Early Identification Of Cases Research Articles

SUPER Score Contributes to Warning and Management in Early-Stage COVID-19

BackgroundSome COVID-19 patients deteriorate to severe cases with relatively higher case-fatality rates, which increases the medical burden. This necessitates identification of patients at risk of severe disease. Early assessment plays a crucial role in identifying patients at risk of severe disease. This study is to assess the effectiveness of SUPER score as a predictor of severe COVID-19 cases. MethodsWe consecutively enrolled COVID-19 patients admitted to a comprehensive medical center in Wuhan, China, and recorded clinical characteristics and laboratory indexes. The SUPER score was calculated using parameters including oxygen saturation, urine volume, pulse, emotional state, and respiratory rate. In addition, the area under the receiver operating characteristic curve (AUC), specificity, and sensitivity of the SUPER score for the diagnosis of severe COVID-19 were calculated and compared with the National Early Warning Score 2 (NEWS2). ResultsThe SUPER score at admission, with a threshold of 4, exhibited good predictive performance for early identification of severe COVID-19 cases, yielding an AUC of 0.985 (95% confidence interval [CI] 0.897–1.000), sensitivity of 1.00 (95% CI 0.715–1.000), and specificity of 0.92 (95% CI 0.775–0.982), similar to NEWS2 (AUC 0.984; 95% CI 0.895–1.000, sensitivity 0.91; 95% CI 0.587–0.998, specificity 0.97; 95% CI 0.858–0.999). Compared with patients with a SUPER score<4, patients in the high-risk group exhibited lower lymphocyte counts, interleukin-2, interleukin-4 and higher fibrinogen, C-reactive protein, aspartate aminotransferase, and lactate dehydrogenase levels. ConclusionsIn conclusion, the SUPER score demonstrated equivalent accuracy to the NEWS2 score in predicting severe COVID-19. Its application in prognostic assessment therefore offers an effective early warning system for critical management and facilitating efficient allocation of health resources.

Mortality amongst hospitalized COVID-19 cases by acquisition and pandemic wave in Wales, UK, February 2020–March 2022

Hospital populations are vulnerable to COVID-19, but the relative severity of hospital acquisition compared to community is unknown. We investigated differences in mortality between hospital and community acquired cases in Wales. We linked SARS-CoV-2 PCR tests from Feb 2020-Mar 2022 to hospital admissions, to identify likely nosocomial acquisition. We measured death from any cause 28-days post positive specimen (mortality), by acquisition. We used multivariable logistic regression to compare mortality by acquisition, adjusting for confounders, computing adjusted odds ratio (aOR) with 95% confidence intervals (95%CI). There were 25,263 COVID-19 hospital cases and 5490 (22%) deaths in the study period. Although significant in univariate analysis, adjustment for confounding showed no association with increased mortality in nosocomial cases compared to cases admitted with COVID-19 (aOR= 0.8, 95%CI= 0.7-0.8). Vaccination (aOR= 0.6, 95%CI= 0.5-0.7) and infection in later pandemic waves (aOR= 0.5, 95%CI= 0.4-0.6) were associated with lower mortality; older age (85+ vs <25 years: aOR= 76.4, 95%CI= 41.8-160.5) and male sex (aOR= 1.5, 95%CI= 1.4-1.6) were associated with higher mortality. One in five hospitalised COVID-19 cases died within a month of infection. Mortality in nosocomial cases was not worse than those admitted with COVID-19, maybe reflecting early identification of nosocomial cases through screening.

An Evaluation of the Hitit Index in Differential Diagnosis of Crimean-Congo Hemorrhagic Fever in the Emergency Department.

Background and Objectives: Crimean-Congo Hemorrhagic Fever (CCHF) is a viral zoonotic infection, which is seen over a wide geographic area. The mortality rate is in inverse proportion to the ability of patients to access healthcare services. Therefore, early identification of patients is extremely important. The aim of this study was to test the sensitivity and specificity of the Hitit Index in the differentiation of CCHF cases at the time of presentation at the Emergency Department and to evaluate the agreement of this index with molecular (CCHFV RNA) and/or serological diagnostic tests (ELISA-CCHF IgM). Materials and Methods: The patients included were those who presented at the Emergency Department (ED) with the complaint of a tick bite or those identified as potential CCHF cases as a result of complaints and/or laboratory findings. For cases that met the study inclusion criteria, the Hitit Index score was calculated automatically from the parameters included in the index formula uploaded to the automation system in the ED at the time of presentation. Through comparisons of the agreement of the Hitit Index with the CCHFV-RNA and/or IgM results the power of the Hitit Index for differentiation of CCHF cases in ED was evaluated. Results: The data of 273 patients were analyzed. There was a history of tick bite in 236 (86%) cases. Of the evaluated cases, 110 (40.2%) were hospitalized; CCHF positivity was determined in 72 (26.4%). The Hitit Index values calculated in ED and at 24 h after hospitalization were determined to be significant in the prediction of the CCHF cases (p < 0.001, AUC = 0.919 (0.887-0.951); p < 0.001, AUC = 0.902 (0.841-0.962). For a cut-off point of 0 of the Hitit Index evaluated in ED, the classification success was found to have a sensitivity of 75% and specificity of 88% (PPV-NPV). For a cut-off point of 0 of the Hitit Index evaluated at 24 h after hospitalization, the classification success was found to have a sensitivity of 79.7% and specificity of 84% (PPV-NPV). Conclusions: The defined form of the Hitit Index can be used in the differentiation of CCHF cases in ED with high sensitivity and specificity levels. Just as evaluation with the Hitit Index prevents unnecessary hospitalization, it can also contribute to reducing mortality rates with the early identification of CCHF cases.

Alcohol Sniff Test (AST): An Important Tool for Screening Post-Viral Olfactory Loss in Acute Flu-Like Dysfunction.

Olfactory disorders have a significant impact on patients' quality of life but are often underestimated in clinical practice. Upper respiratory tract infections (URTIs) are a common cause of olfactory loss. While most cases of olfactory loss due to URTIs are conductive and reversible, post-viral olfactory dysfunction (PVOD) persists despite symptom improvement. PVOD is attributed to damage to the olfactory epithelium and nerves or central olfactory pathway lesions. The Alcohol Sniff Test (AST) has been proposed as a tool to assess olfactory function in the acute phase and aid in differentiating PVOD from conductive disorders. This study aims to evaluate the effectiveness of the AST as a predictor of post-viral olfactory loss in patients with flu-like syndrome. An observational cross-sectional study was conducted among employees with flu-like syndrome at a tertiary hospital. Three groups were formed: flu-like syndrome with conductive disorder without COVID-19 (PVOD-), flu-like syndrome with neurosensory and/or central disorder due to COVID-19 (PVOD +), and an asymptomatic control group. The Alcohol Sniff Test was performed to assess olfactory function. Statistical analysis was conducted to evaluate the AST's performance. For a cut off of 10cm, 88.57% of PVOD + patients and 60.53% of PVOD - patients showed AST alteration, respectively (p = 0.013, OR = 5.05, 95% CI [1.48-17.25]). There was a statistically significant difference in the mean distance between the PVOD + group (4.35 ± 4.1cm) and the control group (20 ± 4.33cm) (p < 0.05). This relationship was also observed between the PVOD + and PVOD- groups (9cm ± 7.5) (p < 0.05) and between the PVOD- and control groups (p < 0.05). For a cut off of 10cm, the AST showed a sensitivity of 88% and specificity of 41%, resulting in an Odds Ratio of 9.7 (95% CI 3.3-28.1) (p < 0.001) and a Positive Predictive Value of 69.4% for PVOD. PVOD, including cases associated with COVID-19, is a prevalent cause of olfactory loss. The Alcohol Sniff Test demonstrated promising results in identifying PVOD in patients with flu-like syndrome. The test's simplicity and accessibility make it a valuable tool for early screening and identifying individuals who may benefit from prompt treatment. The Alcohol Sniff Test (AST) shows potential as an effective tool for screening post-viral olfactory loss in patients with flu-like syndrome. It can aid in early identification of PVOD cases and facilitate timely interventions to reduce the likelihood of persistent hyposmia.

Infrared Imaging of the Brain-Eyelid Thermal Tunnel: A Promising Method for Measuring Body Temperature in Afebrile Children.

(1) Infrared thermography of the inner canthus of the eye has emerged as a promising tool for temperature screening and fever diagnosis. Its non-invasive nature lends itself well to mass screening in diverse settings such as schools, public transport, and healthcare facilities. Swift and accurate temperature assessment plays a pivotal role in the early identification of potential fever cases, facilitating timely isolation, testing, and treatment, thereby mitigating the risk of disease transmission. Nonetheless, the reliability of this approach in the pediatric population, especially when compared to conventional thermometry methods, remains unexplored. This preliminary study aimed to evaluate the concordance between the temperature of the inner canthus of the eye (Tic,eye), referred to as the brain-eyelid thermal tunnel (BTT°), with axillary and tympanic methods in afebrile children. (2) Methods: A cohort of 36 children, matched in a 1:1 ratio for gender and age, underwent comprehensive assessments encompassing anthropometric data, blood pressure evaluations, axillary (Tax) and tympanic (Tty) temperature measurements, as well as BTT° infrared thermography. (3) Results: The findings revealed a high level of concordance among the tympanic, axillary, and BTT° measurement methods. Bland-Altman plots showed that the bias was minimal, and no statistically significant differences were observed when comparing BTT° with axillary (p = 0.136) and tympanic (p = 0.268) measurements. Passing-Bablok regression scatter plots further confirmed the agreement, aligning the fitted regression line closely with the identity line for both axillary versus BTT° and tympanic (Tty) versus BTT° comparisons. (4) Conclusions: This study holds significant implications for public health, especially in the context of infectious disease outbreaks such as COVID-19. BTT° infrared thermography of the inner canthus of the eye (Tic,eye) reliably measures body temperature in afebrile children in controlled settings; nevertheless, its practical application necessitates the adaptation of biothermodynamic parameters to accommodate diverse environmental conditions.

Handgrip strength deficit and time lag between symptom onset and starting of chemotherapy in pulmonary tuberculosis: A cross-sectional study in North India

Objectives: Wasting is the predominant systemic clinical manifestation of chronic diseases like tuberculosis (TB). Delay in diagnosis and therapy initiation may affect handgrip strength, severity and outcome of the disease. Limited data are available on this in the Indian context, despite a high prevalence of TB. This study aimed to estimate and correlate deficits in handgrip strength amongst sputum-positive and sputum-negative pulmonary TB patients in relation to the time lag between symptom onset and starting of antitubercular therapy (ATT). Materials and Methods: We conducted a cross-sectional study amongst newly diagnosed sputum-positive and sputum-negative pulmonary TB patients and age- and sex-matched apparently healthy volunteers. Handgrip strength of 341 newly diagnosed patients of TB was monitored within 1 week of starting ATT and analysed. Demographic details and clinical history of the participants were noted in the pre-designed form. The handgrip strength of 100 healthy volunteers was also taken for comparison. Results: The study findings suggest that deficits in handgrip strength amongst sputum-negative patients were more than sputum-positive patients in comparison to age- and sex-matched healthy controls. It took an average of 63 ± 27 days between the onset of symptoms and starting of ATT in sputum-negative patients in comparison to an average of 47 ± 12 days in sputum-positive patients. Conclusion: Early consultation by patients, rapid diagnosis of TB and the start of ATT, thereby decreasing the time lag between the symptom onset and start of ATT, may lead to a decreased deficit in handgrip strength with the improved overall health of patients. Extensive Information, Education and Communication activities and newer diagnostic modalities for early identification of cases and the start of chemotherapy are required for optimal management of TB patients.

Awareness Among Primary Care Physicians Regarding the Alarm Symptoms and Signs of Rhinosinusitis.

Background Rhinosinusitis is a common condition. Primary care physicians (PCPs) play a vital role in diagnosing and managing rhinosinusitis, including identifying alarm symptoms and signs. However, limited research exists on PCPs' awareness of these alarm symptoms. Objectives This study aimed to assess the awareness of PCPs in Saudi Arabia regarding the alarm symptoms and signs of rhinosinusitis and identify knowledge gaps. Methodology A descriptive cross-sectional study was conducted among 153 PCPs in Taif, Saudi Arabia. An online questionnaire covering demographic data and multiple-choice questions on alarm symptoms and signs of rhinosinusitis was administered. Knowledge level was assessed based on the score of the responses to knowledge items. Data analysis was performed using IBM SPSS software (IBM Corp., Armonk, NY). Results The study revealed a low awareness of alarm symptoms and signs of rhinosinusitis among PCPs. Knowledge gaps were observed in recognizing symptoms and appropriate referral pathways. Participants showed inadequate awareness of severe headaches, frontal swelling, anosmia, cacosmia, and nasal bleeding or crustation as alarm symptoms. The average knowledge score was 4.57 ± 1.91 out of 10. Conclusion The study highlights the need to improve PCP awareness of alarm symptoms and signs of rhinosinusitis in Saudi Arabia. Educational programs should be developed to address knowledge gaps and enhance understanding of guidelines, facilitating early identification and referral of severe cases and improving patient outcomes.

Development and validation of machine learning model for predicting treatment responders in patients with primary biliary cholangitis.

Ursodeoxycholic acid is the first-line treatment for primary biliary cholangitis, and treatment response is one of the factors predicting the outcome. To prescribe alternative therapies, clinicians might need additional information before deciphering the treatment response to ursodeoxycholic acid, contributing to a better patient prognosis. In this study, we developed and validated machine learning (ML) algorithms to predict treatment responses using pretreatment data. This multicenter cohort study included collecting datasets from two data samples. Data 1 included 245 patients from 18 hospitals for ML development, and was divided into (i) training and (ii) development sets. Data 2 (iii: test set) included 51 patients from our hospital for validation. An extreme gradient boosted tree predicted the treatment response in the ML model. The area under the curve was used to evaluate the efficacy of the algorithm. Data 1 showed that patients complying with the Paris II treatment response had significantly lower serum alkaline phosphatase and total bilirubin levels than those who did not respond. Three factors, total bilirubin, total protein, and alanine aminotransferase levels were selected as essential variables for prediction. Data 2 showed that patients complying with the Paris II criteria had significantly high prothrombin time and low total bilirubin levels. The area under the curve of extreme gradient boosted tree was good for (ii) (0.811) and (iii) (0.856). We demonstrated the efficacy of ML in predicting the treatment response for patients with primary biliary cholangitis. Early identification of cases requiring additional treatment with our novel ML model may improve prognosis.

Recent Outbreak of Monkeypox: Implications for Public Health Recommendations and Crisis Management in India.

Monkeypox is a rare and self-limiting disease that was eradicated globally through vaccination approximately forty years ago, following the eradication of smallpox. The purpose of this article is to explore the implications of the recent monkeypox outbreak on public health recommendations and crisis management in India. An overview of the consequences of the current monkeypox epidemic on public health, epidemiology, clinical findings, management, challenges, and existing strategies for this disease, along with recommendations are discussed. It is crucial to develop evidence-based recommendations for the diagnosis and treatment of monkeypox, as well as early case identification and contact tracing. To prevent the spread of infection, travelers from affected countries should be subjected to health testing and quarantine. In order to successfully control the outbreak, a multidisciplinary team should be established to manage the monkeypox virus at tertiary care facilities, and health workers with occupational exposure to the virus should be assessed and given management plans.

Reporting delays of chikungunya cases during the 2017 outbreak in Lazio region, Italy.

Emerging arboviral diseases in Europe pose a challenge due to difficulties in detecting and diagnosing cases during the initial circulation of the pathogen. Early outbreak detection enables public health authorities to take effective actions to reduce disease transmission. Quantification of the reporting delays of cases is vital to plan and assess surveillance and control strategies. Here, we provide estimates of reporting delays during an emerging arboviral outbreak and indications on how delays may have impacted onward transmission. Using descriptive statistics and Kaplan-Meyer curves we analyzed case reporting delays (the period between the date of symptom onset and the date of notification to the public health authorities) during the 2017 Italian chikungunya outbreak. We further investigated the effect of outbreak detection on reporting delays by means of a Cox proportional hazard model. We estimated that the overall median reporting delay was 15.5 days, but this was reduced to 8 days after the notification of the first case. Cases with symptom onset after outbreak detection had about a 3.5 times higher reporting rate, however only 3.6% were notified within 24h from symptom onset. Remarkably, we found that 45.9% of identified cases developed symptoms before the detection of the outbreak. These results suggest that efforts should be undertaken to improve the early detection and identification of arboviral cases, as well as the management of vector species to mitigate the impact of long reporting delays.

Pediatric multi-drug-resistant tuberculosis in Germany – diagnostic and therapeutic challenges of an “orphan disease”

Delay in diagnosing multidrug-resistant tuberculosis (MDR-pTB) in children prolongs time to effective treatment. Data on risk factors for pediatric MDR from low-incidence countries are scarce. Retrospective nationwide case–control study to analyze MDR-pTB cases in Germany between 2010 and 2020 in comparison to a drug-susceptible (DS)-pTB group. We included 52 MDR cases (24 tuberculosis (TB), 28 TB infection (TBI); mean age 7.3 years) and 56 DS cases (31 TB, 26 TBI; mean age 7.9 years). Groups were similar for sex, household size, and migration background. Compared to the DS group, more children with MDR were born in the Commonwealth of Independent States (CIS) (22% MDR-pTB vs. 13% DS-pTB, n.s.) and had more MDR index cases (94% MDR-pTB, 5% DS-pTB, p < 0.001). The interval between first healthcare contact and initiation of effective therapy was significantly longer in MDR-pTB (47 days) than in DS-pTB (11 days, p < 0.001), correlating with disease progression. Treatment for MDR-pTB was successful in 74%, but 22% experienced long-term adverse effects (e.g., hepatopathy, hearing loss).Conclusions: Close contact to MDR cases or birth in MDR-TB-high-incidence countries are risk factors for MDR-pTB. Early identification of potential MDR index cases by contact investigation, and susceptibility testing in children from high-burden MDR-TB countries are essential for timely diagnosis and treatment, reducing the severity of disease and treatment side effects.Trial Registration: Deutsches Register Klinischer Studien (https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00023817), DRKS00023817, 2020–09-08.What is Known:•Management of children with MDR-TB remains challenging due to difficulties in diagnosing MDR-TB (lack of information on MDR index case, lack of microbiological confirmation in paucibacillary disease).•Choice of treatment regimen and monitoring of side effects.What is New:•Children with an MDR-TB index or born in a MDR-TB-high-incidence country are at higher risk of developing MDR-TB in a low incidence country.•The time lag to initiate treatment in MDR-TB is longer than in DS-TB and MDR-TB treatment involves a higher risk of adverse effects in longer treatment regimens especially with injectables.

Detection of drug-resistant Mycobacterium tuberculosis in pericardial fluid culture and its correlation with cartridge based nucleic acid amplification test and adenosine deaminase activity

BackgroundPericardial effusion is the accumulation of fluid in the pericardial cavity. In nations with high tuberculosis (TB) load, TB is the most common cause of pericardial effusion. 1–2% of patients with pulmonary TB develop Pericardial TB worldwide. Multi-drug-resistant (MDR) TB, including extrapulmonary TB (EPTB) cases, are rising in number. Adenosine Deaminase (ADA) is an enzyme in lymphocytes and myeloid cells, which has certain immune functions in the body. ADA levels are increased in inflammatory conditions, like pleural, pericardial, or joint effusions, of bacterial etiology, granulomatous conditions, neoplasms, and autoimmune pathologies. TB is the only lymphocytosis involving disease with increased ADA levels. MDR EPTB is rare, but cases are on the rise, and tuberculous pericardial effusion is one such example. Hence, it is important to know the percentage of cases detected by a culture that can be identified by cartridge-based nucleic acid amplification test (CBNAAT), their resistance patterns, and to identify potential markers like ADA, which can help in early identification of cases. The objectives of this study were to identify the Mycobacterium tuberculosis (MTB) bacilli in culture, and correlate them with cartridge-based nucleic acid amplification test (CBNAAT) results and their drug-resistance, in the Pericardial tubercular effusion, and to find if Adenosine Deaminase (ADA) levels can be used as a predictor of the presence of MTB in pericardial fluid. MethodologyWe enrolled 52 patients with moderate to large tuberculous pericardial effusion, based on pericardial fluid analysis, CBNAAT, and culture methods, between January 2021 and December 2021. ResultsThe mean age of the patients was 41.85 + 17.88 years, with a median of 38 years. Males made up 57.7% of the total patients. MTB was detected in 16 (30.8%) patients in the CBNAAT evaluations. 14 (87.5%) of the CBNAAT-positive TB patients were sensitive to Rifampicin, whereas the remaining 2 (12.5%) were resistant to Rifampicin on CBNAAT. MTB was found to be growing in 8 (15.38%) drug sensitivity test cultures. Out of these 8, 6 were sensitive to first-line drugs, whereas 2 were resistant to both Isoniazid and Rifampicin. The presence of cough was found to have a significant difference between CBNAAT-detected MTB positive and negative patients (p = 0.020), whereas an insignificant difference was found for the presence of hypertension, diabetes mellitus, obesity, dyspnea, or fever. There was also an insignificant difference between the number of patients positive for the Tuberculin skin test, between the two groups. ADA was significantly higher in the MTB-detected CBNAAT group (85.91 + 37.60U/L vs 39.78 + 24.31U/L, p = 0.005), whereas the total leukocyte count, lymphocytes, neutrophils, random blood sugar levels, and serum protein levels had no significant difference. The area under the Receiver Operator Curve (CBNAAT positive: dependent variable; ADA: test result variable) was 0.854 (null hypothesis rejected), with a standard error of 0.078. ConclusionsCulture is the gold standard method to diagnose tuberculosis. Detection of MTB on pericardial fluid culture is very uncommon, though in our study, culture came out positive in 16% of patients, and 4% were resistant to rifampicin and isoniazid. Higher ADA levels in pericardial fluid are an indicator of tuberculous pericardial effusion.

COVID-19 Contact Tracing Experience at a Tertiary Healthcare Center in Saudi Arabia.

Introduction As of May 2023, the end of the pandemic, the cumulative number of COVID-19 cases reached more than 841,000 cases. Healthcare workers (HCWs) especially have been at the frontline during this pandemic and are at a higher chance of contracting COVID-19. Approximately half of all high-risk exposures were to healthcare personnel with COVID-19. While several tools for contact tracing were developed for the general public, contact tracing for infectious diseases in the healthcare setting is limited, and global testing of HCWs, or in-hospital digital tracing, is not performed in most facilities. The King Faisal Specialist Hospital and Research Center (KFSH&RC) collaborated with the Infection Control and Health Information Technology Affairs (HITA)to create an automated COVID-19 contact tracing tool specifically for HCWs who worked at the institute. This study aims to describe the contact tracing experience at KFSH&RC. Methods A retrospective study was conducted to describe the use of an automated tool that was developed to assist in the contact tracing process and that was to be used by KFSH&RC employees who had been in contact with a COVID-19-positiveindividual. This tool is utilized for the early identification of possible COVID-19 cases and risk stratification of the exposed individuals. The tool can be accessed through the KFSH&RC website; it also collects information about the COVID-19 exposure rate among the different departments such as administration, capital projects/facilities, and healthcare at a tertiary care hospital in Riyadh, Saudi Arabia Results The tool has been utilized 7,353 times by contact cases. Approximately 7% of those tested later developed a COVID-19 infection. When assessing the positivity rates per department, The Environmental Services Department had the highest positivity rate of 28.21%, followed by Health Information Technology and Analytics (HITA), and then the Central Transportation Department. Conclusion This study acts as the first of its kind to describe the successful use of the healthcare contact tracing system in one of Saudi Arabia's largest hospitals (KFSH&RC) and describe the infection trends in different departments of the hospital. Through the tracing system, the departments with the highest COVID-19 infection occurrences at the hospital were identified in a timely manner, and safety protocols were implemented.

A Retrospective Study on Smell Dysfunction in COVID-19 Patients Presenting to a Tertiary Care Teaching Hospital in Northern India

Introduction: The smell dysfunction in COVID-19 patients has remained an unexplained topic. The blood parameters’ variability in COVID-19 patients with anosmia has been studied in few literatures. The study is aimed to find the association of anosmia with the blood grouping and C-reactive protein (CRP) levels in coronavirus-infected patients. Materials and Methods: Database from Medical Records Department of a Tertiary Care Teaching Hospital in Northern India was searched from July 2020 to December 2020. Every fifth file was selected using the stratified random sampling. Laboratory-confirmed COVID-19 cases by reverse transcription-polymerase chain reaction files were included. Blood grouping and CRP levels were assessed and statistically correlated. Results: A total of 103 patients of coronavirus-associated infection with anosmia were included among which 52 (50.48%) patients were from moderate category of AIIMS-ICMR joint task Force’s clinical guidelines. A total of 44 (42.71%) patients had moderate levels of elevated CRP. The blood Group B-type was found most commonly in 35 (33.98%) patients. The correlation of severity of COVID-19 infection with CRP was found to be statistically significant (Chi-square test statistic was 31.203 and P = 0.00023) in patients presenting with smell dysfunction. Conclusion: Anosmia was found to a suggestive symptom for the early identification of coronavirus-infected cases. In this study, CRP levels showed statistically significant association with anosmia in COVID-19 patients. Predilection for specific blood groups serves as platform for further research.

The effect of TB patient delay on loss to follow-up in Portugal.

BACKGROUND: Early identification of TB cases, followed by treatment to completion, are essential for controlling and preventing the disease. Previous studies have found some factors associated with both loss to follow-up (LTFU) and patient delay. We aim to build a causal model to investigate the association between TB patient delay and LTFU.METHODS: Pulmonary TB cases were identified using the national surveillance system in Portugal between 2008 and 2017. A directed acyclic graph was used to identify the minimal set of variables to adjust for when studying the association between delay (exposure) and LTFU (outcome). Crude and adjusted hazard were estimated using Cox regression.RESULTS: Nearly 4% of the patients did not follow up treatment. There was no association between patient delay and LTFU, even after adjustment with the minimal set of covariates. Factors associated with a higher risk of LTFU were being younger, being unemployed, living in urban areas, having HIV and the abuse of alcohol and drugs.CONCLUSION: Patient delay was not associated with LTFU, while social conditions were. Future research should investigate the underlying reasons why patients discontinue TB treatment and use these findings to develop targeted interventions that can support patients in completing their treatment regimen.

Diabetic Retinopathy Classification using Transfer learning

Diabetic Retinopathy (DR) is an eye illness that impacts individuals who have diabetes and damages their retina over time, eventually causing blindness. Due to lesions in the retina that are formed because of retinal blood vessel rupture, it impairs vision and, in the worst-case scenario, results in severe blindness. To prevent severity and to lessen challenges in identifying tiny lesions throughout the disease's advanced stages, it is now crucial to diagnose the condition early as, it manifests itself without any symptoms. Even ophthalmologists find it challenging and time-consuming to identify this condition. Early DR case identification and classification is essential for delivering the required medical care. This study proposes applying deep learning techniques to detect DR in retinal fundus images. The data acquired for this process may be incomplete and imbalanced. Data augmentation balances the data and increase the quantity of retinal images. As deep-learning algorithms need more data to process, DCGAN Augmentation technique is employed. The CNN (Convolutional Neural Network) methods, specifically the VGG16 and DenseNet121 architectures, are employed for DR early detection in order to let patients to receive therapy at the appropriate time.

Infection prevention and control for COVID-19 response in the Rohingya refugee camps in Bangladesh: an intra-action review

BackgroundInfection Prevention and Control (IPC) is critical in controlling the COVID-19 pandemic and is one of the pillars of the WHO COVID-19 Strategic Preparedness and Response Plan 2020. We conducted an Intra-Action Review (IAR) of IPC response efforts to the COVID-19 pandemic in Cox's Bazar, Bangladesh, to identify best practices, challenges, and recommendations for improvement of the current and future responses.MethodsWe conducted two meetings with 54 participants purposively selected from different organizations and agencies involved in the frontline implementation of IPC in Cox's Bazar district, Bangladesh. We used the IPC trigger questions from the WHO country COVID-19 IAR: trigger question database to guide the discussions. Meeting notes and transcripts were then analyzed manually using content analysis, and results were presented in text and quotes.ResultsBest practices included: assessments, a response plan, a working group, trainings, early case identification and isolation, hand hygiene in Health Facilities (HFs), monitoring and feedback, general masking in HFs, supportive supervision, design, infrastructure and environmental controls in Severe Acute Respiratory Infection Isolation and Treatment Centers (SARI ITCs) and HFs and waste management. Challenges included: frequent breakdown of incinerators, limited PPE supply, inconsistent adherence to IPC, lack of availability of uniforms for health workers, in particular cultural and gender appropriate uniforms and Personal Protective Equipment (PPE). Recommendations from the IAR were: (1) to promote the institutionalization of IPC, programs in HFs (2) establishment of IPC monitoring mechanisms in all HCFs, (3) strengthening IPC education and training in health care facilities, and (4) strengthen public health and social measures in communities.ConclusionEstablishing IPC programmes that include monitoring and continuous training are critical in promoting consistent and adaptive IPC practices. Response to a pandemic crisis combined with concurrent emergencies, such as protracted displacement of populations with many diverse actors, can only be successful with highly coordinated planning, leadership, resource mobilization, and close supervision.

Monkeypox: A New Challenge for Global Health System?

The COVID-19 pandemic, starting in 2020, has presented a major challenge in terms of early diagnosis and the subsequent containment and management of severe cases. The spread of viruses such as monkeypox in non-endemic countries is now creating new difficulties for healthcare professionals. Proper case definition and clinical examination are crucial for the early identification of suspected cases. For this reason, we performed a review of the literature in order to report the first signs, which are useful for healthcare providers for early case identification. Since 2022 to date, 86,930 laboratory-confirmed cases and 1051 probable cases have been reported worldwide, and of these, 116 were fatal cases and, for the first time, most of the cases were registered in countries that have not historically reported monkeypox and that lack direct or immediate epidemiological links to areas of West or Central Africa where the disease is endemic. Patients with Monkeypox experience prodromal symptoms, such as fever, fatigue, headache, muscle aches, and a rash after an incubation period of 5-21 days. The disease is usually self-limiting within 2-4 weeks but can lead to complications, such as pneumonia, encephalitis, kidney injury, and myocarditis in children, pregnant individuals, and those with weakened immune systems. The case-fatality ratio is between 1 and 10%. Today, prevention campaigns and the control of human monkeypox are the best weapons to prevent infection and stop transmission. Prevention strategies, such as avoiding contact with sick or dead animals, and the proper preparation of all foods containing animal meat or parts, should be adopted. Furthermore, close contact with infected people or contaminated materials should be avoided to prevent human-to-human transmission.

Blockchain-enabled healthcare monitoring system for early Monkeypox detection.

The recent emergence of monkeypox poses a life-threatening challenge to humans and has become one of the global health concerns after COVID-19. Currently, machine learning-based smart healthcare monitoring systems have demonstrated significant potential in image-based diagnosis including brain tumor identification and lung cancer diagnosis. In a similar fashion, the applications of machine learning can be utilized for the early identification of monkeypox cases. However, sharing critical health information with various actors such as patients, doctors, and other healthcare professionals in a secure manner remains a research challenge. Motivated by this fact, our paper presents a blockchain-enabled conceptual framework for the early detection and classification of monkeypox using transfer learning. The proposed framework is experimentally demonstrated in Python 3.9 using a monkeypox dataset of 1905 images obtained from the GitHub repository. To validate the effectiveness of the proposed model, various performance estimators, namely accuracy, recall, precision, and F1-score, are employed. The performance of different transfer learning models, namely Xception, VGG19, and VGG16, is compared against the presented methodology. Based on the comparison, it is evident that the proposed methodology effectively detects and classifies the monkeypox disease with a classification accuracy of 98.80%. In future, multiple skin diseases such as measles and chickenpox can be diagnosed using the proposed model on the skin lesion datasets.

Atypical mucosal lesions may help in the early diagnosis of monkeypox

Since May 2022, monkeypox has been gradually spreading across countries. In past reports and treatment consensus, monkeypox is most widely known for its characteristic skin lesions, which are hard, spherical rashes that appear as herpes and pustules and are widely distributed centrifugally over all parts of the body. Prior to the appearance of the rash, carriers of monkeypox are likely to spread the virus to more susceptible people. Attention to the early atypical mucosal manifestations of monkeypox allows for early identification of potential cases of monkeypox, thereby controlling the further spread of the epidemic.