Bilateral cystoid macular edema as the presenting feature of chronic myeloid leukemia.

PURPOSE: Ophthalmic disease may rarely be a presenting feature of chronic myeloid leukemia (CML). METHODS: We report a case of a 53-year-old man with type 1 diabetes mellitus who presented with a rapid onset of bilateral blurred vision. RESULTS: He was noted to have bilateral macular edema and was initially treated for presumed diabetic macular edema (DME) with intravitreal alifbercept injections. One month later, there was complete resolution of his macular edema. Review of his history and imaging revealed features atypical for DME, specifically; the rapid onset of bilateral blurred vision over 2-3 weeks, numerous cotton wool spots within the macula, the absence of any exudates, the symmetrical macular edema with a "vaulted ceiling" appearance (more typical of cystoid macular edema) and the dramatic response to a single intravitreal aflibercept injection. One week after his intravitreal injection, the patient was diagnosed with CML following marked leucocytosis on a routine blood test by his general practitioner. Although uncommon, sudden onset bilateral edema in the absence of other chronic diabetic changes should prompt consideration of an underlying haematological cause. CONCLUSION: This case highlights the importance of considering CML as a differential diagnosis in patients presenting with sudden onset, bilateral cystoid macular oedema. Vigilance is especially important in patients with co-existing diabetic retinopathy as the clinical features of leukemic retinopathy can overlap. Furthermore, the diagnosis of CML in a patient with diabetes mellitus should prompt extra observation for accelerated worsening of diabetic retinopathy.

Phenogrouping heart failure with preserved or mildly reduced ejection fraction using electronic health record data.

BACKGROUND: Heart failure (HF) with preserved or mildly reduced ejection fraction includes a heterogenous group of patients. Reclassification into distinct phenogroups to enable targeted interventions is a priority. This study aimed to identify distinct phenogroups, and compare phenogroup characteristics and outcomes, from electronic health record data. METHODS: 2,187 patients admitted to five UK hospitals with a diagnosis of HF and a left ventricular ejection fraction ≥ 40% were identified from the NIHR Health Informatics Collaborative database. Partition-based, model-based, and density-based machine learning clustering techniques were applied. Cox Proportional Hazards and Fine-Gray competing risks models were used to compare outcomes (all-cause mortality and hospitalisation for HF) across phenogroups. RESULTS: Three phenogroups were identified: (1) Younger, predominantly female patients with high prevalence of cardiometabolic and coronary disease; (2) More frail patients, with higher rates of lung disease and atrial fibrillation; (3) Patients characterised by systemic inflammation and high rates of diabetes and renal dysfunction. Survival profiles were distinct, with an increasing risk of all-cause mortality from phenogroups 1 to 3 (p < 0.001). Phenogroup membership significantly improved survival prediction compared to conventional factors. Phenogroups were not predictive of hospitalisation for HF. CONCLUSIONS: Applying unsupervised machine learning to routinely collected electronic health record data identified phenogroups with distinct clinical characteristics and unique survival profiles.

Race- and Ethnicity-Related Differences in Heart Failure With Preserved Ejection Fraction Using Natural Language Processing.

Background: Heart failure with preserved ejection fraction (HFpEF) is the predominant form of HF in older adults. It represents a heterogenous clinical syndrome that is less well understood across different ethnicities. Objectives: This study aimed to compare the clinical presentation and assess the diagnostic performance of existing HFpEF diagnostic tools between ethnic groups. Methods: A validated Natural Language Processing (NLP) algorithm was applied to the electronic health records of a large London hospital to identify patients meeting the European Society of Cardiology criteria for a diagnosis of HFpEF. NLP extracted patient demographics (including self-reported ethnicity and socioeconomic status), comorbidities, investigation results (N-terminal pro-B-type natriuretic peptide, H2FPEF scores, and echocardiogram reports), and mortality. Analyses were stratified by ethnicity and adjusted for socioeconomic status. Results: Our cohort consisted of 1,261 (64%) White, 578 (29%) Black, and 134 (7%) Asian patients meeting the European Society of Cardiology HFpEF diagnostic criteria. Compared to White patients, Black patients were younger at diagnosis and more likely to have metabolic comorbidities (obesity, diabetes, and hypertension) but less likely to have atrial fibrillation (30% vs 13%; P < 0.001). Black patients had lower N-terminal pro-B-type natriuretic peptide levels and a lower frequency of H2FPEF scores ≥6, indicative of likely HFpEF (26% vs 44%; P < 0.0001). Conclusions: Leveraging an NLP-based artificial intelligence approach to quantify health inequities in HFpEF diagnosis, we discovered that established markers systematically underdiagnose HFpEF in Black patients, possibly due to differences in the underlying comorbidity patterns. Clinicians should be aware of these limitations and its implications for treatment and trial recruitment.

Primary care optometry-based diabetic retinopathy review clinics - a new model of care and comparison with virtual diabetic retinopathy clinics.

BACKGROUND: Given the increasing prevalence of diabetes and diabetic retinopathy (DR) in the UK, this study evaluates a novel primary care optometry-based DR review service against traditional hospital-based virtual DR clinics. METHODS: In the hospital-based virtual DR service, patients attended for data capture (visual acuity, fundus photography, macular OCT scanning) with asynchronous review at a later data by a hospital clinician. In the primary care optometry DR review clinic, patients attended an optometry practice for a face-to-face(F2F) review (with imaging) by an optometrist with additional training in DR. Data from both clinic types were analysed. Metrics included DR grading, management plans, grading concordance between primary care optometrists and consultant ophthalmologists, and the assessment of "ungradable" retinopathy referrals. RESULTS: One thousand seven hundred and sixty patients attended the virtual clinic between January 2021 and September 2023. 954 patients attended the primary care review clinic between August 2022 and September 2023. Grading agreements between primary care optometrists and hospital consultants on those patients referred for consultant opinion were significant with Weighted Kappa scores of 0.61(95% CI 0.52-0.69) for DR grade and 0.69(95% CI 0.56-0.82) for diabetic macular oedema (DMO) status. Additionally, the primary care optometry clinic reported a considerably reduced non-attendance rate of 5%, in contrast to 21% in virtual clinics. CONCLUSION: The primary care optometry-based DR service emerges as an efficient, safe alternative to hospital services. It offers notable advantages over virtual clinics and addresses a care gap for those unsuitable for virtual consultations. The results highlight the potential of primary care-based models in managing DR.

Changes in the investigation and management of suspected myocardial infarction and injury during COVID-19: a multi-centre study using routinely collected healthcare data.

Objective: The COVID-19 pandemic was associated with a reduction in the incidence of myocardial infarction (MI) diagnosis, in part because patients were less likely to present to hospital. Whether changes in clinical decision making with respect to the investigation and management of patients with suspected MI also contributed to this phenomenon is unknown. Methods: Multicentre retrospective cohort study in three UK centres contributing data to the National Institute for Health Research Health Informatics Collaborative. Patients presenting to the Emergency Department (ED) of these centres between 1st January 2020 and 1st September 2020 were included. Three time epochs within this period were defined based on the course of the first wave of the COVID-19 pandemic: pre-pandemic (epoch 1), lockdown (epoch 2), post-lockdown (epoch 3). Results: During the study period, 10,670 unique patients attended the ED with chest pain or dyspnoea, of whom 6,928 were admitted. Despite fewer total ED attendances in epoch 2, patient presentations with dyspnoea were increased (p < 0.001), with greater likelihood of troponin testing in both chest pain (p = 0.001) and dyspnoea (p < 0.001). There was a dramatic reduction in elective and emergency cardiac procedures (both p < 0.001), and greater overall mortality of patients (p < 0.001), compared to the pre-pandemic period. Positive COVID-19 and/or troponin test results were associated with increased mortality (p < 0.001), though the temporal risk profile differed. Conclusions: The first wave of the COVID-19 pandemic was associated with significant changes not just in presentation, but also the investigation, management, and outcomes of patients presenting with suspected myocardial injury or MI.

Machine Learning and External Validation of the IDENTIFY Risk Calculator for Patients with Haematuria Referred to Secondary Care for Suspected Urinary Tract Cancer.

BACKGROUND: The IDENTIFY study developed a model to predict urinary tract cancer using patient characteristics from a large multicentre, international cohort of patients referred with haematuria. In addition to calculating an individual's cancer risk, it proposes thresholds to stratify them into very-low-risk (<1%), low-risk (1-<5%), intermediate-risk (5-<20%), and high-risk (≥20%) groups. OBJECTIVE: To externally validate the IDENTIFY haematuria risk calculator and compare traditional regression with machine learning algorithms. DESIGN, SETTING, AND PARTICIPANTS: Prospective data were collected on patients referred to secondary care with new haematuria. Data were collected for patient variables included in the IDENTIFY risk calculator, cancer outcome, and TNM staging. Machine learning methods were used to evaluate whether better models than those developed with traditional regression methods existed. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The area under the receiver operating characteristic curve (AUC) for the detection of urinary tract cancer, calibration coefficient, calibration in the large (CITL), and Brier score were determined. RESULTS AND LIMITATIONS: There were 3582 patients in the validation cohort. The development and validation cohorts were well matched. The AUC of the IDENTIFY risk calculator on the validation cohort was 0.78. This improved to 0.80 on a subanalysis of urothelial cancer prevalent countries alone, with a calibration slope of 1.04, CITL of 0.24, and Brier score of 0.14. The best machine learning model was Random Forest, which achieved an AUC of 0.76 on the validation cohort. There were no cancers stratified to the very-low-risk group in the validation cohort. Most cancers were stratified to the intermediate- and high-risk groups, with more aggressive cancers in higher-risk groups. CONCLUSIONS: The IDENTIFY risk calculator performed well at predicting cancer in patients referred with haematuria on external validation. This tool can be used by urologists to better counsel patients on their cancer risks, to prioritise diagnostic resources on appropriate patients, and to avoid unnecessary invasive procedures in those with a very low risk of cancer. PATIENT SUMMARY: We previously developed a calculator that predicts patients' risk of cancer when they have blood in their urine, based on their personal characteristics. We have validated this risk calculator, by testing it on a separate group of patients to ensure that it works as expected. Most patients found to have cancer tended to be in the higher-risk groups and had more aggressive types of cancer with a higher risk. This tool can be used by clinicians to fast-track high-risk patients based on the calculator and investigate them more thoroughly.

Validation of the CREST model & Comparison with SCAI Shock Classification for Prediction of Circulatory Death in Resuscitated Out of Hospital Cardiac Arrest.

OBJECTIVE: We validated the CREST model, a 5 variable score for stratifying risk of circulatory etiology death (CED) following out of hospital cardiac arrest (OHCA), and compared its discrimination with the SCAI shock classification. BACKGROUND: CED occurs in approximately a third of patients admitted after resuscitated OHCA. There is an urgent need for improved stratification of the OHCA patient on arrival to a cardiac arrest centre to improve patient selection for invasive interventions. METHODS: The CREST model and SCAI shock classification were applied to a dual-centre registry of 723 patients with cardiac etiology OHCA, both with and without ST-elevation myocardial infarction, between May 2012 to December 2020. The primary endpoint was 30-day CED. RESULTS: Of 509 patients included (62.3 years, 75.4% male), 125 patients had CREST=0 (24.5%), 162 were CREST=1 (31.8%), 140 were CREST=2 (27.5%), 75 were CREST=3 (14.7%), 7 were CREST of 4 (1.4%) and no patients were CREST=5. CED was observed in 91 (17.9%) patients at 30 days [STEMI - 51/289 (17.6%); NSTEMI - 40/220 (18.2%)]. For the total population, and both NSTEMI & STEMI subpopulations, increasing CREST score was associated with increasing CED (all p<0.001). CREST score and SCAI classification had similar discrimination for the total population (AUC=0.72/calibration slope=0.95), NSTEMI cohort (AUC=0.75/calibration slope=0.940) and STEMI cohort (AUC=0.69 and calibration slope=0.925). AUC meta-analyses demonstrated no significant differences between the two classifications. CONCLUSIONS: The CREST model and SCAI shock classification have similar prediction for the development of CED after OHCA.

The associations of opioid and benzodiazepine prescriptions with injuries among US military service members.

ABSTRACT: Given the high rates of physical trauma and pain among service members, opioid-prescribing practices and use patterns have significant implications for the well-being of service members and can affect military medicine and personnel readiness. This study measured the association between prescribed opioid and benzodiazepine medications and subsequently reported injuries (accidental, alcohol and drug related, self-inflicted, and violence related) among active duty military members. Participants were service members who entered the military between January 1, 2005, and June 30, 2010. In a nested case-control design, we compared individuals with injuries to individuals without injuries with respect to their opioid and benzodiazepine prescriptions in the 30 days before the injury of an index case. We used a multiintercept, logistic regression model to compare coefficient estimates by injury type. Overall, approximately 17% of individuals with an injury and 4% of individuals without an injury had a recorded opioid prescription. Individuals with an injury of any type had greater odds of prior exposure to opioid prescriptions than controls. Although a dose-response effect was observed for all injury types, it reached a plateau sooner for natural or environmental accidents and self-inflicted injuries relative to alcohol-related and drug-related injuries, violence-related injuries, vehicle accidents, accidental falls, and other accidents. Benzodiazepine prescriptions were found in 3.5% of individuals with an injury and 0.5% of individuals without an injury. The association between benzodiazepine prescriptions and injuries was strongest for natural and environmental accidents.

QI short report: Virtual clinics are a safe and efficient method of expanding the hospital diabetic retinopathy service.

Demand for hospital diabetic retinopathy (DR) appointments is increasing and exceeding capacity, leading to long waiting lists. Delays in appropriate treatment can cause irreversible yet avoidable vision loss. We assessed if capacity of the DR service could be safely expanded by utilising virtual clinics. Virtual clinics increased the service capacity by more than 100% and did not cause delays in delivering urgent treatments. The majority of patients reviewed had low-risk disease and follow-up could be maintained in the virtual clinic.

Severe mental illness: cardiovascular risk assessment and management.

Patients with severe mental illness (SMI) including schizophrenia and bipolar disorder die on average 15-20 years earlier than the general population often due to sudden death that, in most cases, is caused by cardiovascular disease. This state-of-the-art review aims to address the complex association between SMI and cardiovascular risk, explore disparities in cardiovascular care pathways, describe how to adequately predict cardiovascular outcomes, and propose targeted interventions to improve cardiovascular health in patients with SMI. These patients have an adverse cardiovascular risk factor profile due to an interplay between biological factors such as chronic inflammation, patient factors such as excessive smoking, and healthcare system factors such as stigma and discrimination. Several disparities in cardiovascular care pathways have been demonstrated in patients with SMI, resulting in a 47% lower likelihood of undergoing invasive coronary procedures and substantially lower rates of prescribed standard secondary prevention medications compared with the general population. Although early cardiovascular risk prediction is important, conventional risk prediction models do not accurately predict long-term cardiovascular outcomes as cardiovascular disease and mortality are only partly driven by traditional risk factors in this patient group. As such, SMI-specific risk prediction models and clinical tools such as the electrocardiogram and echocardiogram are necessary when assessing and managing cardiovascular risk associated with SMI. In conclusion, there is a necessity for differentiated cardiovascular care in patients with SMI. By addressing factors involved in the excess cardiovascular risk, reconsidering risk stratification approaches, and implementing multidisciplinary care models, clinicians can take steps towards improving cardiovascular health and long-term outcomes in patients with SMI.

Introducing WASHOUT: A Large-scale Observational Study of Inpatient Haematuria.

WASHOUT is an international, multicentre, prospective observational study aiming to describe the management of unscheduled haematuria admissions. Preregistration can be done using the following link: https://redcap.link/WASHOUT.

Retinal Oxygenation With Conventional 100-ms Versus Short-Pulse Pan-Retinal Laser Photocoagulation.

BACKGROUND AND OBJECTIVE: Conventional (100 ms) pan-retinal photocoagulation (PRP) laser burns are larger than short-pulse (10 ms to 20 ms) PRP burns. This study investigates the effect of PRP burns of different sizes on retinal oxygenation. METHOD: A mathematical model using COMSOL Multiphysics 6 was used to create a three-dimensional abstraction of the coupled biology of the choroid, photoreceptor, and retinal tissues. Laser burn sizes were varied in the model, specifically considering burn diameters of 500 µm, 250 µm, and 125 µm, while keeping the total burn area constant. RESULTS: Total increase in retinal oxygenation was the same for different burn sizes, but the oxygen distribution differed. Smaller burns resulted in a more even lateral oxygen distribution but with reduced penetration into the inner retina. CONCLUSIONS: Conventional and short-pulse PRP may affect retinal oxygenation differently, even when total burn area is the same. Further investigation into optimum burn size and pattern is required. [Ophthalmic Surg Lasers Imaging Retina 2024;55:40-45.].

Energy metabolism modulates the regulatory impact of activators on gene expression.

Gene expression is a regulated process fueled by ATP consumption. Therefore, regulation must be coupled to constraints imposed by the level of energy metabolism. Here, we explore this relationship both theoretically and experimentally. A stylized mathematical model predicts that activators of gene expression have variable impact depending on metabolic rate. Activators become less essential when metabolic rate is reduced and more essential when metabolic rate is enhanced. We find that, in the Drosophila eye, expression dynamics of the yan gene are less affected by loss of EGFR-mediated activation when metabolism is reduced, and the opposite effect is seen when metabolism is enhanced. The effects are also seen at the level of pattern regularity in the adult eye, where loss of EGFR-mediated activation is mitigated by lower metabolism. We propose that gene activation is tuned by energy metabolism to allow for faithful expression dynamics in the face of variable metabolic conditions.

Artificial intelligence methods for improved detection of undiagnosed heart failure with preserved ejection fraction.

AIM: Heart failure with preserved ejection fraction (HFpEF) remains under-diagnosed in clinical practice despite accounting for nearly half of all heart failure (HF) cases. Accurate and timely diagnosis of HFpEF is crucial for proper patient management and treatment. In this study, we explored the potential of natural language processing (NLP) to improve the detection and diagnosis of HFpEF according to the European Society of Cardiology (ESC) diagnostic criteria. METHODS AND RESULTS: In a retrospective cohort study, we used an NLP pipeline applied to the electronic health record (EHR) to identify patients with a clinical diagnosis of HF between 2010 and 2022. We collected demographic, clinical, echocardiographic and outcome data from the EHR. Patients were categorized according to the left ventricular ejection fraction (LVEF). Those with LVEF ≥50% were further categorized based on whether they had a clinician-assigned diagnosis of HFpEF and if not, whether they met the ESC diagnostic criteria. Results were validated in a second, independent centre. We identified 8606 patients with HF. Of 3727 consecutive patients with HF and LVEF ≥50% on echocardiogram, only 8.3% had a clinician-assigned diagnosis of HFpEF, while 75.4% met ESC criteria but did not have a formal diagnosis of HFpEF. Patients with confirmed HFpEF were hospitalized more frequently; however the ESC criteria group had a higher 5-year mortality, despite being less comorbid and experiencing fewer acute cardiovascular events. CONCLUSIONS: This study demonstrates that patients with undiagnosed HFpEF are an at-risk group with high mortality. It is possible to use NLP methods to identify likely HFpEF patients from EHR data who would likely then benefit from expert clinical review and complement the use of diagnostic algorithms.

Energy metabolism modulates the regulatory impact of activators on gene expression.

Gene expression is a regulated process fueled by ATP consumption. Therefore, regulation must be coupled to constraints imposed by the level of energy metabolism. Here, we explore this relationship both theoretically and experimentally. A stylized mathematical model predicts that activators of gene expression have variable impact depending on metabolic rate. Activators become less essential when metabolic rate is reduced and more essential when metabolic rate is enhanced. We find that in the Drosophila eye, expression dynamics of the yan gene are less affected by loss of EGFR-mediated activation when metabolism is reduced, and the opposite effect is seen when metabolism is enhanced. The effects are also seen at the level of pattern regularity in the adult eye, where loss of EGFR-mediated activation is mitigated by lower metabolism. We propose that gene activation is tuned by energy metabolism to allow for faithful expression dynamics in the face of variable metabolic conditions.

The Relationship Between Cardiac Troponin in People Hospitalised for Exacerbation of COPD and Major Adverse Cardiac Events (MACE) and COPD Readmissions.

Background: No single biomarker currently risk stratifies chronic obstructive pulmonary disease (COPD) patients at the time of an exacerbation, though previous studies have suggested that patients with elevated troponin at exacerbation have worse outcomes. This study evaluated the relationship between peak cardiac troponin and subsequent major adverse cardiac events (MACE) including all-cause mortality and COPD hospital readmission, among patients admitted with COPD exacerbation. Methods: Data from five cross-regional hospitals in England were analysed using the National Institute of Health Research Health Informatics Collaborative (NIHR-HIC) acute coronary syndrome database (2008-2017). People hospitalised with a COPD exacerbation were included, and peak troponin levels were standardised relative to the 99th percentile (upper limit of normal). We used Cox Proportional Hazard models adjusting for age, sex, laboratory results and clinical risk factors, and implemented logarithmic transformation (base-10 logarithm). The primary outcome was risk of MACE within 90 days from peak troponin measurement. Secondary outcome was risk of COPD readmission within 90 days from peak troponin measurement. Results: There were 2487 patients included. Of these, 377 (15.2%) patients had a MACE event and 203 (8.2%) were readmitted within 90 days from peak troponin measurement. A total of 1107 (44.5%) patients had an elevated troponin level. Of 1107 patients with elevated troponin at exacerbation, 256 (22.8%) had a MACE event and 101 (9.0%) a COPD readmission within 90 days from peak troponin measurement. Patients with troponin above the upper limit of normal had a higher risk of MACE (adjusted HR 2.20, 95% CI 1.75-2.77) and COPD hospital readmission (adjusted HR 1.37, 95% CI 1.02-1.83) when compared with patients without elevated troponin. Conclusion: An elevated troponin level at the time of COPD exacerbation may be a useful tool for predicting MACE in COPD patients. The relationship between degree of troponin elevation and risk of future events is complex and requires further investigation.

Oxidative stress and docosahexaenoic acid injury lead to increased necroptosis and ferroptosis in retinal pigment epithelium.

Age-related macular degeneration (AMD) is a complex disease caused by different genetic and environmental risk factors leading to loss of cells in the central part of the retina. Oxidative stress appears to be an important environmental risk factor that contributes to both the initiation and progression of AMD. Retinal pigment epithelium (RPE) plays an important role in regulating oxidative stress in the retina and is one of the main retinal cell types affected in AMD. A main function of RPE is to phagocytose photoreceptor outer segments (POS) which are rich in the polyunsaturated fatty acid (PUFA) docosahexaenoic acid (DHA), making this cell type potentially more susceptible to oxidative stress-induced lipid peroxidation which can lead to cell death. RPE is known to undergo necrotic cell death in response to oxidative stress. The aim of this study was to determine if DHA in POS can increase oxidative damage to RPE. It was found that RPE undergo increased lipid peroxidation and decreased cell viability when stressed with hydrogen peroxide in combination with DHA or POS. H2O2-induced oxidative stress was found to cause both ferroptosis and necroptosis. However, the ferroptosis regulator acyl-CoA synthetase long-chain family member 4 (ACSL4) was found to be downregulated in RPE exposed to H2O2 and this effect was exacerbated when the RPE cells were simultaneously treated with DHA. Together, these results show a response of RPE when stressed which will likely be overwhelmed under disease conditions such as AMD resulting in cell death.

One and Done? The Effectiveness of a Single Session of Physiotherapy Compared With Multiple Sessions to Reduce Pain and Improve Function and Quality of Life in Patients With a Musculoskeletal Disorder: A Systematic Review With Meta-analyses.

OBJECTIVE: To compare single and multiple physiotherapy sessions to improve pain, function, and quality of life (QoL) in patients with musculoskeletal disorders (MSKDs). DATA SOURCES: AMED, Cinahl, SportsDiscus, Medline, Cochrane Register of Clinical Trials, Physiotherapy Evidence Database, and reference lists. STUDY SELECTION: Randomized controlled trials (RCTs) comparing single and multiple physiotherapy sessions for MSKDs. DATA EXTRACTION: Two reviewers extracted data and assessed risk of bias and certainty of evidence using Cochrane Risk of Bias tool 2.0 and Grading of Recommendation Assessment, Development, and Evaluation. DATA SYNTHESIS: Six RCTs (n=2090) were included (conditions studied: osteoporotic vertebral fracture, neck, knee, and shoulder pain). Meta-analyses with low-certainty evidence showed a significant pain improvement at 6 months in favor of multiple sessions compared with single session interventions (3 RCTs; n=1035; standardized mean difference [SMD]: 0.29; 95% CI: 0.05 to 0.53; P=.02) but this significant difference in pain improvement was not observed at 3 months (4 RCTs; n=1312; SMD: 0.39; 95% CI: -0.11 to 0.89; P=.13) and at 12 months (4 RCTs; n=1266; SMD: -0.05; 95% CI: -0.49 to 0.39; P=.82). Meta-analyses with low-certainty evidence showed no significant differences in function at 3 (4 RCTs; n=1583; SMD: 0.05; 95% CI: -0.11 to 0.21; P=.56), 6 (4 RCTs; n=1538; SMD: 0.06; 95% CI: -0.12 to 0.23; P=.53) and 12 months (4 RCTs; n=1528; SMD: 0.08; 95% CI: -0.08 to 0.25; P=.30) and QoL at 3 (4 RCTs; n=1779; SMD: 0.08; 95% CI: -0.02 to 0.17; P=.12), 6 (3 RCTs; n=1206; SMD: 0.03; 95% CI: -0.08 to 0.14; P=.59), and 12 months (4 RCTs; n=1729; SMD: -0.03; 95% CI: -0.12 to 0.07; P=.58). CONCLUSIONS: Low certainty meta-analyses found no clinically significant differences in pain, function, and QoL between single and multiple physiotherapy sessions for MSKD management for the conditions studied. Future research should compare the cost-effectiveness of those different models of care.

Dysfunctional and Dysregulated Nitric Oxide Synthases in Cardiovascular Disease: Mechanisms and Therapeutic Potential.

Nitric oxide (NO) plays an important and diverse signalling role in the cardiovascular system, contributing to the regulation of vascular tone, endothelial function, myocardial function, haemostasis, and thrombosis, amongst many other roles. NO is synthesised through the nitric oxide synthase (NOS)-dependent L-arginine-NO pathway, as well as the nitrate-nitrite-NO pathway. The three isoforms of NOS, namely neuronal (NOS1), inducible (NOS2), and endothelial (NOS3), have different localisation and functions in the human body, and are consequently thought to have differing pathophysiological roles. Furthermore, as we continue to develop a deepened understanding of the different roles of NOS isoforms in disease, the possibility of therapeutically modulating NOS activity has emerged. Indeed, impaired (or dysfunctional), as well as overactive (or dysregulated) NOS activity are attractive therapeutic targets in cardiovascular disease. This review aims to describe recent advances in elucidating the physiological role of NOS isoforms within the cardiovascular system, as well as mechanisms of dysfunctional and dysregulated NOS in cardiovascular disease. We then discuss the modulation of NO and NOS activity as a target in the development of novel cardiovascular therapeutics.