Utrecht Patient Oriented Database Research Articles

#615 Generalisability of cardiovascular RCTs to patients with chronic kidney disease in clinical practice: a comparison between RCTs and real-world data

Abstract Background and Aims Randomised controlled trials (RCTs) often apply stringent eligibility criteria, which could limit the external applicability of RCTs to patients in routine clinical practice. This is specifically troublesome in the setting of chronic kidney disease (CKD) given that kidney disease is commonly used as an ineligibility criterion in RCTs. In this pilot study we estimated the eligibility of patients with CKD in routine clinical practice in five major cardiovascular outcome trials - CREDENCE, DAPA-CKD, CIBIS II, CIBIS III, and AUGUSTUS - and described reasons for ineligibility. Method We included patients with CKD (defined as an estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m2 or an urinary albumin creatinine ratio (UACR) >3 mg/mmol present for >3 months) from the Utrecht Patient Oriented Database (UPOD) who visited a cardiovascular outpatient clinic in the University Medical Centre Utrecht between 2012 and 2019. The eligibility criteria were extracted from the selected RCTs and consequently modelled on the patients from UPOD. The percentage of eligible patients and reasons for ineligibility were described descriptively. The percentage of eligible patients for CIBIS II and CIBIS III were only calculated for patients with heart failure, and for the AUGUSTUS trial for patients with coronary artery disease as patients with these conditions were targeted. Patients could not fulfil multiple inclusion criteria and or meet multiple exclusion criteria or both. Results In total, 9005 UPOD patients with CKD were included. Patients had a mean age of 65 ± 14 years, 42% was female, mean eGFR was 49 ± 17, 1741 (19%) had a history of atherosclerotic cardiovascular disease, and 765 (8%) of heart failure. Overall, 0.05% of patients would be eligible for the DAPA-CKD trial and 0% for the CREDENCE trial. Of included patients with heart failure, 2% would have been eligible for CIBIS II and 3% for CIBIS III. Of included patients with coronary artery disease, 2% would have been eligible for the AUGUSTUS trial. Main reasons for ineligibility for DAPA-CKD were not fulfilling the inclusion criteria for UACR (52%), eGFR (20%), or the prescription of RAAS-inhibitors (arb) (49%) or meeting the exclusion criteria for primary kidney disease (PRD, 6%), or a kidney transplant (15%), or other comorbidities. Similarly, patients were often ineligible for the CREDENCE trial because they did not fulfill the inclusion criteria for UACR (48%), eGFR (18%), HbA1c (35%), or prescription of a RAAS-inhibitor (43%) or met one of the exclusion criteria for PRD (29%), cardiovascular disease (23%), or prescription of a mineralocorticoid receptor antagonist (10%). For CIBIS II, main reasons for ineligibility were not fulfilling the inclusion criteria for left-ventricular ejection fraction (LVEF, 50%) or prescription of an ace-inhibitor (42%) or diuretic (33%) or meeting the exclusion criteria of coronary artery disease (17%) or prescription of a calcium-channel blocker (16%). For CIBIS III, patients were also ineligible because they were not fulfilling the inclusion criteria for age (46%), LVEF (46%), or prescription of diuretics (31%) or met the exclusion criteria for serum creatinine (9%) or prescription of an angiotension receptor blocker (14%). Lastly, for the AUGUSTUS trial, patients were mainly ineligible due to not fulfilling the inclusion criteria of atrial fibrillation (79%) or percutaneous coronary interventions (PCI, 91%) or meeting the eGFR exclusion criteria (14%). Conclusion Based on this pilot study, less than 3% of patients with CKD in routine clinical practice would be eligible to participate in cardiovascular RCTs. Patients were often ineligible because they did not fulfil the inclusion criteria and a substantial number of patients was ineligible due to kidney disease. The low eligibility rate of patients with CKD in cardiovascular trials could limit the generalisability of results to patients with CKD treated in practice. To improve generalisability, RCTs in patients with CKD should aim to include more patients who reflect the patients with CKD treated in practice.

#1920 The impact of kidney function on cardiac diastolic dysfunction trajectories: insights from a longitudinal study

Abstract Background and Aims Although the association between kidney dysfunction and cardiac diastolic dysfunction has been investigated in cross-sectional studies, we currently lack a complete understanding of how the diastolic dysfunction changes over time in individuals with different kidney functions. Exploring the diastolic dysfunction trajectories is crucial as it can provide valuable insights into how kidney function influences cardiac health and which patients are at the highest cardiovascular risk. E/e’ is an echocardiography measure that estimates left ventricular filling pressure and diastolic dysfunction. This study evaluates how kidney function impacts changes in E/e′ over time. Method We identified patients from the Utrecht Patient Oriented Database (UPOD) who visited the outpatient clinic of Utrecht University Medical Center between January 2012 and April 2022. Patients who had received at least three echocardiography reports with a minimum of 12 months between them and had recorded serum creatinine measurements in their electronic health records were included. The estimated glomerular filtration rate (eGFR [mL/min/1.73 m2]) was calculated using the CKD-EPI 2021 creatinine formula without ethnicity and categorized as follows: eGFR ≥ 90, eGFR ≥ 60 - <90, eGFR < 60. Linear mixed-effect models were utilized to determine the impact of kidney function on changes in E/e′ over time. Results A total of 436 patients were included of whom 34.7% were women. The total number of echocardiography examination was 1308. Overall, the median eGFR for all patients was 78.2 mL/min/1.73 m2 [IQR: 61.9, 90.7]. Among them, 26.6%, 51.4%, and 22.0%, had an eGFR ≥ 90, eGFR ≥ 60 - < 90, and eGFR < 60, respectively. Patients with an eGFR < 60 had a higher prevalence of hypertension (64.6%) and cardiovascular disease (84.4%) compared to those with an eGFR ≥ 90, where the prevalence of hypertension and cardiovascular disease was 49.1% and 67.2%, respectively. Additionally, patients with an eGFR < 60 had the lowest mean ejection fraction of 44.9% ± 18.5% and the highest median E/e′ of 12.84 [10.10, 16.16]. The linear mixed model analysis showed that the estimated change in E/e′ per year depended on the level of kidney function. For patients with eGFR ≥ 60 - <90, E/e′ did not significantly change per year (p-value: 0.927). However, for patients with eGFR < 60, a statistically significant (p = 0.014) increase in the E/e′ of 0.45 (0.09, 0.81) was observed per year. Hypertension, diabetes mellitus, and cardiovascular disease were found to affect the change in E/e′, with estimates of 0.95 (0.41, 1.49), 1.82 (0.82, 2.89), and 1.25 (0.54, 1.97), respectively. Conclusion The trajectory of changes in E/e′ over time was significantly affected by varying levels of kidney function. Patients with impaired kidney function (eGFR < 60) have a higher E/e’ compared to those with normal kidney function (eGFR ≥ 90) and presented a significant increase of E/e’ per year.

#614 Identifying distinct patient phenotypes in patients with chronic kidney disease

Abstract Background and Aims Patients with chronic kidney disease (CKD) are heterogeneous in terms of age, causes of CKD, and comorbidities. Although individual risk factors greatly influence patients’ risk of clinical outcomes, this heterogeneity is rarely used to guide clinical decision-making. In this study we aimed to derive phenotypes in patients with CKD based on characteristics commonly available in routine clinical practice and evaluated whether these phenotypes were associated with clinical outcomes. Method Patients from the Utrecht Patient Oriented Database (UPOD) who were 18 years or older with CKD (defined as an eGFR <60 ml/min/1.73 m2 or an UACR > 3 mg/mmol present for >3 months) and visited one of the cardiovascular outpatient clinics of the University Medical Center Utrecht between 2012 and 2019 were included. Patient phenotypes were derived with latent class analyses based on age, sex, CKD stage, cause of kidney disease, and (cardiovascular) comorbidities. The incidence rate/100 person years (IR/100PY) for all-cause mortality and kidney failure (defined as initiation of kidney replacement therapy or a sustained eGFR <15) and 95% confidence interval (95% CI) was calculated for each phenotype. Results Overall 9005 patients were included (mean age 65 ± 14 years, 42% women, mean estimated glomerular filtration rate (eGFR) 49 ± 17 ml/min/1.73 m2). The median follow-up was 3.8 years [interquartile range 1.8–6.4]. Latent class analysis identified 7 phenotypes with the following characteristics: phenotype 1 were young patients with primary kidney disease (10%); phenotype 2 were patients with diabetes and a preserved eGFR (9%); phenotype 3 were patients with low comorbidity and inflammation (28%); phenotype 4 were older patients with a history of cardiovascular disease (27%); phenotype 5 were older patients with a history of cardiovascular disease and severe CKD (16%); phenotype 6 were younger patients with a kidney transplant and low comorbidity (6%); and phenotype 7 were older patients with a kidney transplant and cardiovascular disease (6%). The risk of all-cause mortality and kidney failure differed significantly between the identified phenotypes. The phenotypes of younger kidney transplant recipients, younger patients with primary kidney disease, and diabetes with preserved eGFR had the lowest risk for all-cause mortality (for all, IR/100 PY <5) (Fig. 1). The phenotypes with an intermediate incidence rate for all-cause mortality were the low comorbidity and inflammation phenotype (IR/100PY 7.4, 95% CI 6.9–8.0), the phenotype of older patients with cardiovascular disease (IR/100PY 7.2, 95% CI 6.7–7.8), and the phenotype of older patients with a kidney transplant and cardiovascular disease (IR/100PY 6.5, 95% CI 5.5–7.6). The phenotypes with highest incidence rate for all-cause mortality was the phenotype of older patients with cardiovascular disease and severe CKD (IR/100PY 12.5, 95% CI11.5–13.4). The phenotypes with the lowest risk for kidney failure were the diabetes phenotype, the low comorbidity and inflammation phenotype, and the phenotype of older patients with cardiovascular disease (all IR/100 PY <1). The phenotype of older patients with cardiovascular disease and severe CKD also had the highest risk to develop kidney failure (IR/100PY 5.8, 95% CI 5.1–6.6), followed by the phenotype of patients with primary kidney disease (IR/100PY 4.4, 95% CI 3.7 −5.5). Conclusion We identified 7 different phenotypes of patients with CKD including 2 phenotypes of patients with a kidney transplant with different clinical characteristics and prognosis. The differences in risk of all-cause mortality and kidney failure warrants a different monitoring and follow-up across the different phenotypes within the setting of CKD. Future studies should invest In evaluating the implementation of our identified phenotypes in routine clinical practice or clinical trial design with respect to differences in treatments.

#5596 MODERATE AND SEVERE KIDNEY DYSFUNCTION ASSOCIATED WITH LEFT VENTRICLE DIASTOLIC DYSFUNCTION: A COHORT WITH DATA FROM ELECTRONIC HEALTHCARE RECORDS

Abstract Background and Aims Left ventricular diastolic dysfunction is observed in patients with chronic kidney disease (CKD) and may lead to heart failure with preserved ejection fraction (HFpEF). In this study, we investigate the association between kidney dysfunction and left ventricular diastolic dysfunction (LVDD) in a cohort using data from electronic healthcare records. Method We utilized electronic healthcare data from the Utrecht Patient Oriented Database (UPOD), including all patients treated at University Medical Center Utrecht (UMCU), a university teaching hospital. We extracted demographic patient data, admission data, medication orders, and laboratory results. All performed echocardiography from baseline (i.e., first visit to the hospital) to end of follow-up (i.e., death or censoring) were included. The estimated glomerular filtration rate (eGFR) was calculated using the creatinine formula without ethnicity. Participants were divided into four groups depending on their eGFR (mL/min/1.73 m2) as follows: normal kidney function (eGFR ≥ 90), mild kidney dysfunction (eGFR ≥ 60–89), moderate kidney dysfunction (eGFR ≥ 30–59), and severe kidney dysfunction (eGFR < 30). The association of eGFR with E/A and E/e’ ratio was tested by multivariable adjusted cox proportional hazards survival analysis, reporting hazard ratios (HR) and 95% confidence intervals (CI). Results We identified 6,216 participants who received echocardiography as part of their routine care between 2012 and 2022. The mean age was 66.9 (SD: 12.04 years), and 41.7% of individuals were females. In total, 90.4% and 24.5% of the patients had, respectively, hypertension and diabetes. Twenty-six per cent of participants had normal kidney function, 48.2% had mild kidney dysfunction, and 21.3% and 4% had moderate and severe kidney dysfunction, respectively. In total, 16,935 echocardiography were performed. The median time from the first to the final echocardiography was 0.78 (IQR: 2.89 years). Adjusted multivariable analysis showed that patients with moderate (HR: 1.19; 95% CI: 1.09, 1.31) and severe kidney dysfunction (HR: 1.36; 95% CI: 1.14, 1.62) had higher probabilities of having E/A ratio <0.75 or >1.8 compared with those with normal kidney function. Similarly, for an E/e’ ratio >14, participants with moderate and severe kidney dysfunction had higher probabilities, HR: 1.62 (95% CI: 1.49, 1.77) and 2.10 (95% CI: 1.83, 2.42), respectively, compared with participants with normal kidney function. Conclusion Moderate and severe kidney dysfunction are independently associated with LVDD. This association is independent of sex, age, hypertension, and diabetes status and is stronger for severe kidney dysfunction. Early recognition of LVDD in kidney dysfunction might help identify those at highest risk of developing HFpEF.

Added diagnostic value of routinely measured hematology variables in diagnosing immune checkpoint inhibitor mediated toxicity in the emergency department.

Immune checkpoint inhibitors (ICI) show remarkable results in cancer treatment, but at the cost of immune-related adverse events (irAE). irAE can be difficult to differentiate from infections or tumor progression, thereby challenging treatment, especially in the emergency department (ED) where time and clinical information are limited. As infections are traceable in blood, we were interested in the added diagnostic value of routinely measured hematological blood cell characteristics in addition to standard diagnostic practice in the ED to aid irAE assessment. Hematological variables routinely measured with our hematological analyzer (Abbott CELL-DYN Sapphire) were retrieved from Utrecht Patient Oriented Database (UPOD) for all patients treated with ICI who visited the ED between 2013 and 2020. To assess the added diagnostic value, we developed and compared two models; a base logistic regression model trained on the preliminary diagnosis at the ED, sex, and gender, and an extended model trained with lasso that also assessed the hematology variables. A total of 413 ED visits were used in this analysis. The extended model showed an improvement in performance (area under the receiver operator characteristic curve) over the base model, 0.79 (95% CI 0.75-0.84), and 0.67 (95% CI 0.60-0.73), respectively. Two standard blood count variables (eosinophil granulocyte count and red blood cell count) and two advanced variables (coefficient of variance of neutrophil depolarization and red blood cell distribution width) were associated with irAE. Hematological variables are a valuable and inexpensive aid for irAE diagnosis in the ED. Further exploration of the predictive hematological variables could yield new insights into the pathophysiology underlying irAE and in distinguishing irAE from other inflammatory conditions.

Optimizing cardiovascular risk assessment and registration in a developing cardiovascular learning health care system: Women benefit most.

Since 2015 we organized a uniform, structured collection of a fixed set of cardiovascular risk factors according the (inter)national guidelines on cardiovascular risk management. We evaluated the current state of a developing cardiovascular towards learning healthcare system-the Utrecht Cardiovascular Cohort Cardiovascular Risk Management (UCC-CVRM)-and its potential effect on guideline adherence in cardiovascular risk management. We conducted a before-after study comparing data from patients included in UCC-CVRM (2015-2018) and patients treated in our center before UCC-CVRM (2013-2015) who would have been eligible for UCC-CVRM using the Utrecht Patient Oriented Database (UPOD). Proportions of cardiovascular risk factor measurement before and after UCC-CVRM initiation were compared, as were proportions of patients that required (change of) blood pressure, lipid, or blood glucose lowering treatment. We estimated the likelihood to miss patients with hypertension, dyslipidemia, and elevated HbA1c before UCC-CVRM for the whole cohort and stratified for sex. In the present study, patients included up to October 2018 (n = 1904) were matched with 7195 UPOD patients with similar age, sex, department of referral and diagnose description. Completeness of risk factor measurement increased, ranging from 0% -77% before to 82%-94% after UCC-CVRM initiation. Before UCC-CVRM, we found more unmeasured risk factors in women compared to men. This sex-gap resolved in UCC-CVRM. The likelihood to miss hypertension, dyslipidemia, and elevated HbA1c was reduced by 67%, 75% and 90%, respectively, after UCC-CVRM initiation. A finding more pronounced in women compared to men. In conclusion, a systematic registration of the cardiovascular risk profile substantially improves guideline adherent assessment and decreases the risk of missing patients with elevated levels with an indication for treatment. The sex-gap disappeared after UCC-CVRM initiation. Thus, an LHS approach contributes to a more inclusive insight into quality of care and prevention of cardiovascular disease (progression).

Preventing unnecessary imaging in patients suspect of coronary artery disease through machine learning of electronic health records.

With the ageing European population, the incidence of coronary artery disease (CAD) is expected to rise. This will likely result in an increased imaging use. Symptom recognition can be complicated, as symptoms caused by CAD can be atypical, particularly in women. Early CAD exclusion may help to optimize use of diagnostic resources and thus improve the sustainability of the healthcare system. To develop sex-stratified algorithms, trained on routinely available electronic health records (EHRs), raw electrocardiograms, and haematology data to exclude CAD in patients upfront. We trained XGBoost algorithms on data from patients from the Utrecht Patient-Oriented Database, who underwent coronary computed tomography angiography (CCTA), and/or stress cardiac magnetic resonance (CMR) imaging, or stress single-photon emission computerized tomography (SPECT) in the UMC Utrecht. Outcomes were extracted from radiology reports. We aimed to maximize negative predictive value (NPV) to minimize the false negative risk with acceptable specificity. Of 6808 CCTA patients (31% female), 1029 females (48%) and 1908 males (45%) had no diagnosis of CAD. Of 3053 CMR/SPECT patients (45% female), 650 females (47%) and 881 males (48%) had no diagnosis of CAD. On the train and test set, the CCTA models achieved NPVs and specificities of 0.95 and 0.19 (females) and 0.96 and 0.09 (males). The CMR/SPECT models achieved NPVs and specificities of 0.75 and 0.041 (females) and 0.92 and 0.026 (males). Coronary artery disease can be excluded from EHRs with high NPV. Our study demonstrates new possibilities to reduce unnecessary imaging in women and men suspected of CAD.

Microarray testing in patients with systemic lupus erythematosus identifies a high prevalence of CpG DNA-binding antibodies

ObjectiveMany autoantibodies are known to be associated with SLE, although their role in clinical practice is limited because of low sensitivity and weak associations with clinical manifestations. There has been...

Routinely measured hematological parameters and prediction of recurrent vascular events in patients with clinically manifest vascular disease.

Background and aimsThe predictive value of traditional risk factors for vascular events in patients with manifest vascular disease is limited, underscoring the need for novel biomarkers to improve risk stratification. Since hematological parameters are routinely assessed in clinical practice, they are readily available candidates.MethodsWe used data from 3,922 vascular patients, who participated in the Second Manifestations of ARTerial Disease (SMART) study. We first investigated associations between recurrent vascular events and 22 hematological parameters, obtained from the Utrecht Patient Oriented Database (UPOD), and then assessed whether parameters associated with outcome improved risk prediction.ResultsAfter adjustment for all SMART risk score (SRS) variables, lymphocyte %, neutrophil count, neutrophil % and red cell distribution width (RDW) were significantly associated with vascular events. When individually added to the SRS, lymphocyte % improved prediction of recurrent vascular events with a continuous net reclassification improvement (cNRI) of 17.4% [95% CI: 2.1, 32.1%] and an increase in c-statistic of 0.011 [0.000, 0.022]. The combination of lymphocyte % and neutrophil count resulted in a cNRI of 22.2% [3.2, 33.4%] and improved c-statistic by 0.011 [95% CI: 0.000, 0.022]. Lymphocyte % and RDW yielded a cNRI of 18.7% [3.3, 31.9%] and improved c-statistic by 0.016 [0.004, 0.028]. However, the addition of hematological parameters only modestly increased risk estimates for patients with an event during follow-up.ConclusionsSeveral hematological parameters were independently associated with recurrent vascular events. Lymphocyte % alone and in combination with other parameters enhanced discrimination and reclassification. However, the incremental value for patients with a recurrent event was limited.

Commonly available hematological biomarkers are associated with the extent of coronary calcifications

Background and aimsWe aimed to improve the understanding of potential associations between commonly available hematological biomarkers and the coronary artery calcification (CAC) score, which may help unravel the pathophysiology of coronary calcifications and subclinical coronary artery disease. MethodsA cross-sectional study was performed within the Utrecht Patient Oriented Database (UPOD). Patients with suspected or known coronary artery disease who underwent CT CAC scoring as well as standard hematology analysis that was part of routine clinical care (within 3 months of CT acquisition) were included. Complete hematology datasets were extracted from hematology analyzers. Linear regression adjusted for potential confounders was used to assess if hematological biomarkers were related to the CAC score. ResultsIn total, 1504 patients were included, of whom 43% (n = 647) had a CAC score of 0. Mean age (±SD) was 53 ± 13 years, and 34% of patients were women. Red blood cell distribution width (RDW, β = 0.20 [0.05–0.36], p=0.007), the fraction of immature reticulocytes (β = 0.97 [0.10–6.43], p=0.004), coefficient of variation of neutrophil lobularity (β = 0.13 [0.01–0.25], p=0.040) and mean lymphocyte cell size (β = 0.21 [0.08–0.34], p=0.001) were positively associated with the CAC score after adjustment for age, sex, body mass index (BMI), diabetes, glomerular filtration rate (GFR) and high-density lipoprotein (HDL). ConclusionsThis study confirms the known association of RDW with the CAC score, and presents the fraction of immature reticulocytes, coefficient of variation of neutrophil lobularity, and mean lymphocyte cell size as new markers associated with a higher CAC score.

Routinely analyzed leukocyte characteristics improve prediction of mortality after coronary angiography.

Inflammation and leukocyte infiltration are hallmarks of atherosclerosis. Clinically routine hematology analyzers mostly perform an entire differential blood count by default, irrespective of the requested parameter. We hypothesize that these normally unreported leukocyte characteristics associate with coronary artery disease (CAD) severity and can improve prediction of mortality in coronary angiography patients. We studied coronary angiography patients suspected of CAD (n = 1015) from the Utrecht Coronary Biobank cohort. Leukocyte characteristics were routinely assessed in blood drawn directly prior to angiography using an automated hematology analyzer and extracted from the Utrecht patient oriented database (UPOD) database. Patients were followed up for a median duration of 805 days, during which 65 patients died. We evaluated the association of leukocyte characteristics with synergy between PCI with taxus and cardiac surgery (SYNTAX) score as a measure of CAD severity, all-cause and cardiovascular mortality and major adverse cardiovascular events (MACEs). In order to determine the improvement of risk prediction, we calculated continuous net reclassification improvement (cNRI) and integrated discrimination improvement (IDI). Monocyte percentage showed strong independent predictive value for all-cause mortality (hazard ratio (HR) 1.44 (1.19-1.74), p < 0.001), and the monocyte-to-lymphocyte ratio performed best for cardiovascular mortality (HR 1.42 (1.11-1.81), p = 0.005). The cNRIs and IDIs of leukocyte characteristics for all-cause mortality confirmed the improvement in mortality risk prediction. No significantly predictive leukocyte characteristics were found for MACEs. Readily available yet unreported leukocyte characteristics from routine hematology analyzers significantly improved prediction of mortality in coronary angiography patients on top of clinical characteristics.

Hematological Parameters Improve Prediction of Mortality and Secondary Adverse Events in Coronary Angiography Patients: A Longitudinal Cohort Study.

Prediction of primary cardiovascular events has been thoroughly investigated since the landmark Framingham risk score was introduced. However, prediction of secondary events after initial events of coronary artery disease (CAD) poses a new challenge. In a cohort of coronary angiography patients (n = 1760), we examined readily available hematological parameters from the UPOD (Utrecht Patient Oriented Database) and their addition to prediction of secondary cardiovascular events. Backward stepwise multivariable Cox regression analysis was used to test their ability to predict death and major adverse cardiovascular events (MACE). Continuous net reclassification improvement (cNRI) and integrated discrimination improvement (IDI) measures were calculated for the hematological parameters on top of traditional risk factors to assess prediction improvement. Panels of 3 to 8 hematological parameters significantly improved prediction of death and adverse events. The IDIs ranged from 0.02 to 0.07 (all P < 0.001) among outcome measures and the cNRIs from 0.11 to 0.40 (P < 0.001 in 5 of 6 outcome measures). In the hematological panels red cell distribution width (RDW) appeared most often. The multivariable adjusted hazard ratio of RDW per 1 standard deviation (SD) increase for MACE was 1.19 [1.08-1.32], P < 0.001. Routinely measured hematological parameters significantly improved prediction of mortality and adverse events in coronary angiography patients. Accurately indicating high-risk patients is of paramount importance in clinical decision-making.

Fluorescence of neutrophil granulocytes as a biomarker for clozapine use

Non-adherence to medication is a major issue in the treatment of schizophrenia in general and in particular for those treated with clozapine. A reliable tool to quantify patients long-term adherence to clozapine is currently unavailable. Enhanced FL3 neutrophil granulocyte fluorescence was serendipitously observed in a small population of schizophrenic patients treated with clozapine. The present study was aimed at assessing the association between clozapine use and FL3-fluorescence.A cross-sectional study was performed using data from the Utrecht Patient Oriented Database (UPOD). A total of 38,390 inpatients were included, of which 124 (0.33%) used clozapine.FL3-fluorescence was significantly higher (U=240,179, P<0.001) in clozapine users (mean (SD)=90.5 (11.8)) than in non-users (mean (SD)=69.8 (3.3)). Observed FL3-fluorescence was found to increase with increasing clozapine dose. The area under the receiver operating characteristic curve was 0.95.Our results confirm the association between use of clozapine and elevated FL3-fluorescence. Further research is needed to unravel the underlying mechanism and to investigate the true potential of FL3-fluorescence as a clozapine-adherence biomarker in clinical practice.

Identification of exacerbations in obstructive lung disease through biomarkers

Inflammation has been identified as an important factor for disease exacerbation in obstructive lung disease. In this study, we used neutrophil and eosinophil counts as biomarkers for exacerbation in obstructive lung disease. We conducted a case–control study within a cohort of patients frequenting an outpatient clinic of Respiratory Medicine using data from the Utrecht Patient Oriented Database (UPOD). Cases were patients with a hospital admission for obstructive lung disease in 2005. For each case, one control patient was sampled from the same study base. We identified 143 cases (118 patients with chronic obstructive pulmonary disease and 25 asthma patients) and 143 controls. Admission was associated with both neutrophilia (adjusted odds ratio (OR) 4.3; 95% confidence interval (CI) 2.2–8.5), and eosinophilia (adjusted OR 2.6; 95% CI 1.1–6.2). The association with eosinophilia was only seen in asthma patients. In conclusion, neutrophil and eosinophil counts seem to be useful biomarkers for identifying exacerbations in pharmacoepidemiological studies on obstructive lung disease.

Compliance with Platelet Count Monitoring Recommendations and Management of Possible Heparin-Induced Thrombocytopenia in Hospitalized Patients Receiving Low-Molecular-Weight Heparin

Summaries of product characteristics (SPCs) and clinical guideline recommendations are available for monitoring the platelet count for heparin-induced thrombocytopenia (HIT) in patients receiving low-molecular-weight heparin (LMWH). Testing for the presence of heparin-platelet factor 4 antibodies (HPF4-Ab) and starting alternative anticoagulation is recommended when HIT is suspected. To investigate the frequency of compliance with recommendations for platelet count monitoring and management of possible HIT in hospitalized patients receiving prophylaxis and treatment dosing of LMWH for at least 5 consecutive days. A retrospective cohort study within the Utrecht Patient Oriented Database (UPOD) was conducted. For all inpatients, all episodes of exposure to dalteparin or nadroparin for at least 5 consecutive days in 2004-2005 were selected. In 4 different nonexclusive groups of patients (all pts. receiving dalteparin, all pts. receiving nadroparin, surgical pts. with a prophylactic dose of either dalteparin or nadroparin, and pts. exposed to unfractionated heparin [UFH] within 100 days before receiving either dalteparin or nadroparin), compliance with recommendations for platelet count monitoring from SPCs and a clinical guideline was studied. The frequency of compliance with these recommendations was determined. In addition, it was determined whether patient and treatment characteristics were associated with regular platelet count monitoring. Finally, the frequency of testing for HPF4-Ab and the initiation of danaparoid treatment in patients with a drop of at least 50% in platelet count were investigated. A total of 6804 patients, with 7770 episodes of LMWH treatment, were included in the analysis. The frequency of compliance with platelet count monitoring recommendations was 26.3% for all patients receiving dalteparin, 35.6% for all patients receiving nadroparin, 23.0% for surgical patients receiving prophylactic dosing of either dalteparin or nadroparin, and 41.5% for patients exposed to UFH within 100 days before the start of either dalteparin or nadroparin treatment. Regular platelet count monitoring was strongly positively associated with medical patients (relative risk [RR] 2.33), surgical patients (RR 2.03), critically ill patients (RR 2.80), and those with recent exposure to UFH (RR 2.19). The frequency of testing for HPF4-Ab was 5.4% and the initiation of alternative anticoagulation with danaparoid in patients with a 50% drop in platelet count was 0%. The results suggest that compliance with recommendations for platelet count monitoring and management of possible HIT is low at our institution. Policies and tools to improve compliance with recommended laboratory monitoring should be developed to secure the safe use of LMWH and other medications.

Hematocytometry analysis as discriminative marker for asthma phenotypes

There is an increasing demand for easy to measure biomarkers in clinical practice. We created the relational database Utrecht Patient Oriented Database (UPOD) to develop tools for identifying new biomarkers for disease. In this study, we used UPOD to identify better biomarkers for discriminating different asthma phenotypes. We performed a prospective study at the University Medical Center (UMC) Utrecht using blood from patients with asthma and a healthy reference group. Since asthma is an inflammatory disease, absolute leukocyte counts and leukocyte differential parameters were analyzed using raw data files and a logistic regression model. We compared 17 difficult-to-treat asthma (DTA) cases, 13 non-difficult-to-treat asthma cases, and 19 healthy volunteers. Absolute leukocyte counts and differential parameters for leukocytes were able to discriminate asthma patients from healthy volunteers. However, among patients with asthma, difficult-to-treat cases could be more accurately defined with a neutrophil morphology change (OR 8.0; 95% CI 1.5-42.0), compared to the absolute neutrophil count (OR 4.0; 95% CI 0.8-21.0). In this asthma patient population, we were able to define asthma phenotypes more precisely using neutrophil morphology parameters, compared to absolute counts. Using UPOD with differential parameters, it is possible to conduct larger scale biomarker studies, combining clinical, laboratory medicine, and epidemiological techniques.

Platelet Measurements versus Discharge Diagnoses for Identification of Patients with Potential Drug-Induced Thrombocytopenia

In pharmacoepidemiological studies on the risk of drug-induced blood dyscrasias, including drug-induced thrombocytopenia (DIT), hospital discharge diagnoses have been used to identify potential cases. One of the possible limitations of discharge diagnoses is that due to incomplete registration not all potential cases are identified, which may limit statistical power. Clinical laboratory data have been suggested as a data type that is potentially more sensitive for identifying potential cases of adverse drug reactions than discharge diagnoses. To compare the number of patients with potential DIT that could be identified by using platelet measurements with the number of patients with potential DIT that could be identified by using discharge diagnoses for thrombocytopenia within a population of hospitalized patients. The study population of this cross-sectional study comprised all patients admitted to the University Medical Center Utrecht in 2004 and 2005, as captured within the Utrecht Patient Oriented Database (UPOD). The ratio of the number of patients with potential DIT based on platelet measurements (>or=1 platelet count below 100x10(9)/L without alternative diagnoses for DIT) to the number of patients with potential DIT based on discharge diagnoses for thrombocytopenia (International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM] codes 287.3-287.5 without alternative diagnoses for DIT) was determined. Within the study period there were 56,411 hospitalizations. 2817 patients (5.0%) had >or=1 platelet count below 100x10(9)/L. In 96.3% of these patients, alternative diagnoses for DIT were present, resulting in 103 (0.2%) patients with potential DIT based on platelet measurements. There were 74 patients (0.1%) with a discharge diagnosis for thrombocytopenia. In 81.1% of these patients, alternative diagnoses for DIT were present, resulting in 14 (0.02%) patients with potential DIT based on discharge diagnoses. This resulted in a ratio of the number of patients with potential DIT based on platelet measurements to the number of patients with potential DIT based on discharge diagnoses for thrombocytopenia of seven. This study showed that the use of platelet measurements is a more sensitive approach to the identification of patients with potential DIT than the use of discharge diagnoses for thrombocytopenia.

Adherence to Guidelines for Monitoring for Heparin-Induced Thrombocytopenia in Patients Treated with Low Molecular Weight Heparin

Laboratory monitoring for early detection of adverse drug reactions is recommended for many drugs. For patients treated with low molecular weight heparin (LMWH), the Summary of Product Characteristics (SPC) and clinical guidelines recommend to monitor the platelet count for heparin-induced thrombocytopenia (HIT), a potentially life-threatening adverse event, characterised by a typical drop in platelet count. When the platelet count drops without obvious explanation in these patients, testing for heparin-platelet factor 4 antibodies (HPF4-Ab) and initiating alternative anticoagulation are advised. In the current study adherence to recommended platelet count monitoring in clinical patients without thrombocytopenia-associated diseases treated with LMWH for at least five days at our institution, and adherence to recommended testing for HPF4-Ab and initiation of alternative anticoagulation in patients with potential HIT (defined as a drop of at least 50% in platelet count between days 5 and 14 following the start of LMWH treatment, or stopdate, whichever occurred first, compared to the highest platelet count within days 1–4) were investigated. Data from the Utrecht Patient Oriented Database (UPOD) were used for this retrospective cohort study. Inpatients exposed to the LMWHs dalteparin or nadroparin for at least five days during the period 2004–2005 were included. Patients with thrombocytopenia-related diseases were excluded. Firstly, adherence to recommended platelet count monitoring, based on recommendations from SPCs and clinical guidelines, was investigated. Secondly, the association between patient- and treatment characteristics and obtaining at least 2 platelets counts during treatment was investigated. Thirdly, adherence to recommended testing for HPF4-Ab and initiating treatment with danaparoid was investigated in patients with potential HIT. 6,804 patients with 7,770 episodes of LMWH treatment of at least five days were included. Adherence to the recommendations for platelet count monitoring from the SPC of nadroparin and dalteparin was 36.5% and 26.3% respectively. Adherence to the different platelet count monitoring recommendations from the 2002 clinical guideline on HIT was 23.0% and 41.5%. Obtaining at least 2 platelet counts during treatment was found to be strongly associated with ICU admission, previous UFH exposure, and a treatment duration of at least 10 days. There were 98 patients with potential HIT. Adherence to testing for HPF4-Ab in patients with potential HIT was 6.1%. Adherence to starting alternative anticoagulation in patients with potential HIT treatment was 0%. The results of this study suggest that adherence to recommendations for monitoring for HIT with LMWH is low at our institution. The results of this study justify to say that there is a need to think of appropriate actions for improving the awareness of HIT as an adverse reaction to LMWH, and to secure the safe use of LMWH.

Linking laboratory and medication data: new opportunities for pharmacoepidemiological research

Transfer of automated laboratory data collected during routine clinical care from the laboratory information system into a database format that enables linkage to other administrative (e.g., patient characteristics) or clinical (e.g., medication, diagnoses, procedures) data provides a valuable tool for clinical epidemiological research. It allows the investigation of biochemical characteristics of diseases, therapeutic effects and diagnostic and/or prognostic markers for disease with easy access and at relatively low cost. To this end, the Utrecht Patient Oriented Database (UPOD), an infrastructure of relational databases comprising data on patient characteristics, laboratory test results, medication orders, hospital discharge diagnoses and medical procedures for all patients treated at the University Medical Centre Utrecht since January 2004, was established. Current research within UPOD is focused on the innovative linkage of laboratory and medication data, which, for example, makes it possible to assess the quality of pharmacotherapy in clinical practice, to investigate interference between laboratory tests and drugs, to study the risk of adverse drug reactions, and to develop diagnostic and prognostic markers or algorithms for adverse drug reactions. Although recently established, we believe that UPOD broadens the opportunities for clinical pharmacoepidemiological research and can contribute to patient care from a laboratory perspective.