‘Caveat emptor’: the cautionary tale of endocarditis and the potential pitfalls of clinical coding data—an electronic health records study

Background Diagnostic codes from electronic health records are widely used to assess patterns of disease. Infective endocarditis is an uncommon but serious infection, with objective diagnostic criteria. Electronic health records have been used to explore the impact of changing guidance on antibiotic prophylaxis for dental procedures on incidence, but limited data on the accuracy of the diagnostic codes exists. Endocarditis was used as a clinically relevant case study to investigate the relationship between clinical cases and diagnostic codes, to understand discrepancies and to improve design of future studies. Methods Electronic health record data from two UK tertiary care centres were linked with data from a prospectively collected clinical endocarditis service database (Leeds Teaching Hospital) or retrospective clinical audit and microbiology laboratory blood culture results (Oxford University Hospitals Trust). The relationship between diagnostic codes for endocarditis and confirmed clinical cases according to the objective Duke criteria was assessed, and impact on estimations of disease incidence and trends. Results In Leeds 2006–2016, 738/1681(44%) admissions containing any endocarditis code represented a definite/possible case, whilst 263/1001(24%) definite/possible endocarditis cases had no endocarditis code assigned. In Oxford 2010–2016, 307/552(56%) reviewed endocarditis-coded admissions represented a clinical case. Diagnostic codes used by most endocarditis studies had good positive predictive value (PPV) but low sensitivity (e.g. I33-primary 82% and 43% respectively); one (I38-secondary) had PPV under 6%. Estimating endocarditis incidence using raw admission data overestimated incidence trends twofold. Removing records with non-specific codes, very short stays and readmissions improved predictive ability. Estimating incidence of streptococcal endocarditis using secondary codes also overestimated increases in incidence over time. Reasons for discrepancies included changes in coding behaviour over time, and coding guidance allowing assignment of a code mentioning ‘endocarditis’ where endocarditis was never mentioned in the clinical notes. Conclusions Commonly used diagnostic codes in studies of endocarditis had good predictive ability. Other apparently plausible codes were poorly predictive. Use of diagnostic codes without examining sensitivity and predictive ability can give inaccurate estimations of incidence and trends. Similar considerations may apply to other diseases. Health record studies require validation of diagnostic codes and careful data curation to minimise risk of serious errors

Mouse DRG Cell Line with Properties of Nociceptors

In vitro cell lines from DRG neurons aid drug discovery because they can be used for early stage, high-throughput screens for drugs targeting pain pathways, with minimal dependence on animals. We have established a conditionally immortal DRG cell line from the Immortomouse. Using immunocytochemistry, RT-PCR and calcium microfluorimetry, we demonstrate that the cell line MED17.11 expresses markers of cells committed to the sensory neuron lineage. Within a few hours under differentiating conditions, MED17.11 cells extend processes and following seven days of differentiation, express markers of more mature DRG neurons, such as NaV1.7 and Piezo2. However, at least at this time-point, the nociceptive marker NaV1.8 is not expressed, but the cells respond to compounds known to excite nociceptors, including the TRPV1 agonist capsaicin, the purinergic receptor agonist ATP and the voltage gated sodium channel agonist, veratridine. Robust calcium transients are observed in the presence of the inflammatory mediators bradykinin, histamine and norepinephrine. MED17.11 cells have the potential to replace or reduce the use of primary DRG culture in sensory, pain and developmental research by providing a simple model to study acute nociception, neurite outgrowth and the developmental specification of DRG neurons

Identification and structural analysis of the tripartite α-pore forming toxin of Aeromonas hydrophila

The alpha helical CytolysinA family of pore forming toxins (α-PFT) contains single, two, and three component members. Structures of the single component Eschericia coli ClyA and the two component Yersinia enterolytica YaxAB show both undergo conformational changes from soluble to pore forms, and oligomerization to produce the active pore. Here we identify tripartite α-PFTs in pathogenic Gram negative bacteria, including Aeromonas hydrophila (AhlABC). We show that the AhlABC toxin requires all three components for maximal cell lysis. We present structures of pore components which describe a bi-fold hinge mechanism for soluble to pore transition in AhlB and a contrasting tetrameric assembly employed by soluble AhlC to hide their hydrophobic membrane associated residues. We propose a model of pore assembly where the AhlC tetramer dissociates, binds a single membrane leaflet, recruits AhlB promoting soluble to pore transition, prior to AhlA binding to form the active hydrophilic lined pore