OHDSI MEETINGS THIS WEEK
OHDSI Community Call @gregk will give a demo of ARACHNE
Population-Level Estimation (Western hemisphere) workgroup meeting - Thursday at 12pm EThttps://meetings.webex.com/collabs/#/meetings/detail?uuid=M3T9BZV9RSB6YNDM8WDDZMI19D-D1JL&rnd=229240.54296
Hadoop WG meeting - Friday at 11am EThttps://meet.lync.com/quintiles-quintilesims/mui.vanzandt/R8V4N3S9
GIS working group meeting - Monday (February 5th) at 10am ET
Simple, modern video meetings for the global workforce. Join from anywhere, including your desktop, browser, mobile device, or video room device.
ANNOUNCEMENTS
2018 OHDSI Symposium - SAVE THE DATE!
2018 OHDSI F2F : It’s official! The next OHDSI face-to-face will take place on May 2-3rd 2018 at Columbia University Medical Center in New York. More details to come.
COMMUNITY PUBLICATIONS
Design and Evaluation of Trust–Eliciting Cues in Drug–Drug Interaction Alerts
Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms.
DJ Albers, N Elhadad, J Claassen, R Perotte, A Goldstein and G Hripcsak,
Journal of biomedical informatics , Feb 2018
We study the question of how to represent or summarize raw laboratory data taken from an electronic health record (EHR) using parametric model selection to reduce or cope with biases induced through clinical care. It has been previously demonstrated that the health care process (Hripcsak and Albers, 2012, 2013), as defined by measurement context (Hripcsak and Albers, 2013; Albers et al., 2012) and measurement patterns (Albers and Hripcsak, 2010, 2012), can influence how EHR data are distributed statistically (Kohane and Weber, 2013; Pivovarov et al., 2014). We construct an algorithm, PopKLD, which is based on information criterion model selection (Burnham and Anderson, 2002; Claeskens and Hjort, 2008), is intended to reduce and cope with health care process biases and to produce an intuitively understandable continuous summary. The PopKLD algorithm can be automated and is designed to be applicable in high-throughput settings; for example, the output of the PopKLD algorithm can be used as input for phenotyping algorithms. Moreover, we develop the PopKLD-CAT algorithm that transforms the continuous PopKLD summary into a categorical summary useful for applications that require categorical data such as topic modeling. We evaluate our methodology in two ways. First, we apply the method to laboratory data collected in two different health care contexts, primary versus intensive care. We show that the PopKLD preserves known physiologic features in the data that are lost when summarizing the data using more common laboratory data summaries such as mean and standard deviation. Second, for three disease-laboratory measurement pairs, we perform a phenotyping task: we use the PopKLD and PopKLD-CAT algorithms to define high and low values of the laboratory variable that are used for defining a disease state. We then compare the relationship between the PopKLD-CAT summary disease predictions and the same predictions using empirically estimated mean and standard deviation to a gold standard generated by clinical review of patient records. We find that the PopKLD laboratory data summary is substantially better at predicting disease state. The PopKLD or PopKLD-CAT algorithms are not meant to be used as phenotyping algorithms, but we use the phenotyping task to show what information can be gained when using a more informative laboratory data summary. In the process of evaluation our method we show that the different clinical contexts and laboratory measurements necessitate different statistical summaries. Similarly, leveraging the principle of maximum entropy we argue that while some laboratory data only have sufficient information to estimate a mean and standard deviation, other laboratory data captured in an EHR contain substantially more information than can be captured in higher-parameter models.
Central and cerebral haemodynamic changes after antihypertensive therapy in ischaemic stroke patients: A double-blind randomised trial.
MH Choi, JS Lee, SE Lee, SJ Lee, D Yoon, RW Park and JM Hong,
Scientific reports , 24 2018 01
Central and cerebral haemodynamic parameters can vary under similar brachial blood pressure (BP). We aimed to investigate the effects of antihypertensive agents on central and cerebral haemodynamic parameters in hypertensive patients with ischaemic stroke. The Fimasartan, Atenolol, and Valsartan On haemodynamic paRameters (FAVOR) study was conducted in a prospective, double-blinded manner. One hundred five patients were randomly administered atenolol, valsartan, or fimasartan during 12 weeks. We measured brachial, central, cerebral haemodynamic parameters and plasma N-terminal pro-brain natriuretic peptide (NT-proBNP) levels at baseline and after 12-week. Baseline haemodynamic parameters were balanced among the three groups. Even with similar brachial BP reduction, significantly lower central systolic BP (atenolol; 146.5 ± 18.8 vs. valsartan; 133.5 ± 20.7 vs. fimasartan; 133.6 ± 19.8 mmHg, p = 0.017) and augmentation index values (89.8 ± 13.2 vs. 80.6 ± 9.2 vs. 79.2 ± 11.6%; p = 0.001) were seen in the angiotensin receptor blockers (ARBs) groups. The pulsatility index on transcranial Doppler was significantly reduced in valsartan (p = 0.002) and fimasartan group (p = 0.008). Plasma NT-proBNP level was also significantly decreased in ARB groups, especially for the fimasartan group (37.8 ± 50.6 vs. 29.2 ± 36.9 vs.19.2 ± 27.8 pg/mL; p = 0.006). These findings suggest that short-term ARB administration would be favourable for ischaemic stroke patients with hypertension, permitting effective reduction of central pressure and dampening of cerebral pulsatility.
Calcium Channel Blockers in Secondary Cardiovascular Prevention and Risk of Acute Events: Real-World Evidence from Nested Case-Control Studies on Italian Hypertensive Elderly.
A Bettiol, E Lucenteforte, A Vannacci, N Lombardi, G Onder, N Agabiti, C Vitale, G Trifirò, G Corrao, G Roberto, A Mugelli, A Chinellato, N Agabiti, C Bartolini, R Bernabei, A Bettiol, S Bonassi, AP Caputi, S Cascini, A Chinellato, G Corrao, M Davoli, M Fini, R Gini, F Giorgianni, U Kirchmayer, F Lapi, N Lombardi, E Lucenteforte, A Mugelli, G Onder, F Rea, G Roberto, C Sorge, M Tari, G Trifirò, A Vannacci, DL Vetrano and C Vitale,
Clinical drug investigation , Dec 2017
Antihypertensive treatment with calcium channel blockers (CCBs) is consolidated in clinical practice; however, different studies observed increased risks of acute events for short-acting CCBs. This study aimed to provide real-world evidence on risks of acute cardiovascular (CV) events, hospitalizations and mortality among users of different CCB classes in secondary CV prevention.Three case-control studies were nested in a cohort of Italian elderly hypertensive CV-compromised CCBs users. Cases were subjects with CV events (n = 25,204), all-cause hospitalizations (n = 19,237), or all-cause mortality (n = 17,996) during the follow-up. Up to four controls were matched for each case. Current or past exposition to CCBs at index date was defined based on molecule, formulation and daily doses of the last CCB delivery. The odds ratio (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression models.Compared to past users, current CCB users had significant reductions in risks of CV events [OR 0.88 (95% CI: 0.84-0.91)], hospitalization [0.90 (0.88-0.93)] and mortality [0.48 (0.47-0.49)]. Current users of long-acting dihydropyridines (DHPs) had the lowest risk [OR 0.87 (0.84-0.90), 0.86 (0.83-0.90), 0.55 (0.54-0.56) for acute CV events, hospitalizations and mortality], whereas current users of short-acting CCBs had an increased risk of acute CV events [OR 1.77 (1.13-2.78) for short-acting DHPs; 1.19 (1.07-1.31) for short-acting non-DHPs] and hospitalizations [OR 1.84 (0.96-3.51) and 1.23 (1.08-1.42)].The already-existing warning on short-acting CCBs should be potentiated, addressing clinicians towards the choice of long-acting formulations.
