Handwork vs machine: a comparison of rheumatoid arthritis patient populations as identified from EHR free-text by diagnosis extraction through machine-learning or traditional criteria-based chart review

Background Electronic health records (EHRs) offer a wealth of observational data. Machine-learning (ML) methods are efficient at data extraction, capable of processing the information-rich free-text physician notes in EHRs. The clinical diagnosis contained therein represents physician expert opinion and is more consistently recorded than classification criteria components. Objectives To investigate the overlap and differences between rheumatoid arthritis patients as identified either from EHR free-text through the extraction of the rheumatologist diagnosis using machine-learning (ML) or through manual chart-review applying the 1987 and 2010 RA classification criteria. Methods Since EHR initiation, 17,662 patients have visited the Leiden rheumatology outpatient clinic. For ML, we used a support vector machine (SVM) model to identify those who were diagnosed with RA by their rheumatologist. We trained and validated the model on a random selection of 2000 patients, balancing PPV and sensitivity to define a cutoff, and assessed performance on a separate 1000 patients. We then deployed the model on our entire patient selection (including the 3000). Of those, 1127 patients had both a 1987 and 2010 EULAR/ACR criteria status at 1 year after inclusion into the local prospective arthritis cohort. In these 1127 patients, we compared the patient characteristics of RA cases identified with ML and those fulfilling the classification criteria. Results The ML model performed very well in the independent test set (sensitivity=0.85, specificity=0.99, PPV=0.86, NPV=0.99). In our selection of patients with both EHR and classification information, 373 were recognized as RA by ML and 357 and 426 fulfilled the 1987 or 2010 criteria, respectively. Eighty percent of the ML-identified cases fulfilled at least one of the criteria sets. Both demographic and clinical parameters did not differ between the ML extracted cases and those identified with EULAR/ACR classification criteria. Conclusions With ML methods, we enable fast patient extraction from the huge EHR resource. Our ML algorithm accurately identifies patients diagnosed with RA by their rheumatologist. This resulting group of RA patients had a strong overlap with patients identified using the 1987 or 2010 classification criteria and the baseline (disease) characteristics were comparable. ML-assisted case labeling enables high-throughput creation of inclusive patient selections for research purposes.Pathophysiology and treatment of rheumatic disease

Validating ATLAS: A regional-scale high-throughput tracking system

Fine-scale tracking of animal movement is important to understand the proximate mechanisms of animal behaviour. The reverse-GPS system—ATLAS—uses inexpensive (~€25), lightweight (90% at 15 of 16 stationary sites. Tags on birds (1/6 Hz) on the Griend mudflat had a mean fix rate of 51%, yielding an average sampling rate of 0.085 Hz. Fix rates were higher in more central parts of the receiver array. ATLAS provides accurate, regional-scale tracking with which hundreds of relatively small-bodied species can be tracked simultaneously for long periods of time. Future ATLAS users should consider the height of receivers, their spatial arrangement, density and the movement modes of their study species (e.g. ground-dwelling or flying)

Molecular characterization of MRSA collected during national surveillance between 2008 and 2019 in the Netherlands

Background.Although the Netherlands is a country with a low endemic level, methicillin-resistant Staphylococcus aureus (MRSA) poses a significant health care problem. Therefore, high coverage national MRSA surveillance has been in place since 1989. To monitor possible changes in the type-distribution and emergence of resistance and virulence, MRSA isolates are molecularly characterized.Methods.All 43,321 isolates from 36,520 persons, collected 2008–2019, were typed by multiple-locus variable number tandem repeats analysis (MLVA) with simultaneous PCR detection of the mecA, mecC and lukF-PV genes, indicative for PVL. Next-generation sequencing data of 4991 isolates from 4798 persons were used for whole genome multi-locus sequence typing (wgMLST) and identification of resistance and virulence genes.Results.We show temporal change in the molecular characteristics of the MRSA population with the proportion of PVL-positive isolates increasing from 15% in 2008–2010 to 25% in 2017–2019. In livestock-associated MRSA obtained from humans, PVL-positivity increases to 6% in 2017–2019 with isolates predominantly from regions with few pig farms. wgMLST reveals the presence of 35 genogroups with distinct resistance, virulence gene profiles and specimen origin. Typing shows prolonged persistent MRSA carriage with a mean carriage period of 407 days. There is a clear spatial and a weak temporal relationship between isolates that clustered in wgMLST, indicative for regional spread of MRSA strains.Conclusions.Using molecular characterization, this exceptionally large study shows genomic changes in the MRSA population at the national level. It reveals waxing and waning of types and genogroups and an increasing proportion of PVL-positive MRSA

WATLAS: high-throughput and real-time tracking of many small birds in the Dutch Wadden Sea

Tracking animal movement is important for understanding how animals interact with their (changing) environment, and crucial for predicting and explaining how animals are affected by anthropogenic activities. The Wadden Sea is a UNESCO World Heritage Site and a region of global importance for millions of shorebirds. Due to climate change and anthropogenic activity, understanding and predicting movement and space-use in areas like the Wadden Sea is increasingly important. Monitoring and predicting animal movement, however, requires high-resolution tracking of many individuals. While high-resolution tracking has been made possible through GPS, trade-offs between tag weight and battery life limit its use to larger species. Here, we introduce WATLAS (the Wadden Sea deployment of the ATLAS tracking system) capable of monitoring the movements of hundreds of (small) birds simultaneously in the Dutch Wadden Sea. WATLAS employs an array of receiver stations that can detect and localize small, low-cost tags at fine spatial (metres) and temporal resolution (seconds). From 2017 to 2021, we tracked red knots, sanderlings, bar-tailed godwits, and common terns. We use parts of these data to give four use-cases revealing its performance and demonstrating how WATLAS can be used to study numerous aspects of animal behaviour, such as, space-use (both intra- and inter-specific), among-individual variation, and social networks across levels of organization: from individuals, to species, to populations, and even communities. After describing the WATLAS system, we first illustrate space-use of red knots across the study area and how the tidal environment affects their movement. Secondly, we show large among-individual differences in distances travelled per day, and thirdly illustrate how high-throughput WATLAS data allows calculating a proximity-based social network. Finally, we demonstrate that using WATLAS to monitor multiple species can reveal differential space use. For example, despite sanderlings and red knots roosting together, they foraged in different areas of the mudflats. The high-resolution tracking data collected by WATLAS offers many possibilities for research into the drivers of bird movement in the Wadden Sea. WATLAS could provide a tool for impact assessment, and thus aid nature conservation and management of the globally important Wadden Sea ecosystem

Molecular characterization of MRSA collected during national surveillance between 2008 and 2019 in the Netherlands

Background.Although the Netherlands is a country with a low endemic level, methicillin-resistant Staphylococcus aureus (MRSA) poses a significant health care problem. Therefore, high coverage national MRSA surveillance has been in place since 1989. To monitor possible changes in the type-distribution and emergence of resistance and virulence, MRSA isolates are molecularly characterized.Methods.All 43,321 isolates from 36,520 persons, collected 2008-2019, were typed by multiple-locus variable number tandem repeats analysis (MLVA) with simultaneous PCR detection of the mecA, mecC and lukF-PV genes, indicative for PVL. Next-generation sequencing data of 4991 isolates from 4798 persons were used for whole genome multi-locus sequence typing (wgMLST) and identification of resistance and virulence genes.Results.We show temporal change in the molecular characteristics of the MRSA population with the proportion of PVL-positive isolates increasing from 15% in 2008-2010 to 25% in 2017-2019. In livestock-associated MRSA obtained from humans, PVL-positivity increases to 6% in 2017-2019 with isolates predominantly from regions with few pig farms. wgMLST reveals the presence of 35 genogroups with distinct resistance, virulence gene profiles and specimen origin. Typing shows prolonged persistent MRSA carriage with a mean carriage period of 407 days. There is a clear spatial and a weak temporal relationship between isolates that clustered in wgMLST, indicative for regional spread of MRSA strains.Conclusions.Using molecular characterization, this exceptionally large study shows genomic changes in the MRSA population at the national level. It reveals waxing and waning of types and genogroups and an increasing proportion of PVL-positive MRSA.A group of bacteria that cause difficult-to-treat infections in humans is methicillin-resistant Staphylococcus aureus (MRSA). The aim of this study was to monitor changes in the spread of MRSA, their disease causing potential and resistance to antibiotics used to treat MRSA infections. MRSA from patients and their contacts in the Netherlands were collected over a period of 12 years and characterized. This revealed new types of MRSA emerged and others disappeared. An increasing number of MRSA produces a protein called PVL toxin, enabling MRSA to cause more severe infections. Also, some people appear to carry MRSA without any disease for more than a year. These findings suggest an increasing disease potential of MRSA and possible unnoticed sources of infection. Consequently, it is important to maintain monitoring of these infections to minimize MRSA spread.Schouls et al. characterize 43,321 methicillin-resistant Staphylococcus aureus (MRSA) isolates obtained between 2008 and 2019 in the Netherlands. Genomic changes occur in the MRSA population, with increases in the proportion of PVL-positive MRSA.Molecular basis of bacterial pathogenesis, virulence factors and antibiotic resistanc

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

Treatment-associated polymorphisms in protease are significantly associated with higher viral load and lower CD4 count in newly diagnosed drug-naive HIV-1 infected patients

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