 to 2021. The overall completeness of procedure registration was 72% (95% CI 72-73), increasing from 14% (95% CI 13-15) in 2017 to 98% (95% CI 98-98) in 2021. The mean completeness of variable registration was 89%. The validity of entered data was high, with an overall PPV for the selected key variables of 95% (95% CI 94-95) and NPV of 94% (95% CI 93-96).

Conclusion: The WDHR-MPI is one of the largest systematic MPI cohorts. The overall high completeness and validity of the data support its potential for cardio-epidemiological research.

The Western Denmark Heart Registry (WDHR) is a semi-national, multicenter-based clinical registry with unique potential for cardiovascular research. The registry has provided detailed prospectively registered information on patient and procedure characteristics since 1999. WDHR data can be linked to additional data in other healthcare registries in Denmark. Therefore, the WDHR is a valuable data resource for cardiovascular research, providing a foundation for numerous research projects and publications. This review describes three currently available cohorts from the WDHR containing individual-level information on: i) 200,647 first-time coronary angiographies from 2003 to 2021, ii) 88,630 first-time percutaneous coronary interventions from 1999 to 2022, and iii) 85,512 first-time coronary computed tomography angiographies from 2008 to 2021. Furthermore, we describe other frequently cross-linked Danish healthcare registries containing information on various patient characteristics and outcomes, such as vital status, cause of death, hospitalizations, medications, and laboratory test results. The comprehensive overview of these cohorts aims to assist researchers, collaborators, and other interested parties in understanding the scope and potential applications of the available data. All cohorts are regularly updated, thereby supporting continuing research on cardiovascular clinical practice and prognosis in Denmark.

Background: Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia in critically ill patients and significantly impacts mortality. This study sought to evaluate the impact of new-onset AF on mortality in a critically ill population.

Methods: This study identified 48018 adult patients admitted to the ICU from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Patients were categorized as no AF, pre-existing AF, or new-onset AF. We analyzed mortality at 3 months, 6 months, and 1 year.

Results: Overall, 31,562 (65.73%) patients had no AF, 4877 (10.16%) had pre-existing AF, and 11,579 (24.11%) had new-onset AF. Median ages were 61.47 years (no AF), 76.12 years (pre-existing AF), and 75.26 years (new-onset AF). New-onset AF was associated with the highest mortality rates: 25.16% at 3 months, 29.23% at 6 months, and 34.04% at 1 year, compared to 17.94%, 22.55%, and 28.52% for pre-existing AF, and 14.54%, 17.25%, and 20.69% for no AF respectively (p < 0.001 for all). Multivariate Cox regression indicated that new-onset AF significantly increased the risk of 1-year mortality by 15.5% compared to no AF (HR: 1.155, 95% CI: 1.101-1.212; p < 0.001) and by 23.9% compared to pre-existing AF (HR: 1.239, 95% CI: 1.164-1.318; p < 0.001). Kaplan-Meier analysis confirmed lower survival probabilities for new-onset AF over one year compared to the other groups (p < 0.001).

Conclusion: In patients with critical illness, new-onset AF is associated with an increased risk of mortality compared with pre-existing AF or no AF.

Purpose: Routinely collected clinical data are a valuable resource for epidemiological research in infectious diseases. We examined the validity of the ICD-10 diagnosis code K75.0 for pyogenic liver abscess (PLA) from hospital discharge registries.

Patients and methods: This validation study was conducted in the North Denmark Region, using data from Aalborg University Hospital and the North Denmark Regional Hospital, along with their smaller regional satellite hospitals. The study period extended from January 1, 2010, to June 30, 2022, covering a catchment population of approximately 590,000 inhabitants. We identified patients with a first diagnosis (primary or secondary) of PLA (ICD-10 code K75.0) recorded in the Danish National Patient Registry and estimated the positive predictive value (PPV) of the PLA diagnosis using medical records as the reference standard. Subanalyses of PPV were conducted based on the department setting (emergency, medical, or surgical).

Results: A total of 297 patients received an ICD-10 diagnosis code of K75.0 during the study period. Five (2.0%) patients were excluded due to initial hospitalization outside the North Denmark Region, and 67 (23%) were misclassified. The overall PPV for the K75.0 diagnosis code during the study period was 77% (95% CI: 72-82%). The highest PPV, 88% (95% CI: 81-93%), was observed in patients diagnosed in medical departments, while the lowest PPV, 56% (95% CI: 30-80%), was observed in patients diagnosed in emergency wards. The PPV for surgical departments was 69% (95% CI: 61-77%).

Conclusion: The overall PPV of the ICD-10 diagnosis code K75.0 for PLA was 77%. Variability in PPVs across departments suggested differences in diagnostic accuracy, with medical departments demonstrating the highest PPV.