Significance of abnormal stress electrocardiography with normal cardiac imaging during stress testing-a meta-analysis.

BACKGROUND AND AIMS: Diagnostic testing for coronary artery disease frequently involves functional stress testing where imaging is often coupled with electrocardiogram (ECG) analysis. While decision-making is straightforward when both functional testing and ECG are either positive or negative, interpretation is challenging and prognostic importance uncertain with positive ECG and negative imaging since imaging is considered more sensitive. Prior studies have demonstrated mixed results. We sought to perform a meta-analysis of published studies to determine the significance of this particular type of discordant stress test result. METHODS AND RESULTS: PubMed, Cochrane, and Google Scholar were searched to identify studies reporting results of functional imaging (pharmacological exercise echocardiography or SPECT) and ECG analysis, along with the major adverse cardiovascular events (MACE) at patient follow-up. Studies were stratified based on functional imaging modality used. Primary outcome was a composite of all-cause death or myocardial infarction, and secondary outcome was the need for coronary revascularization. Random effects model was used to calculate risk ratios (RR), and heterogeneity among studies was assessed using the Higgins I2 value. Nine studies with a total of 23,715 patients were included. Primary end point was more common with discordant results with exercise stress echocardiography (RR 1.33, 95% confidence intervals [1.08-1.63]) or pharmacological SPECT (RR 6.53 95% CI [2.31-18.48]). CONCLUSIONS: Patients in the discordant exercise stress echocardiography and pharmacological SPECT groups were more likely to suffer the primary end point than those with a normal stress test. Discordant results should be interpreted carefully in the clinical context, given their prognostic impact based on the stress modality used.

Machine Learning in Cardiovascular Risk Prediction and Precision Preventive Approaches.

PURPOSE OF REVIEW: In this review, we sought to provide an overview of ML and focus on the contemporary applications of ML in cardiovascular risk prediction and precision preventive approaches. We end the review by highlighting the limitations of ML while projecting on the potential of ML in assimilating these multifaceted aspects of CAD in order to improve patient-level outcomes and further population health. RECENT FINDINGS: Coronary artery disease (CAD) is estimated to affect 20.5 million adults across the USA, while also impacting a significant burden at the socio-economic level. While the knowledge of the mechanistic pathways that govern the onset and progression of clinical CAD has improved over the past decade, contemporary patient-level risk models lag in accuracy and utility. Recently, there has been renewed interest in combining advanced analytic techniques that utilize artificial intelligence (AI) with a big data approach in order to improve risk prediction within the realm of CAD. By virtue of being able to combine diverse amounts of multidimensional horizontal data, machine learning has been employed to build models for improved risk prediction and personalized patient care approaches. The use of ML-based algorithms has been used to leverage individualized patient-specific data and the associated metabolic/genomic profile to improve CAD risk assessment. While the tool can be visualized to shift the paradigm toward a patient-specific care, it is crucial to acknowledge and address several challenges inherent to ML and its integration into healthcare before it can be significantly incorporated in the daily clinical practice.

One- versus two-specimen Xpert strategy to discontinue airborne isolation in suspected pulmonary tuberculosis: systematic review and meta-analysis.

BACKGROUND: Evaluation of a patient with suspected pulmonary tuberculosis (TB) involves initiation of airborne infection isolation (AII). However, guidelines detailing discontinuation of AII utilizing the Xpert MTB/RIF provide little clarity between use of one-specimen (1-Xpert') versus two-specimens (2-Xpert'). OBJECTIVES: To evaluate the diagnostic accuracy of one-Xpert versus two-Xpert strategy in guiding discontinuation of AII. METHODS: Data sources: PubMed, Embase, and EBSCO databases. STUDY ELIGIBILITY CRITERIA: Studies providing diagnostic accuracy data for one- versus two-Xperts in discontinuation of AII. PARTICIPANTS: Adult patients with suspected TB. TESTS: Xpert MTB/RIF on one- versus two-sputum specimens. Reference standard: Solid and liquid culture media. Assessment of risk of bias: Quality Assessment of Diagnostic Accuracy Studies tool was used. Methods of data synthesis: Meta-analysis was performed to calculate the pooled sensitivities and specificities using Stata 17.2. RESULTS: Four studies were included involving 1776 patients. A total of 68% were males, 36% were HIV positive, and 80% participants belonged to the United States. In patients with suspected pulmonary TB, 7% (95% CI, 6-9%) participants were found to have culture-positive MTB. For one-Xpert strategy, the pooled sensitivity was 86% (95% CI, 75-92%; I2, 1.05%) and specificity was 100% (95% CI, 99-100%; I2, 36%). Two-Xpert strategy had a pooled sensitivity of 92% (95% CI, 84-96%; I2, 16%) and a specificity of 100% (95% CI, 98-100%; I2, 27%). There was statistically significant difference between sensitivities of one-Xpert and two-Xpert strategies (p 0.05) with no statistically significant difference in their specificities. DISCUSSION: The results of this review must be interpreted in the context of a predominantly low-TB prevalence setting. Two-Xpert strategy has an incrementally higher sensitivity when compared with one-Xpert strategy with similar specificities between the two. Obtaining a second Xpert is crucial for individuals with a continued high suspicion for TB or those at a high risk of morbidity/mortality from TB.

Artificial Intelligence, Wearables and Remote Monitoring for Heart Failure: Current and Future Applications.

Substantial milestones have been attained in the field of heart failure (HF) diagnostics and therapeutics in the past several years that have translated into decreased mortality but a paradoxical increase in HF-related hospitalizations. With increasing data digitalization and access, remote monitoring via wearables and implantables have the potential to transform ambulatory care workflow, with a particular focus on reducing HF hospitalizations. Additionally, artificial intelligence and machine learning (AI/ML) have been increasingly employed at multiple stages of healthcare due to their power in assimilating and integrating multidimensional multimodal data and the creation of accurate prediction models. With the ever-increasing troves of data, the implementation of AI/ML algorithms could help improve workflow and outcomes of HF patients, especially time series data collected via remote monitoring. In this review, we sought to describe the basics of AI/ML algorithms with a focus on time series forecasting and the current state of AI/ML within the context of wearable technology in HF, followed by a discussion of the present limitations, including data integration, privacy, and challenges specific to AI/ML application within healthcare.

Influence of Iron Deficiency on Clinical and Haemodynamic Parameters in Pulmonary Arterial Hypertension Cohorts.

BACKGROUND: Iron deficiency (Fedef) has been shown to be common in patients with group 1 or pulmonary arterial hypertension (PAH). Several studies have shown a negative impact of Fedef on clinical and haemodynamic parameters of the disease, but data from individual studies have not been strong enough to lead to incorporation of the finding of Fedef into prognostic or therapeutic algorithms. The goal of this meta-analysis was to combine data from available studies to better define any associations between Fedef and established variables of prognostic importance in PAH. METHODS: A literature search identified nine studies with extractable data relevant to the study questions. The impact of Fedef upon the following parameters was evaluated: 6-minute walk distance (6MWD), WHO-functional class, N-terminal pro-brain natriuretic peptide (NT-proBNP) levels, echocardiography, and findings from right heart catheterisation (RHC). Pooled results were reported as mean difference or risk difference with 95% confidence intervals utilising a random effects modeling approach. RESULTS: Fedef in the PAH population was common (47% of cases) and was associated with cardiovascular dysfunction (lower tricuspid annular plane systolic excursion [TAPSE], elevated NT-proBNP, and lower mixed venous oxygen saturation) and with reduction in functional capacity (lower 6MWD and higher functional class). CONCLUSION: This meta-analysis strengthens the relationships between Fedef and several markers of poor outcome in PAH. Fedef in patients with PAH warrants further scrutiny and merits consideration as a cause of clinical deterioration. Even though causation and longitudinal relationships between Fedef and PAH could not be identified, effect of Fedef on factors that affect disease prognosis is noteworthy and worthy of more focussed studies.

A 72-Year-Old Woman With Dyspnea, Multiple Pulmonary Nodules, and Mediastinal Lymphadenopathy.

CASE PRESENTATION: A 72-year-old woman presented to our institution with gradually worsening shortness of breath and bilateral lower extremity edema of 3 weeks' duration. She had associated complaints of cough and intermittent hemoptysis. Her medical history was significant for hypertension and hypothyroidism. She was a former cigarette smoker with a 35 pack-year smoking history. She had no recent travel history and had a pet dog at home. Six months before the current hospitalization, evaluation for cough had revealed mediastinal lymphadenopathy at an outside institution. She underwent evaluation with an endobrachial ultrasound procedure at an outside facility 8 weeks before the current admission. The procedure demonstrated both acute and chronic inflammation, with one specimen showing few atypical cells on cytopathology and no growth on bacterial, fungal, and mycobacterial cultures. She was treated empirically with oral steroids for presumed sarcoidosis. However, this did not result in clinical benefit, and because of progressive symptoms, she presented to our institution.

Contemporary Applications of Machine Learning for Device Therapy in Heart Failure.

Despite a better understanding of the underlying pathogenesis of heart failure (HF), pharmacotherapy, surgical, and percutaneous interventions do not prevent disease progression in all patients, and a significant proportion of patients end up requiring advanced therapies. Machine learning (ML) is gaining wider acceptance in cardiovascular medicine because of its ability to incorporate large, complex, and multidimensional data and to potentially facilitate the creation of predictive models not constrained by many of the limitations of traditional statistical approaches. With the coexistence of "big data" and novel advanced analytic techniques using ML, there is ever-increasing research into applying ML in the context of HF with the goal of improving patient outcomes. Through this review, the authors describe the basics of ML and summarize the existing published reports regarding contemporary applications of ML in device therapy for HF while highlighting the limitations to widespread implementation and its future promises.

A Systematic Review of Reported Cases of Immune Thrombocytopenia after COVID-19 Vaccination.

With the recent outbreak of the COVID-19 pandemic and emergency use authorization of anti-SARS-CoV-2 vaccines, reports of post-vaccine immune thrombocytopenia (ITP) have gained attention. With this systematic review, we aim to analyze the clinical characteristics, therapeutic strategies, and outcomes of patients presenting with ITP after receiving COVID-19 vaccination. Medline, Embase, and Ebsco databases were systematically explored from inception until 1 June 2022. Case reports and case series investigating the association between the anti-SARS-CoV-2 vaccine and ITP were included. We found a total of 66 patients. The mean age of presentation was 63 years with a female preponderance (60.6%). Sixteen patients had pre-existing ITP. The mean time from vaccine administration to symptom onset was 8.4 days. More ITP events were triggered by mRNA vaccines (BNT162b2 (n = 29) > mRNA-1273 (n = 13)) than with adenoviral vaccines (ChAdOx1-S AstraZeneca (n = 15) > Ad26.COV2-S (n = 9)). Most of the patients were treated with steroids or IVIG, or both. The overall outcome was promising, with no reported deaths. Our review attempts to increase awareness among physicians while evaluating patients presenting with thrombocytopenia after receiving the vaccine. In our solicited opinion, the rarity of these events and excellent outcomes for patients should not change views regarding the benefits provided by immunization.

Thrombotic thrombocytopenic purpura (TTP) after COVID-19 vaccination: A systematic review of reported cases.

INTRODUCTION: With the advent of COVID-19 vaccines, hospitalization rates and progression to severe COVID-19 disease have reduced drastically. Most of the adverse events reported by the vaccine recipients were minor. However, autoimmune hematological complications such as vaccine-induced immune thrombotic thrombocytopenia (VITT), immune thrombocytopenic purpura (ITP) and TTP have also been reported post-COVID-19 vaccination. Given this, we sought to reflect on the existing cases of TTP, whether de novo or relapsing, reported after COVID-19 vaccination to further gain insight into any association, if present, and outcomes. METHODS: We searched PubMed, Embase, and Ebsco databases for published individual case reports on the occurrence or relapse of TTP after receiving any COVID-19 vaccine. A total of 23 articles (27 patients) were included in this qualitative analysis. RESULTS: The mean age for the patients who developed de novo TTP post-COVID-19 vaccination was 51.3 years. TTP episodes were seen mostly after BNT162b2 vaccine, followed by mRNA-1273 vaccine. All patients with immune TTP except one received plasma exchange (PLEX) and steroids. One patient passed away after two days of hospitalization, likely due to a sudden cardiovascular event. CONCLUSION: Our review underscores the importance of in-depth anamnesis before vaccination and outlines characteristics of predisposed individuals. Evaluation of post-vaccine thrombocytopenia must include the possibility of TTP given the associated fatality with this condition.

Emergence of Chronic Lymphocytic Leukemia During Admission for COVID-19: Cause or Coincidence?

Chronic lymphocytic leukemia (CLL) is the most common leukemia affecting the western adult population. While CLL is known to be a risk factor for morbidity and mortality from coronavirus disease 2019 (COVID-19), COVID-19 has not been shown to be a risk factor for the development of CLL. We report a case of a 55-year-old man who presented with COVID-19 pneumonia and developed overt CLL during hospitalization. Four other cases were culled from the literature. We discuss mechanistic possibilities for the unmasking of CLL in susceptible individuals with COVID-19.

Current and Future Applications of Artificial Intelligence in Coronary Artery Disease.

Cardiovascular diseases (CVDs) carry significant morbidity and mortality and are associated with substantial economic burden on healthcare systems around the world. Coronary artery disease, as one disease entity under the CVDs umbrella, had a prevalence of 7.2% among adults in the United States and incurred a financial burden of 360 billion US dollars in the years 2016-2017. The introduction of artificial intelligence (AI) and machine learning over the last two decades has unlocked new dimensions in the field of cardiovascular medicine. From automatic interpretations of heart rhythm disorders via smartwatches, to assisting in complex decision-making, AI has quickly expanded its realms in medicine and has demonstrated itself as a promising tool in helping clinicians guide treatment decisions. Understanding complex genetic interactions and developing clinical risk prediction models, advanced cardiac imaging, and improving mortality outcomes are just a few areas where AI has been applied in the domain of coronary artery disease. Through this review, we sought to summarize the advances in AI relating to coronary artery disease, current limitations, and future perspectives.

Acquired Hyperzincaemia Due to Zinc-Laden Denture Adhesives Leading to Hypocupraemia as a Cause of Neutropenia.

INTRODUCTION: Copper deficiency or hypocupraemia is a rare cause of anaemia and neutropenia. CASE DESCRIPTION: We hereby present the case of a 34-year-old female with gastric bypass surgery who presented with neutropenic fever, abdominal pain and diarrhoea, later found to have extended-spectrum beta-lactamase resistant Escherichia coli urinary tract infection and small bowel bacterial overgrowth syndrome, with her anaemia and neutropenia being caused by copper deficiency due to hyperzincaemia induced by using zinc denture adhesive cream. DISCUSSION: Various causes of copper deficiency have been recognized including, but not limited to, malnutrition, gastrectomy, gastric bypass surgery, protein-losing enteropathies (coeliac disease, tropical sprue), Wilson disease and Menkes syndrome. Copper deficiency caused by zinc overuse is not very prevalent. The haematologic abnormalities associated with copper deficiency are neutropenia, sideroblastic anaemia and/or pancytopenia. CONCLUSION: Because of its low prevalence and nonspecific haematologic and clinical manifestations, the diagnosis of zinc-induced copper deficiency (ZICD) can be missed. LEARNING POINTS: Zinc toxicity is a rare cause of hypocupraemia.The bone marrow and haematological manifestations of copper deficiency are not pathognomonic but include sideroblastic anaemia, pancytopenia or neutropenia.Early detection of hypocupraemia as a cause for neutropenia will improve morbidity and mortality by avoiding untoward infections due to neutropenia, neurological decline or unnecessary interventions.

A Late Presentation of COVID-19 Vaccine-Induced Myocarditis.

With the introduction of the coronavirus disease 2019 (COVID-19) mRNA vaccines, the incidence of severe infection has significantly decreased. While the vaccines have been shown to be effective and safe, there have been few case reports of acute myocarditis within 3-5 days following the second dose of the vaccine. We report a case of an elderly man who presented with acute-onset chest pain after three months of receiving the second dose of the mRNA vaccine. He was found to have acute myocarditis on cardiac magnetic resonance imaging (CMRI), which was attributed to exposure to the COVID-19 vaccine in the absence of any other risk factors. Our patient demonstrated quick resolution of symptoms and was discharged within 72 hours. We review the literature and summarize published case reports on COVID-19 vaccine-associated myocarditis. The present case report provides new evidence regarding the possible subacute presentation of myocarditis post-COVID-19 vaccine, and further highlights the favorable outcome in this newly described clinical entity.

Choroidal Metastasis as the Initial Presentation of Rectal Adenocarcinoma.

Choroidal metastasis from rectal cancer is a rare occurrence with limited literature on appropriate evidence-based treatment options. We describe the case of 44-year-old man who presented with left-sided painful vision loss who was found to have left choroidal and multiple lung metastasis from an unknown primary which was later found to be rectal adenocarcinoma. LEARNING POINTS: Ocular metastasis from colorectal cancer is rare with choroid being the most common site of involvement if it occurs.Ocular metastasis usually occurs as a part of generalized metastasis to multiple organ systems.Treatment options include systemic chemotherapy, radiation, bevacizumab and enucleation.

Diagnostic accuracy of non-contact infrared thermometers and thermal scanners: a systematic review and meta-analysis.

Infrared thermal screening, via the use of handheld non-contact infrared thermometers (NCITs) and thermal scanners, has been widely implemented all over the world. We performed a systematic review and meta-analysis to investigate its diagnostic accuracy for the detection of fever. We searched PubMed, Embase, the Cochrane Library, medRxiv, bioRxiv, ClinicalTrials.gov, COVID-19 Open Research Dataset, COVID-19 research database, Epistemonikos, EPPI-Centre, World Health Organization International Clinical Trials Registry Platform, Scopus and Web of Science databases for studies where a non-contact infrared device was used to detect fever against a reference standard of conventional thermometers. Forest plots and Hierarchical Summary Receiver Operating Characteristics curves were used to describe the pooled summary estimates of sensitivity, specificity and diagnostic odds ratio. From a total of 1063 results, 30 studies were included in the qualitative synthesis, of which 19 were included in the meta-analysis. The pooled sensitivity and specificity were 0.808 (95%CI 0.656-0.903) and 0.920 (95%CI 0.769-0.975), respectively, for the NCITs (using forehead as the site of measurement), and 0.818 (95%CI 0.758-0.866) and 0.923 (95%CI 0.823-0.969), respectively, for thermal scanners. The sensitivity of NCITs increased on use of rectal temperature as the reference. The sensitivity of thermal scanners decreased in a disease outbreak/pandemic setting. Changes approaching statistical significance were also observed on the exclusion of neonates from the analysis. Thermal screening had a low positive predictive value, especially at the initial stage of an outbreak, whereas the negative predictive value (NPV) continued to be high even at later stages. Thermal screening has reasonable diagnostic accuracy in the detection of fever, although it may vary with changes in subject characteristics, setting, index test and the reference standard used. Thermal screening has a good NPV even during a pandemic. The policymakers must take into consideration the factors surrounding the screening strategy while forming ad-hoc guidelines.

Facemasks for prevention of viral respiratory infections in community settings: A systematic review and meta-analysis.

BACKGROUND: There is paucity of evidence on the effectiveness of facemask use in COVID-19 in community settings. OBJECTIVES: We aimed to estimate the effectiveness of facemask use alone or along with hand hygiene in community settings in reducing the transmission of viral respiratory illness. METHODS: We searched PubMed and Embase for randomized controlled trials on facemask use in community settings to prevent viral respiratory illnesses published up to April 25, 2020. Two independent reviewers were involved in synthesis of data. Data extraction and risk-of-bias assessment were done in a standard format from the selected studies. Outcome data for clinically diagnosed or self-reported influenza-like illness (ILI) was recorded from individual studies. Pooled effect size was estimated by random-effects model for "facemask only versus control" and "facemask plus hand hygiene versus control." RESULTS: Of the 465 studies from PubMed and 437 studies from Embase identified from our search, 9 studies were included in qualitative synthesis and 8 studies in quantitative synthesis. Risk of bias was assessed as low (n = 4), medium (n = 3), or high (n = 1) risk. Interventions included using a triple-layered mask alone or in combination with hand hygiene. Publication bias was not significant. There was no significant reduction in ILI either with facemask alone (n = 5, pooled effect size: -0.17; 95% confidence interval [CI]: -0.43-0.10; P = 0.23; I2 = 10.9%) or facemask with handwash (n = 6, pooled effect size: (n=6, pooled effect size: -0.09; 95% CI: -0.58 to 0.40; P = 0.71, I2 = 69.4%). CONCLUSION: : Existing data pooled from randomized controlled trials do not reveal a reduction in occurrence of ILI with the use of facemask alone in community settings.

Clinical Profile and Outcome in Patients of Diabetic Foot Infection.

PURPOSE: The aim is to study the clinical profile and outcome of patients presenting with diabetic foot infections (DFI). METHODS: This was a prospective study recruiting patients >18 years of age, with DFI. All patients underwent a detailed history and clinical examination. Patients were classified as per the International Working Group on the Diabetic Foot -IDSA classification. The patients were followed up every month for 3 months. Clinical outcome was studied regarding the rate of amputations, readmissions, and mortality. RESULTS: There were 65 patients with a mean age of 58.49 ± 11.04 years with male predilection (83.08%). Mean duration of diabetes mellitus was 12.03 ± 6.96 years. Ulcer (92.31%) and discharge (72.31%) were the most common presenting complaints. Monomicrobial growth was present in 36 patients (55.38%). Majority of isolates were Gram-negative (71.43%). The most common isolates were Escherichia coli and Staphylococcus aureus (28.57% each). Mild, moderate, and severe DFI was present in 40%, 47.69%, and 12.31% of patients, respectively. Severe DFI was associated with poor ulcer healing (P = 0.02) and higher number of major amputations (P < 0.001). Minor amputations were most commonly associated with moderate and severe DFI. Severe DFI had the highest number of readmissions (P = 0.04). Patients undergoing minor amputations had a significant association with area of ulcer (P < 0.001). CONCLUSION: This study shows the predominance of monomicrobial growth and Gram-negative organisms in diabetic foot patients. With increase in the severity of DFI, there was increased rate of hospital readmissions, amputations (major and minor), and mortality. Dimensions of ulcer may have a bearing on rate of minor amputations.