Combined effect of CYP2C19 and CYP2D6 genotypes on escitalopram serum concentration and its metabolic ratio in a European patient population.

AIMS: The aim of the present study was to investigate the impact of CYP2D6 genotype on exposure and metabolism of escitalopram in patients stratified by CYP2C19 genotype in a large real-world population. METHODS: Patients were included from a therapeutic drug monitoring service if they had measured serum concentration of escitalopram and the metabolite, N-desmethyl escitalopram, and performed CYP2C19 and CYP2D6 genotyping. Patients were divided into 16 combined genotype-predicted phenotype subgroups (poor [PM], intermediate [IM], normal [NM] and ultrarapid metabolizers [UM]) of CYP2C19/CYP2D6. The concentration-to-dose (CD) ratio and metabolite-to-parent ratio (metabolic ratio) of escitalopram were compared across subgroups using the Kruskal-Wallis test followed by Dunn's test with CYP2D6 NMs as the reference group. RESULTS: A total of 5067 patients were included in the study. A stepwise increase in escitalopram CD ratio by decreasing CYP2D6 activity was observed in all CYP2C19 subgroups, except for in CYP2C19 UMs. The percentage differences in escitalopram CD ratio between CYP2D6 PMs and NMs were 24% in CYP2C19 NMs (P < .001), 28% in CYP2C19 IMs (P < .001) and 31% in CYP2C19 PMs (P = .04). As for the CD ratio, CYP2D6 genotype effect on metabolic ratio increased stepwise by decreasing CYP2C19 metabolism. CONCLUSIONS: CYP2D6 genotype is of significant importance for the individual variation in escitalopram pharmacokinetics. The most relevant increase in escitalopram concentration is seen in individuals with decreased and/or absent CYP2C19 activity. By combining CYP2C19 and CYP2D6 genotypes, the optimal dose for patients may be predicted with greater precision than for CYP2C19 genotype alone.

A Rapid Assay for SARS-CoV-2 Neutralizing Antibodies That Is Insensitive to Antiretroviral Drugs.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike pseudotyped virus (PSV) assays are widely used to measure neutralization titers of sera and of isolated neutralizing Abs (nAbs). PSV neutralization assays are safer than live virus neutralization assays and do not require access to biosafety level 3 laboratories. However, many PSV assays are nevertheless somewhat challenging and require at least 2 d to carry out. In this study, we report a rapid (<30 min), sensitive, cell-free, off-the-shelf, and accurate assay for receptor binding domain nAb detection. Our proximity-based luciferase assay takes advantage of the fact that the most potent SARS-CoV-2 nAbs function by blocking the binding between SARS-CoV-2 and angiotensin-converting enzyme 2. The method was validated using isolated nAbs and sera from spike-immunized animals and patients with coronavirus disease 2019. The method was particularly useful in patients with HIV taking antiretroviral therapies that interfere with the conventional PSV assay. The method provides a cost-effective and point-of-care alternative to evaluate the potency and breadth of the predominant SARS-CoV-2 nAbs elicited by infection or vaccines.

B cells expressing authentic naive human VRC01-class BCRs can be recruited to germinal centers and affinity mature in multiple independent mouse models.

Animal models of human antigen-specific B cell receptors (BCRs) generally depend on "inferred germline" sequences, and thus their relationship to authentic naive human B cell BCR sequences and affinities is unclear. Here, BCR sequences from authentic naive human VRC01-class B cells from healthy human donors were selected for the generation of three BCR knockin mice. The BCRs span the physiological range of affinities found in humans, and use three different light chains (VK3-20, VK1-5, and VK1-33) found among subclasses of naive human VRC01-class B cells and HIV broadly neutralizing antibodies (bnAbs). The germline-targeting HIV immunogen eOD-GT8 60mer is currently in clinical trial as a candidate bnAb vaccine priming immunogen. To attempt to model human immune responses to the eOD-GT8 60mer, we tested each authentic naive human VRC01-class BCR mouse model under rare human physiological B cell precursor frequency conditions. B cells with high (HuGL18HL) or medium (HuGL17HL) affinity BCRs were primed, recruited to germinal centers, and they affinity matured, and formed memory B cells. Precursor frequency and affinity interdependently influenced responses. Taken together, these experiments utilizing authentic naive human VRC01-class BCRs validate a central tenet of germline-targeting vaccine design and extend the overall concept of the reverse vaccinology approach to vaccine development.

Effectiveness of a Videoconferencing-Delivered Psychological Intervention for Mental Health Problems during COVID-19: A Proof-of-Concept Randomized Clinical Trial.

INTRODUCTION: Anxiety and depression have increased markedly during the COVID-19 pandemic. There is a lack of evidence-based strategies to address these mental health needs during the pandemic. OBJECTIVE: We aim to conduct a proof-of-concept trial of the efficacy of a brief group-based psychological intervention delivered via videoconferencing for adults in Australia distressed by the pandemic. METHODS: In this single-blind, parallel, randomised controlled trial, adults who screened positive for COVID-related psychological distress across Australia were randomly allocated to either a 6-session group-based program based on behavioural principles (n = 120) or enhanced usual care (EUC, n = 120). Primary outcome was total score on the Hospital Anxiety and Depression (HADS) anxiety and depression subscales assessed at baseline, 1 week posttreatment, 2 months (primary outcome time point), and 6 months after treatment, as well as secondary outcome measures of worry, sleep impairment, anhedonia, mood, and COVID-19-related stress. RESULTS: Between May 20, 2020, and October 20, 2020, 240 patients were enrolled into the trial. Relative to EUC, at 2 months participants receiving intervention showed greater reduction on anxiety (mean difference, 1.4 [95% CI, 0.3 to 2.6], p = 0.01; effect size, 0.4 [95% CI, 0.1 to 0.7]) and depression (mean difference, 1.6 [95% CI, 0.4 to 2.8], p = 0.009; effect size, 0.4 [95% CI, 0.2 to 0.7]) scales. These effects were maintained at 6 months. There were also greater reductions of worry, anhedonia, COVID-19-related fears, and contamination fears. CONCLUSIONS: This trial provides initial evidence that brief group-based behavioural intervention delivered via videoconferencing results in moderate reductions in common psychological problems arising during the COVID-19 pandemic. This program may offer a viable and scalable means to mitigate the rising mental health problems during the pandemic.

Neural processes during response inhibition in complex posttraumatic stress disorder.

BACKGROUND: A common feature of complex posttraumatic stress disorder (CPTSD) is impulsivity. Despite the importance of this characteristic in functional difficulties in CPTSD, little is known about its mechanisms. The aim of this study was to identify the distinctive neural profile of CPTSD during attempted inhibition. METHODS: The present study examined functional alterations in neural networks involved in inhibitory control across functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) paradigms in CPTSD (n = 30), PTSD (n = 40), and healthy control (n = 40) participants who completed a Go/NoGo response inhibition task during separate fMRI and EEG sessions. Brain activations were calculated during the NoGo trials relative to the baseline to evaluate response inhibition functioning. RESULTS: There was reduced bilateral thalamic activation in participants with CPTSD relative to PTSD and controls during inhibition trials, but no activation differences between PTSD and controls for this brain region. There were no differences in functional connectivity between the thalamus and other regions involved in cognitive control between groups. No differences were observed between groups on EEG responses. CONCLUSIONS: These findings provide initial evidence of aberrant functioning in the neurocircuitry of inhibitory control, involving the thalamus, in CPTSD. This evidence suggests that CPTSD is distinguished from PTSD by impaired neural processes implicated in response inhibition.

Multi-morbidity and blood pressure trajectories in hypertensive patients: A multiple landmark cohort study.

BACKGROUND: Our knowledge of how to better manage elevated blood pressure (BP) in the presence of comorbidities is limited, in part due to exclusion or underrepresentation of patients with multiple chronic conditions from major clinical trials. We aimed to investigate the burden and types of comorbidities in patients with hypertension and to assess how such comorbidities and other variables affect BP levels over time. METHODS AND FINDINGS: In this multiple landmark cohort study, we used linked electronic health records from the United Kingdom Clinical Practice Research Datalink (CPRD) to compare systolic blood pressure (SBP) levels in 295,487 patients (51% women) aged 61.5 (SD = 13.1) years with first recorded diagnosis of hypertension between 2000 and 2014, by type and numbers of major comorbidities, from at least 5 years before and up to 10 years after hypertension diagnosis. Time-updated multivariable linear regression analyses showed that the presence of more comorbidities was associated with lower SBP during follow-up. In hypertensive patients without comorbidities, mean SBP at diagnosis and at 10 years were 162.3 mm Hg (95% confidence interval [CI] 162.0 to 162.6) and 140.5 mm Hg (95% CI 140.4 to 140.6), respectively; in hypertensive patients with ≥5 comorbidities, these were 157.3 mm Hg (95% CI 156.9 to 157.6) and 136.8 mm Hg (95% 136.4 to 137.3), respectively. This inverse association between numbers of comorbidities and SBP was not specific to particular types of comorbidities, although associations were stronger in those with preexisting cardiovascular disease. Retrospective analysis of recorded SBP showed that the difference in mean SBP 5 years before diagnosis between those without and with ≥5 comorbidities was -9 mm Hg (95% CI -9.7 to -8.3), suggesting that mean recorded SBP already differed according to the presence of comorbidity before baseline. Within 1 year after the diagnosis, SBP substantially declined, but subsequent SBP changes across comorbidity status were modest, with no evidence of a more rapid decline in those with more or specific types of comorbidities. We identified factors, such as prescriptions of antihypertensive drugs and frequency of healthcare visits, that can explain SBP differences according to numbers or types of comorbidities, but these factors only partly explained the recorded SBP differences. Nevertheless, some limitations have to be considered including the possibility that diagnosis of some conditions may not have been recorded, varying degrees of missing data inherent in analytical datasets extracted from routine health records, and greater measurement errors in clinical measurements taken in routine practices than those taken in well-controlled clinical study settings. CONCLUSIONS: BP levels at which patients were diagnosed with hypertension varied substantially according to the presence of comorbidities and were lowest in patients with multi-morbidity. Our findings suggest that this early selection bias of hypertension diagnosis at different BP levels was a key determinant of long-term differences in BP by comorbidity status. The lack of a more rapid decline in SBP in those with multi-morbidity provides some reassurance for BP treatment in these high-risk individuals.

Association between cardiometabolic disease multimorbidity and all-cause mortality in 2 million women and men registered in UK general practices.

BACKGROUND: Myocardial infarction (MI), stroke and diabetes share underlying risk factors and commonalities in clinical management. We examined if their combined impact on mortality is proportional, amplified or less than the expected risk separately of each disease and whether the excess risk is explained by their associated comorbidities. METHODS: Using large-scale electronic health records, we identified 2,007,731 eligible patients (51% women) and registered with general practices in the UK and extracted clinical information including diagnosis of myocardial infarction (MI), stroke, diabetes and 53 other long-term conditions before 2005 (study baseline). We used Cox regression to determine the risk of all-cause mortality with age as the underlying time variable and tested for excess risk due to interaction between cardiometabolic conditions. RESULTS: At baseline, the mean age was 51 years, and 7% (N = 145,910) have had a cardiometabolic condition. After a 7-year mean follow-up, 146,994 died. The sex-adjusted hazard ratios (HR) (95% confidence interval [CI]) of all-cause mortality by baseline disease status, compared to those without cardiometabolic disease, were MI = 1.51 (1.49-1.52), diabetes = 1.52 (1.51-1.53), stroke = 1.84 (1.82-1.86), MI and diabetes = 2.14 (2.11-2.17), MI and stroke = 2.35 (2.30-2.39), diabetes and stroke = 2.53 (2.50-2.57) and all three = 3.22 (3.15-3.30). Adjusting for other concurrent comorbidities attenuated these estimates, including the risk associated with having all three conditions (HR = 1.81 [95% CI 1.74-1.89]). Excess risks due to interaction between cardiometabolic conditions, particularly when all three conditions were present, were not significantly greater than expected from the individual disease effects. CONCLUSION: Myocardial infarction, stroke and diabetes were associated with excess mortality, without evidence of any amplification of risk in people with all three diseases. The presence of other comorbidities substantially contributed to the excess mortality risks associated with cardiometabolic disease multimorbidity.

Commercial Serology Assays Predict Neutralization Activity against SARS-CoV-2.

BACKGROUND: It is unknown whether a positive serology result correlates with protective immunity against SARS-CoV-2. There are also concerns regarding the low positive predictive value of SARS-CoV-2 serology tests, especially when testing populations with low disease prevalence. METHODS: A neutralization assay was validated in a set of PCR-confirmed positive specimens and in a negative cohort. In addition, 9530 specimens were screened using the Diazyme SARS-CoV-2 IgG serology assay and all positive results (N = 164 individuals) were reanalyzed using the neutralization assay, the Roche total immunoglobin assay, and the Abbott IgG assay. The relationship between the magnitude of a positive SARS-CoV-2 serology result and neutralizing activity was determined. Neutralizing antibody titers (50% inhibitory dilution, ID50) were also longitudinally monitored in patients confirmed to have SARS-CoV-2 by PCR. RESULTS: The SARS-CoV-2 neutralization assay had a positive percentage agreement (PPA) of 96.6% with a SARS-CoV-2 PCR test and a negative percentage agreement (NPA) of 98.0% across 100 negative control individuals. ID50 neutralization titers positively correlated with all 3 clinical serology platforms. Longitudinal monitoring of hospitalized PCR-confirmed patients with COVID-19 demonstrated they made high neutralization titers against SARS-CoV-2. PPA between the Diazyme IgG assay alone and the neutralization assay was 50.6%, while combining the Diazyme IgG assay with either the Roche or Abbott platforms increased the PPA to 79.2 and 78.4%, respectively. CONCLUSIONS: These 3 clinical serology assays positively correlate with SARS-CoV-2 neutralization activity observed in patients with COVID-19. All patients confirmed SARS-CoV-2 positive by PCR develop neutralizing antibodies.

Two-year follow-up of trauma-focused cognitive behavior therapy for posttraumatic stress disorder in emergency service personnel: A randomized clinical trial.

BACKGROUND: Emergency service personnel experience elevated rates of posttraumatic stress disorder (PTSD). There are few controlled trials for PTSD in this population, and none report longer term effects of treatment. This study evaluated the benefits of cognitive behavior therapy (CBT) for PTSD in emergency service personnel who received either brief exposure (CBT-B) to trauma memories or prolonged exposure (CBT-L) 2 years following treatment. METHODS: One hundred emergency service personnel with PTSD were randomized to CBT-L, CBT-B, or Wait-List (WL). Following posttreatment assessment, WL participants were randomized to an active treatment. Participants randomized to CBT-L or CBT-B were assessed at baseline, posttreatment, 6-month, and 2-year follow-up. Both CBT conditions involved 12 weekly individual sessions comprising education, CBT skills building, imaginal exposure, in vivo exposure, cognitive restructuring, and relapse prevention. Reliving trauma memories occurred for 40 min per session in CBT-L and for 10 min in CBT-B. RESULTS: At the 2-year follow-up, there were no differences in PTSD severity (Clinician Administered PTSD Scale) between CBT-L and CBT-B. There were very large effect sizes for CBT-L (1.28, 95% confidence interval [CI] = 0.90-1.64) and CBT-B (1.28, 95% CI = 0.05-1.63) from baseline to 2-year follow-up. CONCLUSIONS: This study highlights that CBT can be an effective treatment of PTSD in emergency service personnel using either prolonged or brief periods of reliving the trauma memory, and that these benefits can last for at least 2 years after treatment.

Brief videoconferencing psychological intervention for reducing COVID-19 related distress: study protocol for a randomized controlled trial.

BACKGROUND: Globally COVID-19 has had a profound impact on the psychological wellbeing of millions of people, and there is an urgent imperative to address elevated levels of distress during the COVID-19 pandemic. The World Health Organization (WHO) has developed Problem Management Plus (PM+), a low intensity psychological intervention for adults experiencing psychological distress. This paper outlines the study protocol for a trial that tests the effectiveness of an adapted version of PM+ to reduce distress associated with COVID-19. METHODS: A single-blind, parallel, randomized controlled trial will be carried out for distressed people across Australia. via video conferencing on a small group basis. Following informed consent, adults that screen positive for levels of psychological distress (General Health Questionnaire-12 (GHQ-12 score ≥ 3) and have access to videoconferencing platform will be randomised to an adapted version of gPM+ (n = 120) or enhanced treatment as usual (ETAU) (n = 120). The primary outcome will be reduction in psychological distress including anxiety and depression at 2-months post treatment. Secondary outcomes include worry, sleep problems, anhedonia, social support, and stress in relation to COVID-19. DISCUSSION: The trial aims assess whether an adapted version of videoconferencing PM+ that is specifically designed to target COVI-19 related distress will result in reduced distress relative to enhanced usual care. TRIAL REGISTRATION: This trial was prospectively registered on the ANZCTR on 14/4/20 ( ACTRN12620000468921 ).

Poisonings by substances of abuse at the Oslo Accident and Emergency Outpatient Clinic 2014-18. / Rusrelaterte forgiftninger ved Legevakten i Oslo i 2014­18.

BACKGROUND: Poisonings by substances of abuse are potentially dangerous and indicate risky substance use behaviour. To be prepared to handle patients with poisonings by substances of abuse, we need updated knowledge about the kinds of substances we can be expected to encounter. Most substance use-related poisonings in Oslo are treated at the OAEOC, and we describe the poisonings observed there in the period 2014-2018. MATERIAL AND METHOD: We included all patients treated for poisoning by substances of abuse at the OAEOC in the years 2014-18, with the exception of lone ethanol poisonings. For 2018, these were also included. The patients were identified retrospectively by a review of the patient registration lists in the clinic's electronic records system. The diagnosis of the substances involved was based on the clinical assessment made by the doctor responsible for treatment. RESULTS: In the period 2014-18, altogether 8 116 cases of poisoning by a substance of abuse were treated at OAEOC, lone ethanol poisonings not included. The most frequently occurring intoxicants were heroin (3 237 cases), benzodiazepines (2 196), amphetamine/methamphetamine (1 827), cannabis (1 081), gamma-hydroxybutyrate (GHB) (904), cocaine (569) and unspecified opioids (546). There was an increasing trend in number of cases per year for central stimulants, cannabis and GHB, and a decreasing one for benzodiazepines. The number of heroin poisonings fell until 2017, but rose again in 2018. In 2018 there were 4 021 poisonings by substances of abuse, of which 2 022 were lone ethanol poisonings. INTERPRETATION: The number of poisonings increased for most substances in 2014-18, but fell for heroin and benzodiazepines.

Deep learning for electronic health records: A comparative review of multiple deep neural architectures.

Despite the recent developments in deep learning models, their applications in clinical decision-support systems have been very limited. Recent digitalisation of health records, however, has provided a great platform for the assessment of the usability of such techniques in healthcare. As a result, the field is starting to see a growing number of research papers that employ deep learning on electronic health records (EHR) for personalised prediction of risks and health trajectories. While this can be a promising trend, vast paper-to-paper variability (from data sources and models they use to the clinical questions they attempt to answer) have hampered the field's ability to simply compare and contrast such models for a given application of interest. Thus, in this paper, we aim to provide a comparative review of the key deep learning architectures that have been applied to EHR data. Furthermore, we also aim to: (1) introduce and use one of the world's largest and most complex linked primary care EHR datasets (i.e., Clinical Practice Research Datalink, or CPRD) as a new asset for training such data-hungry models; (2) provide a guideline for working with EHR data for deep learning; (3) share some of the best practices for assessing the "goodness" of deep-learning models in clinical risk prediction; (4) and propose future research ideas for making deep learning models more suitable for the EHR data. Our results highlight the difficulties of working with highly imbalanced datasets, and show that sequential deep learning architectures such as RNN may be more suitable to deal with the temporal nature of EHR.

Platelet microRNA expression and association with platelet maturity and function in patients with essential thrombocythemia.

Essential thrombocythemia (ET) is characterized by persistently elevated platelet counts and an increased risk of thromboembolic events. Dysregulated expression of small noncoding microRNAs (miRNAs) have been shown in ET and may influence platelet maturity and function in ET patients. In this study, we included 22 ET patients and 19 healthy controls to investigate the expression of 12 platelet miRNAs previously reported to be dysregulated in ET. Further, we investigated the correlation between the expression of selected miRNAs and platelet maturity and platelet function. Total RNA was isolated from platelets, and expression analyses were performed using TaqMan quantitative PCR (qPCR). Mean platelet volume (MPV) and immature platelet count and -fraction (IPC and IPF) were measured using the Sysmex XE-5000 automated haematology system. Platelet function was investigated by multiple electrode aggregometry (agonists: arachidonic acid (AA), thrombin-receptor-activating-peptide (TRAP) and adenosine diphosphate (ADP)), while platelet activation was determined by multi-colour flow cytometry (antibodies: bound-fibrinogen, CD63 and P-selectin (CD62p), agonists: AA, TRAP and ADP). We showed that miR-9 and miR-490 were significantly upregulated in ET patients compared with healthy controls (p-values < 0.01), while miR-10a, miR-28, miR-126, miR-155, miR-221, miR-222, miR-223 and miR-431 were significantly downregulated in ET patients (all p-values < 0.001). A significant positive correlation was observed between miR-431 and MPV, IPC and IPF (all p-values < 0.05). The expression of miR-126 was negatively correlated with platelet aggregation induced by AA and TRAP (p < 0.05). In addition, we found the expression of miR-9 and miR-490 to be negatively correlated with the percentage of fibrinogen-, CD63- and P-selectin- positive platelets using TRAP as agonist (p < 0.05). In conclusion, our data indicate that platelet microRNAs may play a role in ET and that specific microRNAs are correlated with platelet maturity and platelet function.

Diagnostic tests, drug prescriptions, and follow-up patterns after incident heart failure: A cohort study of 93,000 UK patients.

BACKGROUND: Effective management of heart failure is complex, and ensuring evidence-based practice presents a major challenge to health services worldwide. Over the past decade, the United Kingdom introduced a series of national initiatives to improve evidence-based heart failure management, including a landmark pay-for-performance scheme in primary care and a national audit in secondary care started in 2004 and 2007, respectively. Quality improvement efforts have been evaluated within individual clinical settings, but patterns of care across its continuum, although a critical component of chronic disease management, have not been studied. We have designed this study to investigate patients' trajectories of care around the time of diagnosis and their variation over time by age, sex, and socioeconomic status. METHODS AND FINDINGS: For this retrospective population-based study, we used linked primary and secondary health records from a representative sample of the UK population provided by the Clinical Practice Research Datalink (CPRD). We identified 93,074 individuals newly diagnosed with heart failure between 2002 and 2014, with a mean age of 76.7 years and of which 49% were women. We examined five indicators of care: (i) diagnosis care setting (inpatient or outpatient), (ii) posthospitalisation follow-up in primary care, (iii) diagnostic investigations, (iv) prescription of essential drugs, and (v) drug treatment dose. We used Poisson and linear regression models to calculate category-specific risk ratios (RRs) or adjusted differences and 95% confidence intervals (CIs), adjusting for year of diagnosis, age, sex, region, and socioeconomic status. From 2002 to 2014, indicators of care presented diverging trends. Outpatient diagnoses and follow-up after hospital discharge in primary care declined substantially (ranging from 56% in 2002 to 36% in 2014, RR 0.64 [0.62, 0.67] and 20% to 14%, RR 0.73 [0.65, 0.82], respectively). Primary care referral for diagnostic investigations and appropriate initiation of beta blockers and angiotensin-converting-enzyme inhibitors (ACE-Is) or angiotensin receptor blockers (ARBs) both increased significantly (37% versus 82%, RR 2.24 [2.15, 2.34] and 18% versus 63%, RR 3.48 [2.72, 4.43], respectively). Yet, the average daily dose prescribed remained below guideline recommendations (42% for ACE-Is or ARBs, 29% for beta blockers in 2014) and was largely unchanged beyond the first 30 days after diagnosis. Despite increasing rates of treatment initiation, the overall dose prescribed to patients in the 12 months following diagnosis improved little over the period of study (adjusted difference for the combined dose of beta blocker and ACE-I or ARB: +6% [+2%, +10%]). Women and patients aged over 75 years presented significant gaps across all five indicators of care. Our study was limited by the available clinical information, which did not include exact left ventricular ejection fraction values, investigations performed during hospital admissions, or information about follow-up in community heart failure clinics. CONCLUSIONS: Management of heart failure patients in the UK presents important shortcomings that affect screening, continuity of care, and medication titration and disproportionally impact women and older people. National reporting and incentive schemes confined to individual clinical settings have been insufficient to identify these gaps and address patients' long-term care needs.

Temporal trends and patterns in heart failure incidence: a population-based study of 4 million individuals.

BACKGROUND: Large-scale and contemporary population-based studies of heart failure incidence are needed to inform resource planning and research prioritisation but current evidence is scarce. We aimed to assess temporal trends in incidence and prevalence of heart failure in a large general population cohort from the UK, between 2002 and 2014. METHODS: For this population-based study, we used linked primary and secondary electronic health records of 4 million individuals from the Clinical Practice Research Datalink (CPRD), a cohort that is representative of the UK population in terms of age and sex. Eligible patients were aged 16 years and older, had contributed data between Jan 1, 2002, and Dec 31, 2014, had an acceptable record according to CPRD quality control, were approved for CPRD and Hospital Episodes Statistics linkage, and were registered with their general practice for at least 12 months. For patients with incident heart failure, we extracted the most recent measurement of baseline characteristics (within 2 years of diagnosis) from electronic health records, as well as information about comorbidities, socioeconomic status, ethnicity, and region. We calculated standardised rates by applying direct age and sex standardisation to the 2013 European Standard Population, and we inferred crude rates by applying year-specific, age-specific, and sex-specific incidence to UK census mid-year population estimates. We assumed no heart failure for patients aged 15 years or younger and report total incidence and prevalence for all ages (>0 years). FINDINGS: From 2002 to 2014, heart failure incidence (standardised by age and sex) decreased, similarly for men and women, by 7% (from 358 to 332 per 100 000 person-years; adjusted incidence ratio 0·93, 95% CI 0·91-0·94). However, the estimated absolute number of individuals with newly diagnosed heart failure in the UK increased by 12% (from 170 727 in 2002 to 190 798 in 2014), largely due to an increase in population size and age. The estimated absolute number of prevalent heart failure cases in the UK increased even more, by 23% (from 750 127 to 920 616). Over the study period, patient age and multi-morbidity at first presentation of heart failure increased (mean age 76·5 years [SD 12·0] to 77·0 years [12·9], adjusted difference 0·79 years, 95% CI 0·37-1·20; mean number of comorbidities 3·4 [SD 1·9] vs 5·4 [2·5]; adjusted difference 2·0, 95% CI 1·9-2·1). Socioeconomically deprived individuals were more likely to develop heart failure than were affluent individuals (incidence rate ratio 1·61, 95% CI 1·58-1·64), and did so earlier in life than those from the most affluent group (adjusted difference -3·51 years, 95% CI -3·77 to -3·25). From 2002 to 2014, the socioeconomic gradient in age at first presentation with heart failure widened. Socioeconomically deprived individuals also had more comorbidities, despite their younger age. INTERPRETATION: Despite a moderate decline in standardised incidence of heart failure, the burden of heart failure in the UK is increasing, and is now similar to the four most common causes of cancer combined. The observed socioeconomic disparities in disease incidence and age at onset within the same nation point to a potentially preventable nature of heart failure that still needs to be tackled. FUNDING: British Heart Foundation and National Institute for Health Research.

Elevated blood pressure and risk of aortic valve disease: a cohort analysis of 5.4 million UK adults.

Aims: To test two related hypotheses that elevated blood pressure (BP) is a risk factor for aortic valve stenosis (AS) or regurgitation (AR). Methods and results: In this cohort study of 5.4 million UK patients with no known cardiovascular disease or aortic valve disease at baseline, we investigated the relationship between BP and risk of incident AS and AR using multivariable-adjusted Cox regression models. Over a median follow-up of 9.2 years, 20 680 patients (0.38%) were diagnosed with AS and 6440 (0.12%) patients with AR. Systolic BP (SBP) was continuously related to the risk of AS and AR with no evidence of a nadir down to 115 mmHg. Each 20 mmHg increment in SBP was associated with a 41% higher risk of AS (hazard ratio 1.41, 95% confidence interval 1.38-1.45) and a 38% higher risk of AR (1.38, 1.31-1.45). Associations were stronger in younger patients but with no strong evidence for interaction by gender or body mass index. Each 10 mmHg increment in diastolic BP was associated with a 24% higher risk of AS (1.24, 1.19-1.29) but not AR (1.04, 0.97-1.11). Each 15 mmHg increment in pulse pressure was associated with a 46% greater risk of AS (1.46, 1.42-1.50) and a 53% higher risk of AR (1.53, 1.45-1.62). Conclusion: Long-term exposure to elevated BP across its whole spectrum was associated with increased risk of AS and AR. The possible causal nature of the observed associations warrants further investigation.

Patterns and temporal trends of comorbidity among adult patients with incident cardiovascular disease in the UK between 2000 and 2014: A population-based cohort study.

BACKGROUND: Multimorbidity in people with cardiovascular disease (CVD) is common, but large-scale contemporary reports of patterns and trends in patients with incident CVD are limited. We investigated the burden of comorbidities in patients with incident CVD, how it changed between 2000 and 2014, and how it varied by age, sex, and socioeconomic status (SES). METHODS AND FINDINGS: We used the UK Clinical Practice Research Datalink with linkage to Hospital Episode Statistics, a population-based dataset from 674 UK general practices covering approximately 7% of the current UK population. We estimated crude and age/sex-standardised (to the 2013 European Standard Population) prevalence and 95% confidence intervals for 56 major comorbidities in individuals with incident non-fatal CVD. We further assessed temporal trends and patterns by age, sex, and SES groups, between 2000 and 2014. Among a total of 4,198,039 people aged 16 to 113 years, 229,205 incident cases of non-fatal CVD, defined as first diagnosis of ischaemic heart disease, stroke, or transient ischaemic attack, were identified. Although the age/sex-standardised incidence of CVD decreased by 34% between 2000 to 2014, the proportion of CVD patients with higher numbers of comorbidities increased. The prevalence of having 5 or more comorbidities increased 4-fold, rising from 6.3% (95% CI 5.6%-17.0%) in 2000 to 24.3% (22.1%-34.8%) in 2014 in age/sex-standardised models. The most common comorbidities in age/sex-standardised models were hypertension (28.9% [95% CI 27.7%-31.4%]), depression (23.0% [21.3%-26.0%]), arthritis (20.9% [19.5%-23.5%]), asthma (17.7% [15.8%-20.8%]), and anxiety (15.0% [13.7%-17.6%]). Cardiometabolic conditions and arthritis were highly prevalent among patients aged over 40 years, and mental illnesses were highly prevalent in patients aged 30-59 years. The age-standardised prevalence of having 5 or more comorbidities was 19.1% (95% CI 17.2%-22.7%) in women and 12.5% (12.0%-13.9%) in men, and women had twice the age-standardised prevalence of depression (31.1% [28.3%-35.5%] versus 15.0% [14.3%-16.5%]) and anxiety (19.6% [17.6%-23.3%] versus 10.4% [9.8%-11.8%]). The prevalence of depression was 46% higher in the most deprived fifth of SES compared with the least deprived fifth (age/sex-standardised prevalence of 38.4% [31.2%-62.0%] versus 26.3% [23.1%-34.5%], respectively). This is a descriptive study of routine electronic health records in the UK, which might underestimate the true prevalence of diseases. CONCLUSIONS: The burden of multimorbidity and comorbidity in patients with incident non-fatal CVD increased between 2000 and 2014. On average, older patients, women, and socioeconomically deprived groups had higher numbers of comorbidities, but the type of comorbidities varied by age and sex. Cardiometabolic conditions contributed substantially to the burden, but 4 out of the 10 top comorbidities were non-cardiometabolic. The current single-disease paradigm in CVD management needs to broaden and incorporate the large and increasing burden of comorbidities.

Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.

BACKGROUND: Emergency admissions are a major source of healthcare spending. We aimed to derive, validate, and compare conventional and machine learning models for prediction of the first emergency admission. Machine learning methods are capable of capturing complex interactions that are likely to be present when predicting less specific outcomes, such as this one. METHODS AND FINDINGS: We used longitudinal data from linked electronic health records of 4.6 million patients aged 18-100 years from 389 practices across England between 1985 to 2015. The population was divided into a derivation cohort (80%, 3.75 million patients from 300 general practices) and a validation cohort (20%, 0.88 million patients from 89 general practices) from geographically distinct regions with different risk levels. We first replicated a previously reported Cox proportional hazards (CPH) model for prediction of the risk of the first emergency admission up to 24 months after baseline. This reference model was then compared with 2 machine learning models, random forest (RF) and gradient boosting classifier (GBC). The initial set of predictors for all models included 43 variables, including patient demographics, lifestyle factors, laboratory tests, currently prescribed medications, selected morbidities, and previous emergency admissions. We then added 13 more variables (marital status, prior general practice visits, and 11 additional morbidities), and also enriched all variables by incorporating temporal information whenever possible (e.g., time since first diagnosis). We also varied the prediction windows to 12, 36, 48, and 60 months after baseline and compared model performances. For internal validation, we used 5-fold cross-validation. When the initial set of variables was used, GBC outperformed RF and CPH, with an area under the receiver operating characteristic curve (AUC) of 0.779 (95% CI 0.777, 0.781), compared to 0.752 (95% CI 0.751, 0.753) and 0.740 (95% CI 0.739, 0.741), respectively. In external validation, we observed an AUC of 0.796, 0.736, and 0.736 for GBC, RF, and CPH, respectively. The addition of temporal information improved AUC across all models. In internal validation, the AUC rose to 0.848 (95% CI 0.847, 0.849), 0.825 (95% CI 0.824, 0.826), and 0.805 (95% CI 0.804, 0.806) for GBC, RF, and CPH, respectively, while the AUC in external validation rose to 0.826, 0.810, and 0.788, respectively. This enhancement also resulted in robust predictions for longer time horizons, with AUC values remaining at similar levels across all models. Overall, compared to the baseline reference CPH model, the final GBC model showed a 10.8% higher AUC (0.848 compared to 0.740) for prediction of risk of emergency admission within 24 months. GBC also showed the best calibration throughout the risk spectrum. Despite the wide range of variables included in models, our study was still limited by the number of variables included; inclusion of more variables could have further improved model performances. CONCLUSIONS: The use of machine learning and addition of temporal information led to substantially improved discrimination and calibration for predicting the risk of emergency admission. Model performance remained stable across a range of prediction time windows and when externally validated. These findings support the potential of incorporating machine learning models into electronic health records to inform care and service planning.

Modulated Fragmentation of Proapoptotic Peptide Nanoparticles Regulates Cytotoxicity.

Peptides perform a diverse range of physiologically important functions. The formulation of nanoparticles directly from functional peptides would therefore offer a versatile and robust platform to produce highly functional therapeutics. Herein, we engineered proapoptotic peptide nanoparticles from mitochondria-disrupting KLAK peptides using a template-assisted approach. The nanoparticles were designed to disassemble into free native peptides via the traceless cleavage of disulfide-based cross-linkers. Furthermore, the cytotoxicity of the nanoparticles was tuned by controlling the kinetics of disulfide bond cleavage, and the rate of regeneration of the native peptide from the precursor species. In addition, a small molecule drug (i.e., doxorubicin hydrochloride) was loaded into the nanoparticles to confer synergistic cytotoxic activity, further highlighting the potential application of KLAK particles in therapeutic delivery.