Healthcare utilisation in people with long COVID: an OpenSAFELY cohort study.

BACKGROUND: Long COVID potentially increases healthcare utilisation and costs. However, its impact on the NHS remains to be determined. METHODS: This study aims to assess the healthcare utilisation of individuals with long COVID. With the approval of NHS England, we conducted a matched cohort study using primary and secondary care data via OpenSAFELY, a platform for analysing anonymous electronic health records. The long COVID exposure group, defined by diagnostic codes, was matched with five comparators without long COVID between Nov 2020 and Jan 2023. We compared their total healthcare utilisation from GP consultations, prescriptions, hospital admissions, A&E visits, and outpatient appointments. Healthcare utilisation and costs were evaluated using a two-part model adjusting for covariates. Using a difference-in-difference model, we also compared healthcare utilisation after long COVID with pre-pandemic records. RESULTS: We identified 52,988 individuals with a long COVID diagnosis, matched to 264,867 comparators without a diagnosis. In the 12 months post-diagnosis, there was strong evidence that those with long COVID were more likely to use healthcare resources (OR: 8.29, 95% CI: 7.74-8.87), and have 49% more healthcare utilisation (RR: 1.49, 95% CI: 1.48-1.51). Our model estimated that the long COVID group had 30 healthcare visits per year (predicted mean: 29.23, 95% CI: 28.58-29.92), compared to 16 in the comparator group (predicted mean visits: 16.04, 95% CI: 15.73-16.36). Individuals with long COVID were more likely to have non-zero healthcare expenditures (OR = 7.66, 95% CI = 7.20-8.15), with costs being 44% higher than the comparator group (cost ratio = 1.44, 95% CI: 1.39-1.50). The long COVID group costs approximately £2500 per person per year (predicted mean cost: £2562.50, 95% CI: £2335.60-£2819.22), and the comparator group costs £1500 (predicted mean cost: £1527.43, 95% CI: £1404.33-1664.45). Historically, individuals with long COVID utilised healthcare resources more frequently, but their average healthcare utilisation increased more after being diagnosed with long COVID, compared to the comparator group. CONCLUSIONS: Long COVID increases healthcare utilisation and costs. Public health policies should allocate more resources towards preventing, treating, and supporting individuals with long COVID.

Impact of long COVID on health-related quality-of-life: an OpenSAFELY population cohort study using patient-reported outcome measures (OpenPROMPT).

Background: Long COVID is a major problem affecting patient health, the health service, and the workforce. To optimise the design of future interventions against COVID-19, and to better plan and allocate health resources, it is critical to quantify the health and economic burden of this novel condition. We aimed to evaluate and estimate the differences in health impacts of long COVID across sociodemographic categories and quantify this in Quality-Adjusted Life-Years (QALYs), widely used measures across health systems. Methods: With the approval of NHS England, we utilised OpenPROMPT, a UK cohort study measuring the impact of long COVID on health-related quality-of-life (HRQoL). OpenPROMPT invited responses to Patient Reported Outcome Measures (PROMs) using a smartphone application and recruited between November 2022 and October 2023. We used the validated EuroQol EQ-5D questionnaire with the UK Value Set to develop disutility scores (1-utility) for respondents with and without Long COVID using linear mixed models, and we calculated subsequent Quality-Adjusted Life-Months (QALMs) for long COVID. Findings: The total OpenPROMPT cohort consisted of 7575 individuals who consented to data collection, with which we used data from 6070 participants who completed a baseline research questionnaire where 24.6% self-reported long COVID. In multivariable regressions, long COVID had a consistent impact on HRQoL, showing a higher likelihood or odds of reporting loss in quality-of-life (Odds Ratio (OR): 4.7, 95% CI: 3.72-5.93) compared with people who did not report long COVID. Reporting a disability was the largest predictor of losses of HRQoL (OR: 17.7, 95% CI: 10.37-30.33) across survey responses. Self-reported long COVID was associated with an 0.37 QALM loss. Interpretation: We found substantial impacts on quality-of-life due to long COVID, representing a major burden on patients and the health service. We highlight the need for continued support and research for long COVID, as HRQoL scores compared unfavourably to patients with conditions such as multiple sclerosis, heart failure, and renal disease. Funding: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).

Novel prognostic impact and cell specific role of endocan in patients with coronary artery disease.

BACKGROUND: Both the clinical and mechanistic impacts of endocan were not well elucidated especially in coronary artery disease (CAD). OBJECTIVE: This study aimed to investigate the prognostic and potential pathological role of endocan for cardiovascular (CV) events in stable CAD patients. METHODS: A total of 1,071 stable CAD patients with previous percutaneous coronary intervention (PCI) were enrolled prospectively in a nationwide Biosignature study. Another cohort of 76 CAD patients with or without PCI were enrolled for validation. Baseline biomarkers including endocan level was measured and total CV events especially hard CV events (including CV mortality, non-fatal myocardial infection and stroke) during follow-up were identified. Circulating endothelial progenitor cells (EPCs) as an in vivo biological contributor to vascular repairment from CAD patients were used for the in vitro functional study. RESULTS: After 24 months, there were 42 patients (3.92%) with hard CV events and 207 (19.3%) with total CV events in the study group. The incidence of both events was increased with the tertiles of baseline endocan level (hard events: 1.7%,3.4%, and 6.7% in 1st,2nd, and 3rd tertile respectively, p = 0.002; total events: 13.8%vs.16.2%vs.28.0%, p < 0.0001). Multivariate regression analysis revealed the independent association of endocan level with total and hard CV events. These findings were validated in another cohort with a 5-year follow-up. Furthermore, in vitro inhibition of endocan improved cell migration and tube formation capacities, and reduced cell adhesiveness of EPCs from CAD patients. CONCLUSIONS: Endocan might be a novel prognostic indicator, mechanistic mediator, and potential therapeutic target for clinical CAD.

CCL4 contributes to aging related angiogenic insufficiency through activating oxidative stress and endothelial inflammation.

Aging is a natural process associated with chronic inflammation in the development of vascular dysfunction. We hypothesized that chemokine C-C motif ligands 4 (CCL4) might play a vital role in aging-related vascular dysfunction. Circulating CCL4 was up-regulated in elderly subjects and in aged animals. CCL4 inhibition reduced generation of reactive oxygen species (ROS), attenuated inflammation, and restored cell functions in endothelial progenitor cells from elderly subjects and in aged human aortic endothelial cells. CCL4 promoted cell aging, with impaired cell functioning, by activating ROS production and inflammation. CCL4 knockout mice and therapeutic administration of anti-CCL4 neutralizing antibodies exhibited vascular and dermal anti-aging effects, with improved wound healing, via the down-regulation of inflammatory proteins and the activation of angiogenic proteins. Altogether, our findings suggested that CCL4 may contribute to aging-related vascular dysfunction via activating oxidative stress and endothelial inflammation. CCL4 may be a potential therapeutic target for vascular protections during aging.

Clinical coding of long COVID in primary care 2020-2023 in a cohort of 19 million adults: an OpenSAFELY analysis.

Background: Long COVID is the patient-coined term for the persistent symptoms of COVID-19 illness for weeks, months or years following the acute infection. There is a large burden of long COVID globally from self-reported data, but the epidemiology, causes and treatments remain poorly understood. Primary care is used to help identify and treat patients with long COVID and therefore Electronic Health Records (EHRs) of past COVID-19 patients could be used to help fill these knowledge gaps. We aimed to describe the incidence and differences in demographic and clinical characteristics in recorded long COVID in primary care records in England. Methods: With the approval of NHS England we used routine clinical data from over 19 million adults in England linked to SARS-COV-2 test result, hospitalisation and vaccination data to describe trends in the recording of 16 clinical codes related to long COVID between November 2020 and January 2023. Using OpenSAFELY, we calculated rates per 100,000 person-years and plotted how these changed over time. We compared crude and adjusted (for age, sex, 9 NHS regions of England, and the dominant variant circulating) rates of recorded long COVID in patient records between different key demographic and vaccination characteristics using negative binomial models. Findings: We identified a total of 55,465 people recorded to have long COVID over the study period, which included 20,025 diagnoses codes and 35,440 codes for further assessment. The incidence of new long COVID records increased steadily over 2021, and declined over 2022. The overall rate per 100,000 person-years was 177.5 cases in women (95% CI: 175.5-179) and 100.5 in men (99.5-102). The majority of those with a long COVID record did not have a recorded positive SARS-COV-2 test 12 or more weeks before the long COVID record. Interpretation: In this descriptive study, EHR recorded long COVID was very low between 2020 and 2023, and incident records of long COVID declined over 2022. Using EHR diagnostic or referral codes unfortunately has major limitations in identifying and ascertaining true cases and timing of long COVID. Funding: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).

Soluble tumor necrosis factor receptor type 1 is an alternative marker of urinary albumin-creatinine ratio and estimated glomerular filtration rate for predicting the decline of renal function in subjects with type 2 diabetes mellitus.

BACKGROUND: Urinary albumin-creatinine ratio (UACR) and estimated glomerular filtration rates (eGFR) help predict worsening diabetic kidney disease (DKD) but have their limitations. Soluble tumor necrosis factor receptor type 1 (sTNFR1) is a biomarker of DKD. The predictive abilities of sTNFR1 and UACR plus eGFR have not been compared. METHODS: This prospective cohort study included patients with type 2 diabetes (T2D) to identify the risk factors of worsening DKD. Renal events were defined as > 30 % loss in eGFR based on consecutive tests after 6 months. The associations of sTNFR1, UACR, and eGFR levels and the risks of renal events were tested using a Cox regression model and the area under the curve (AUC) was compared between sTNFR1 levels and UACR plus eGFR using receiver-operating characteristic (ROC) analysis. The accuracy of stratification was evaluated using Kaplan-Meier analysis. RESULTS: Levels of sTNFR1 and UACR were associated with risks of > 30 % decline in eGFR after adjusting for relevant factors. The association between sTNFR1 levels and renal outcomes was independent of UACR and eGFR at baseline. The AUC of sTNFR1 level was comparable with that of combined UACR and eGFR (0.73 vs. 0.71, respectively, p = 0.72) and the results persisted for quartile groups of sTNFR1 and risk categories of Kidney Disease: Improving Global Outcomes (KDIGO) (0.70 vs. 0.71, respectively, p = 0.84). Both stratifications by sTNFR1 levels and KDIGO were accurate. CONCLUSION: sTNFR1 could be an alternative marker for identifying patients with diabetes at risk of declining renal function.

Recent progress in unraveling cardiovascular complications associated with primary aldosteronism: a succinct review.

This comprehensive review offers a thorough exploration of recent advancements in our understanding of the intricate cardiovascular complications associated with Primary Aldosteronism (PA). PA encompasses a spectrum of conditions characterized by hypertension and excessive production of aldosterone operating independently of the renin-angiotensin system. Given its association with an elevated risk of cardiovascular and cerebrovascular complications, as well as a higher incidence of metabolic syndrome in comparison to individuals with essential hypertension (EH), an accurate diagnosis of PA is of paramount importance. This review delves into the intricate interplay between PA and cardiovascular health and focuses on the key pathophysiological mechanisms contributing to adverse cardiac outcomes. The impact of different treatment modalities on cardiovascular health is also examined, offering insights into potential therapeutic approaches. By highlighting the significance of recognizing PA as a significant contributor to cardiovascular morbidity, this review emphasizes the need for improved screening, early diagnosis, and tailored management strategies to both enhance patient care and mitigate the burden of cardiovascular diseases. The findings presented herein underscore the growing importance of PA in the context of cardiovascular medicine and emphasize the potential for translating these insights into targeted interventions to improve patient outcomes.

The predictors of long-term outcomes after targeted therapy for primary Aldosteronism.

Unilateral primary aldosteronism is thought to be a surgically curable disease, and unilateral adrenalectomy is the mainstay treatment. The Primary Aldosteronism Surgical Outcome (PASO) consensus was developed to assess clinical and biochemical outcomes to standardize the classification of surgical outcomes. However, fewer than half of patients are cured of hypertension after adrenalectomy; therefore, preoperative patient counseling and evaluation might be necessary. Moreover, current studies show that genetic mutations and histopathology classification are associated with the treatment outcome. The Task Force of Taiwan PA recommends using a specific scoring system, including the PASO score and nomogram-based preoperative score, to predict the clinical outcome before adrenalectomy. Herein, we discuss the associations of current histopathological classification and specific somatic gene mutations with clinical outcomes after surgery.

Deep convolutional neural networks for aged microplastics identification by Fourier transform infrared spectra classification.

Infrared (IR) spectroscopy is a powerful technique for detecting and identifying Microplastics (MPs) in the environment. However, the aging of MPs presents a challenge in accurately identification and classification. To address this challenge, a classification model based on deep convolutional neural networks (CNNs) was developed using infrared spectra results. Particularly, original infrared (IR) spectra were used as the sample dataset, therefore, relevant spectral details were preserved and additional noise or distortions were not introduced. The Adam (Adaptive moment estimation) algorithm was employed to accelerate gradient descent and weight update, the Dropout function was implemented to prevent overfitting and enhance the generalization performance of the network. An activation function ReLu (Rectified Linear Unit) was also utilized to simplify the co-adaptation relationship among neurons and prevent gradient disappearance. The performance of the CNN model in MPs classification was evaluated based on accuracy and robustness, and compared with other machine learning techniques. CNN model demonstrated superior capabilities in feature extraction and recognition, and greatly simplified the pre-processing procedure. The identification results of aged commercial microplastic samples showed accuracies of 40 % for Artificial Neural Network, 60 % for Random Forest, 80 % for Deep Neural Network, and 100 % for CNN, respectively. The CNN architecture developed in this work also demonstrates versatility by being suitable for both limited data cases and potential expansion to include more discrete data in the future.

Systemic antibiotics adjuvants to scaling and root planing in type 2 diabetic and periodontitis individuals: Systematic review with network meta-analysis.

Targeting inflammatory pathways is considered a common strategy to control type 2 diabetes (T2D) and periodontitis. This overview was to validate systemic antibiotics as an adjuvant to scaling and root planing (SRP) for the treatments of periodontal patients with T2D. Literature searches were conducted using Web of Science, PubMed, Cochrane, and EMBASE. Randomized trials comparing SRP and systemic antibiotics on glycated hemoglobin (HbA1c) and probing pocket depth (PPD) in adults with T2D and periodontitis were analyzed using network meta-analysis and meta-regression. At 3-month postintervention, meta-analyses of 16 studies revealed that SRP and SRP plus systemic antibiotics (SRPa) had similar significant effects in reducing HbA1c levels of - 0.72% and - 0.96% respectively. While SRP and SRPa also, respectively, reduced PPD of - 0.67 and - 0.89 mm, SRPa showed a better reduction than SRP. At 6-month postintervention, meta-analyses of 7 trials revealed that only SRP was effective in reducing HbA1c levels (-0.29%) but not SRPa. Although both SRP and SRPa still significantly reduced PPD by - 0.56 and - 0.81 mm, respectively, there was no difference between them. The current overview suggested that routine SRP alone is highly recommended for patients with T2D and periodontitis, since systemic antibiotics as an adjuvant provide a rather short-term effect.