Survival and health economic outcomes in heart failure diagnosed at hospital admission versus community settings: a propensity-matched analysis

BACKGROUND AND AIMS: Most patients with heart failure (HF) are diagnosed following a hospital admission. The clinical and health economic impacts of index HF diagnosis made on admission to hospital versus community settings are not known. METHODS: We used the North West London Discover database to examine 34 208 patients receiving an index diagnosis of HF between January 2015 and December 2020. A propensity score-matched (PSM) cohort was identified to adjust for differences in socioeconomic status, cardiovascular risk and pre-diagnosis health resource utilisation cost. Outcomes were stratified by two pathways to index HF diagnosis: a 'hospital pathway' was defined by diagnosis following hospital admission; and a 'community pathway' by diagnosis via a general practitioner or outpatient services. The primary clinical and health economic endpoints were all-cause mortality and cost-consequence differential, respectively. RESULTS: The diagnosis of HF was via hospital pathway in 68% (23 273) of patients. The PSM cohort included 17 174 patients (8582 per group) and was matched across all selected confounders (p>0.05). The ratio of deaths per person-months at 24 months comparing community versus hospital diagnosis was 0.780 (95% CI 0.722 to 0.841, p<0.0001). By 72 months, the ratio of deaths was 0.960 (0.905 to 1.020, p=0.18). Diagnosis via hospital pathway incurred an overall extra longitudinal cost of £2485 per patient. CONCLUSIONS: Index diagnosis of HF through hospital admission continues to dominate and is associated with a significantly greater short-term risk of mortality and substantially increased long-term costs than if first diagnosed in the community. This study highlights the potential for community diagnosis-early, before symptoms necessitate hospitalisation-to improve both clinical and health economic outcomes

Sympathomimetic effects of chronic methamphetamine abuse on oral health: a cross-sectional study

Background: Methamphetamine, a highly addictive sympathomimetic stimulant, is currently widely abused worldwide and has been associated with devastating effects on oral health, resulting in the term "meth mouth". However, "meth mouth" pathology is primarily based on case reports with a lack of systematic clinical evaluation. Therefore, we have conducted a systematic study to investigate (1) the pharmacological impact of methamphetamine on oral health with regard to saliva function, including the parameters saliva flow rate and total saliva production (ml/5 min) and the buffering capacity of saliva;(2) the contribution of the symptoms of bruxism and muscle trismus to potential oral health damage. Methods: We assessed the data of 100 chronic methamphetamine abusers and 100 matched-pair comparison participants. Primarily, we conducted an anamnesis with all methamphetamine abusers with regard to saliva dysfunctions, jaw clenching and pain in the temporomandibular joint. Subsequently, in the first part of the clinical enquiry, we tested the saliva flow rate and the total saliva production (ml/5 min) by using the sialometry method and the buffer capacity of saliva by determining the pH-value. In the second part of the clinical enquiry, we evaluated bruxism symptoms with respect to generalized tooth attrition, dentine exposure and visible enamel cracks and examined a potential muscle trismus by measuring the maximal opening of the mouth. Results: The majority of methamphetamine abusers reported a dry mouth (72 %) and jaw clenching (68 %). Almost half of all methamphetamine abusers experienced pain in the temporomandibular joint (47 %). With regard to the clinical findings, methamphetamine abusers showed significantly lower total saliva production (ml/5 min) (p 0.05). Conclusions: The sympathomimetic effects of chronic methamphetamine abuse may lead to dry mouth and extensive bruxism and therefore can increase the risk for caries decay, periodontal lesions and tooth wear. Furthermore, a significant decline of saliva buffer capacity in methamphetamine abusers may trigger the risk for dental erosions. Methamphetamine abusers and practitioners should be aware of these symptoms

Crystal, Solution and In silico Structural Studies of Dihydrodipicolinate Synthase from the Common Grapevine

Dihydrodipicolinate synthase (DHDPS) catalyzes the rate limiting step in lysine biosynthesis in bacteria and plants. The structure of DHDPS has been determined from several bacterial species and shown in most cases to form a homotetramer or dimer of dimers. However, only one plant DHDPS structure has been determined to date from the wild tobacco species, Nicotiana sylvestris (Blickling et al. (1997) J. Mol. Biol. 274, 608–621). Whilst N. sylvestris DHDPS also forms a homotetramer, the plant enzyme adopts a ‘back-to-back’ dimer of dimers compared to the ‘head-to-head’ architecture observed for bacterial DHDPS tetramers. This raises the question of whether the alternative quaternary architecture observed for N. sylvestris DHDPS is common to all plant DHDPS enzymes. Here, we describe the structure of DHDPS from the grapevine plant, Vitis vinifera, and show using analytical ultracentrifugation, small-angle X-ray scattering and X-ray crystallography that V. vinifera DHDPS forms a ‘back-to-back’ homotetramer, consistent with N. sylvestris DHDPS. This study is the first to demonstrate using both crystal and solution state measurements that DHDPS from the grapevine plant adopts an alternative tetrameric architecture to the bacterial form, which is important for optimizing protein dynamics as suggested by molecular dynamics simulations reported in this study

Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study

BACKGROUND: Most patients who have heart failure with a reduced ejection fraction, when left ventricular ejection fraction (LVEF) is 40% or lower, are diagnosed in hospital. This is despite previous presentations to primary care with symptoms. We aimed to test an artificial intelligence (AI) algorithm applied to a single-lead ECG, recorded during ECG-enabled stethoscope examination, to validate a potential point-of-care screening tool for LVEF of 40% or lower. METHODS: We conducted an observational, prospective, multicentre study of a convolutional neural network (known as AI-ECG) that was previously validated for the detection of reduced LVEF using 12-lead ECG as input. We used AI-ECG retrained to interpret single-lead ECG input alone. Patients (aged ≥18 years) attending for transthoracic echocardiogram in London (UK) were recruited. All participants had 15 s of supine, single-lead ECG recorded at the four standard anatomical positions for cardiac auscultation, plus one handheld position, using an ECG-enabled stethoscope. Transthoracic echocardiogram-derived percentage LVEF was used as ground truth. The primary outcome was performance of AI-ECG at classifying reduced LVEF (LVEF ≤40%), measured using metrics including the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity, with two-sided 95% CIs. The primary outcome was reported for each position individually and with an optimal combination of AI-ECG outputs (interval range 0-1) from two positions using a rule-based approach and several classification models. This study is registered with ClinicalTrials.gov, NCT04601415. FINDINGS: Between Feb 6 and May 27, 2021, we recruited 1050 patients (mean age 62 years [SD 17·4], 535 [51%] male, 432 [41%] non-White). 945 (90%) had an ejection fraction of at least 40%, and 105 (10%) had an ejection fraction of 40% or lower. Across all positions, ECGs were most frequently of adequate quality for AI-ECG interpretation at the pulmonary position (979 [93·3%] of 1050). Quality was lowest for the aortic position (846 [80·6%]). AI-ECG performed best at the pulmonary valve position (p=0·02), with an AUROC of 0·85 (95% CI 0·81-0·89), sensitivity of 84·8% (76·2-91·3), and specificity of 69·5% (66·4-72·6). Diagnostic odds ratios did not differ by age, sex, or non-White ethnicity. Taking the optimal combination of two positions (pulmonary and handheld positions), the rule-based approach resulted in an AUROC of 0·85 (0·81-0·89), sensitivity of 82·7% (72·7-90·2), and specificity of 79·9% (77·0-82·6). Using AI-ECG outputs from these two positions, a weighted logistic regression with l2 regularisation resulted in an AUROC of 0·91 (0·88-0·95), sensitivity of 91·9% (78·1-98·3), and specificity of 80·2% (75·5-84·3). INTERPRETATION: A deep learning system applied to single-lead ECGs acquired during a routine examination with an ECG-enabled stethoscope can detect LVEF of 40% or lower. These findings highlight the potential for inexpensive, non-invasive, workflow-adapted, point-of-care screening, for earlier diagnosis and prognostically beneficial treatment. FUNDING: NHS Accelerated Access Collaborative, NHSX, and the National Institute for Health Research

Chemoproteomics-enabled covalent ligand screen reveals a cysteine hotspot in reticulon 4 that impairs ER morphology and cancer pathogenicity

Chemical genetics has arisen as a powerful approach for identifying novel anti-cancer agents. However, a major bottleneck of this approach is identifying the targets of lead compounds that arise from screens. Here, we coupled the synthesis and screening of fragment-based cysteine-reactive covalent ligands with activity-based protein profiling (ABPP) chemoproteomic approaches to identify compounds that impair colorectal cancer pathogenicity and map the druggable hotspots targeted by these hits. Through this coupled approach, we discovered a cysteine-reactive acrylamide DKM 3-30 that significantly impaired colorectal cancer cell pathogenicity through targeting C1101 on reticulon 4 (RTN4). While little is known about the role of RTN4 in colorectal cancer, this protein has been established as a critical mediator of endoplasmic reticulum tubular network formation. We show here that covalent modification of C1101 on RTN4 by DKM 3-30 or genetic knockdown of RTN4 impairs endoplasmic reticulum and nuclear envelope morphology as well as colorectal cancer pathogenicity. We thus put forth RTN4 as a potential novel colorectal cancer therapeutic target and reveal a unique druggable hotspot within RTN4 that can be targeted by covalent ligands to impair colorectal cancer pathogenicity. Our results underscore the utility of coupling the screening of fragment-based covalent ligands with isoTOP-ABPP platforms for mining the proteome for novel druggable nodes that can be targeted for cancer therapy