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Background: Poliomyelitis is always a great concern in Pakistan and is a public health emergency. COVID‐19 and recent floods have increased the challenge. Aim: This article highlights the situation of polio in Pakistan and also recommends several steps to eradicate the disease as early as possible. Methodology: Selected articles were selected from electronic databases such as PubMed, Google Scholar, and Scopus using keywords such as Wild Poliovirus, Vaccine Derived Polio Infection, Acute Flaccid Paralysis, Vaccine, and Pakistan. Result: Polio infection has two types, wild poliovirus and vaccine‐derived polio infection. 2019 and 2020 were a challenging time as cases were increased at that time in Pakistan. Acute flaccid paralysis is the most common complication of this disease. The maximum cases of polio are being reported from Khyber Pakhtunkhwa. Conclusion: A special public health importance should be given in this province. Regular vaccination and strict surveillance are important. It is also important to spread awareness among the people. Early identification and timely diagnosis are very important. Early diagnosis, proper timely treatment, vaccination, awareness, and community‐based research will help Pakistan to eradicate this disease as early as possible. [ABSTRACT FROM AUTHOR]

Background: The highly arrhythmogenic nature of cardiac sarcoidosis (CS) leads to high morbidity and mortality, the rates of which may be higher in COVID-19 patients. This study aimed to evaluate the outcomes of CS patients admitted to hospitals with COVID-19., Methods: The study utilised the 2020-2021 National Inpatient Sample database, examining primary COVID-19 cases in adults aged older than or equal to 18 years. Those with CS were identified using ICD-10 code "D86.85" and compared with and without propensity matching (1:10) to those without CS for baseline characteristics and primary outcomes of acute kidney injury (AKI), use of mechanical ventilation, cardiac arrest and mortality., Results: In total, 2 543 912 COVID-19 cases were identified. Before propensity matching, CS patients were more likely to be younger (58.0 vs. 64.0 years, P <0.01), male (64.0% vs. 52.6%, P =0.011), of Black ethnicity (60.0% vs. 15.9%, P <0.01), exhibit higher Charlson Comorbidity Index (CCI) scores (3.00 vs. 1.00, P <0.01) and had a higher incidence of in-hospital cardiac arrest (aOR 2.649, 95% CI 1.366-5.134, P =0.004). After propensity matching (CS, N =95; non-CS, N =875), those with CS were at a statistically significant reduced risk of AKI (aOR 0.484, P =0.01); however, the outcomes of death, cardiac arrest, mechanical ventilation, length of stay (LOS) and healthcare costs did not reach significance., Conclusion: In a propensity-matched cohort admitted with COVID-19, CS patients had a reduced risk of AKI, but comparable LOS, rates of cardiac arrest, mechanical ventilator use, and mortality. Future research is warranted to develop evidence-based guidelines for managing COVID-19 in patients with CS., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Globally, cardiovascular diseases take the lives of over 17 million people each year, mostly through myocardial infarction, or MI, and heart failure (HF). This comprehensive literature review examines various aspects related to the diagnosis, prediction, and prognosis of HF in the context of machine learning (ML). The review covers an array of topics, including the diagnosis of HF with preserved ejection fraction (HFpEF) and the identification of high-risk patients with HF with reduced ejection fraction (HFrEF). The prediction of mortality in different HF populations using different ML approaches is explored, encompassing patients in the ICU, and HFpEF patients using biomarkers and gene expression. The review also delves into the prediction of mortality and hospitalization rates in HF patients with mid-range ejection fraction (HFmrEF) using ML methods. The findings highlight the significance of a multidimensional approach that encompasses clinical evaluation, laboratory assessments, and comprehensive research to improve our understanding and management of HF. Promising predictive models incorporating biomarkers, gene expression, and consideration of epigenetics demonstrate potential in estimating mortality and identifying high-risk HFpEF patients. This literature review serves as a valuable resource for researchers, clinicians, and healthcare professionals seeking a comprehensive and updated understanding of the role of ML diagnosis, prediction, and prognosis of HF across different subtypes and patient populations., Competing Interests: No conflicts of interest.Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Dengue fever (DF) is an arthropod-borne viral infection caused by four serotypes of dengue virus (DENV 1-4) transmitted to the host by the vector mosquito Aedes , which causes fever, vomiting, headache, joint pain, muscle pain, and a distinctive itching and skin rash, ultimately leading to dengue hemorrhagic fever and dengue shock syndrome. The first case of DF in Pakistan was documented in 1994, but outbreak patterns began in 2005. As of 20 August 2022, Pakistan has 875 confirmed cases, raising alarming concerns. Misdiagnosis due to mutual symptoms, lack of an effective vaccine, the weakened and overburdened health system of Pakistan, irrational urbanization, climate change in Pakistan, insufficient waste management system, and a lack of awareness are the significant challenges Pakistan faces and result in recurrent dengue outbreaks every year. The recent flood in Pakistan has caused massive destruction, and stagnant dirty water has facilitated mosquito breeding. Sanitization and spraying, proper waste management, an adequate and advanced diagnostic system, control of population size, public awareness, and promotion of medical research and global collaboration, especially amidst flood devastation, are recommended to combat this deadly infection in Pakistan. This article aims to comprehensively review the year-round DF in Pakistan, highlighting the surge amidst ongoing flood havoc and the coronavirus disease 2019 pandemic., Competing Interests: None declared by any authors involved in the manuscript.Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article, (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)