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Objectives: Opioids play a significant role in the effective management of cancer-related pain. The COVID-19 lock down may have reduced access to opioids and caused a decline in the use of prescription of opioids among cancer survivors. This study compared opioid prescription rates among cancer survivors before and after the onset of COVID-19 pandemic using real-world electronic health records (EHR). Method(s): Cohort analyses of cancer patients using data from EHR database from the TriNetX, a global federated health research network across 76 healthcare organizations. We analyzed changes in prescription opioid use before (March 1, 2018, through March 1, 2019) and after onset of COVID-19 (April 01, 2020, through March 2021) among cancer survivors. The key outcome variable was any opioid prescription within 1 year of cancer diagnosis. One-to-one propensity score matching was used to balance the characteristics (age, sex, race, diagnoses including diabetes, hypertensive diseases, overweight, mood disorders, and visual disturbances) of the two cohorts. Data were analyzed using the TriNetX platform. Result(s): There were 1,502,143 cancer survivors before COVID-19 and 1,412,599 cancer survivors after the onset of COVID-19. The one-to-one propensity-score match yielded 1,382,561 cancer patients, mean age 64 at cancer diagnosis, and 73% were white. Percentage of opioid use among cancer patients declined from 35.6% before the COVID-19 to 35.1% after the onset of the pandemic (OR=0.976, 95% CI 0.971-0.981). Average number of opioid prescriptions within 1 year of cancer diagnosis declined from 5.7 before to 5.3 after the COVID-19 onset (p<0.001). Conclusion(s): Among cancer survivors, a small decline in prescription opioid use was observed after the onset of COVID-19 pandemic. Future studies are needed to distinguish the impact of revised guidelines, opioid prescription policy changes, and COVID-19 lock down on lower rates of prescription opioid use among cancer survivors.Copyright © 2023
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Objectives: Using a historical control or external control arm (ECA) to augment or replace a concurrent control arm in a randomized trial is a hot topic given the challenge of patient recruitment in rare diseases or during COVID-19 pandemic. The FDA released draft guidance in 2021 on effectiveness and safety submissions using real-world evidence. While the guidance focuses mainly on elements of study design and data source selection, there is a lack of consensus in the selection of appropriate statistical methods when constructing an ECA. This study discusses rigorous statistical methodology for ECA-supported trials in regulatory or HTA submissions. Method(s): Targeted literature reviews of statistical simulations comparing methods for ECA in statistical journals were performed. The articles compared commonly used ECA-construction and analysis methods were selected and summarized, including but not limited to propensity score (PS)-based matching, weighting, and stratification, and PS plus Bayesian integrated approaches. Result(s): Type I error, power, bias, and coverage probability are common criteria used to compare different methods. When imbalances only exist in known baseline covariates and the outcome distributions are the same between the trial concurrent control and ECA, the PS method alone or paired with commensurate prior yield almost unbiased estimates, good Type I errors, and coverage probability. PS plus Bayesian approaches have wider interval width and lower power compared with PS-only methods. When there is a change in the outcome distribution over time, the PS (matching or IPTW) and commensurate prior integrated methods yield the smallest biases among all methods. Conclusion(s): PS and Bayesian integrated methods outperformed the PS-only methods in terms of bias and Type I error when outcome distribution changed with current trial control. A "sweet spot" that balances all criteria through trial-specific simulations could provide the ideal setting of trial analyses plan based on specific trial design and scenarios.Copyright © 2023
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Objectives: Data about COVID-19 patients treated with veno-arterial-ECMO (VA-ECMO) is limited. Reported survival rates range from 27.9% to 77.8%, depending on VA-ECMO indication. A subgroup of patients suffers from circulatory failure due to a COVID-19 associated hyperinflammatory state (CovHI). In these patients, differentiation between inflammation and sepsis is difficult but important. In this retrospective case series, differential diagnoses of COVID-19 associated refractory circulatory failure and survival rates in different indications for VA-ECMO are investigated. Method(s): Retrospective analysis of 28 consecutive COVID-19 patients requiring VA-ECMO at the University Hospital Regensburg between March 2020 and May 2022. Specific treatment for COVID-19 was in accordance with respective guidelines. Mycotic infections were either invasive or met current definitions of COVID19-associated-pulmonary aspergillosis. Result(s): At VA-ECMO initiation, median age was 57.3 years (IQR: 51.4 - 61.8), SOFA score 16 (IQR: 13 - 17) and norepinephrine dosing 0.53mug/kg/min (IQR: 0.32 - 0.78). Virus-variants were: 61% wild-type, 14% Alpha, 18% Delta and 7% Omicron. Survival to hospital discharge was 39%. 17 patients were primarily supported with VA-ECMO only (survival 42%), 3 patients were switched from VV to VA-ECMO (survival 0%), and 8 patients were converted from VA to VAV or VV-ECMO (survival 50%). Indications for VA-ECMO support were pulmonary embolism (PE) (n=5, survival 80%), right heart failure due to secondary pulmonary hypertension (n=5, survival 20%), cardiac arrest (n=4, survival 25%), acute left heart failure (ALHF) (n=11, survival 36%) and refractory vasoplegia (n=3, survival 0%). Inflammatory markers at VA-ECMO initiation were higher in patients with ALHF or vasoplegia;in these patients a higher rate of invasive fungal infections (10/14, 71% vs. 4/14, 29%;p=0.023) compared to the other patients was found. Conclusion(s): Survival on VA-ECMO in COVID-19 depends on VA-ECMO indication, which should be considered in further studies and clinical decisions making. Circulatory failure due to vasoplegia should be considered very carefully as indication for VA-ECMO. A high rate of mycotic infections mandates an intense microbiological workup of these patients and must be considered as an important differential diagnosis to CovHI.
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Objectives: Treatment of severe respiratory distress syndrome (ARDS) due to COVID-19 by veno-venous extracorporeal membrane oxygenation (VV-ECMO) had a mortality of up to 70% in Germany. Many patients with COVID-19 need VV-ECMO support longer than 28 days (long-term VV-ECMO). Evidence on mortality, complications during intensive care, functional status after discharge and mortality-predictors for patients supported with long-term VV-ECMO is lacking. Method(s): Retrospective study of 137 consecutive patients treated with VV-ECMO for ARDS due to COVID-19 at University Hospital Regensburg from March 2020 to March 2022. Result(s): 38% (n=52;87% male) of patients needed longterm VV-ECMO support. In these, SOFA score (median [IQR]) at ECMO initiation was 9 [8-11], age 58.2 [50.6- 62.5] years, PaO2/FiO2-ratio 67 [52-88] mmHg, pCO262 [52-74] mmHg, Murray-Score 3.3 [3.0-3.6] and PEEP 15 [13 - 16] cmH2O. Duration of long-term support was 45 [35-65] days. 26 (50%) patients were discharged from the ICU. Only one patient died after hospital discharge. At VVECMO initiation, baseline characteristics did not differ between deceased and survivors. Complications were frequent (acute kidney injury: 31/52, renal replacement therapy: 14/52, pulmonary embolism: 21/52, intracranial hemorrhage 8/52, major bleeding 34/52 and secondary sclerosing cholangitis: 5/52) and more frequent in the deceased. Karnofsky index (normal 100) after rehabilitation was 70 [57.5-82.5]. Twelve of the 18 patients discharged from rehabilitation had a satisfactory quality of life according to their own subjective assessment. Four patients required nursing support. Mortality-predictors within the first 30 days on VV-ECMO only observed in those who deceased later, were: Bilirubin >5mg/dl for > 7 days, pulmonary compliance <10ml/mbar for >14 days, and repeated serum concentrations of interleukin 8 >150ng/L. Conclusion(s): Long-term extracorporeal lung support in patients with COVID-19 resulted in 50 % survival and subsequently lead to a satisfactory quality of life and functionality in the majority of patients. It should preferably be performed in experienced centers because of a high incidence of complications. Several findings during the early course were associated with late mortality but need validation in large prospective studies.
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Aim: During the coronavirus disease, a palliative approach was recommended for the management of endodontic emergencies. This retrospective cohort study was conducted to investigate the effectiveness of dexamethasone or ibuprofen-acetaminophen combination for pain management in endodontic emergencies. Material(s) and Method(s): One hundred and eight records of patients who presented to the emergency department with dental pain were evaluated retrospectively. Since interventional procedures were not performed during the pandemic period, Specific analgesics/antibiotics for the management of pain were preferred. A follow-up protocol with a questionnaire was developed to observe the effectiveness of palliative treatment and make changes if necessary. All participants received a questionnaire to rate the pain levels 6, 12, 18, 24, 48, and 72 hours after taking the drug. All data were collected from the patient file and assessed. After inclusion and exclusion criteria, 32 patients were included (n = 19, ibuprofen + acetaminophen;n = 13, dexamethasone). Data were analyzed using the chi-square test (P = 0.05). Result(s): In both groups, a significant decrease in pain was experienced immediately after medication and at 6, 12, and 18 hours, with no significant difference (P >.05). However, dexamethasone (Group II) resulted in lower pain levels than ibuprofen\acetaminophen (Group I) at 24 and 48 hours (P <.05) Discussion: Both dexamethasone and ibuprofen-acetaminophen can be good palliative choices in endodontic emergencies in pandemic conditions. However, at 24 and 48 hours, dexamethasone resulted in lower pain levels.Copyright © 2022, Derman Medical Publishing. All rights reserved.
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Objectives: It is important to predict the prognosis during hospital admission of Covid-19 patients. The purpose of this study was to see how CRP/ Albumin (CAR) and Platelet/Lymphocyte (PLR) ratios, obtained from patients in the intensive care unit (ICU) within the first 24 hours of their hospitalization with a Covid-19 diagnosis, predictmortality and how they correlated with acute physiology and chronic health evaluation (APACHE II) and sequential organ failure assessment (SOFA). Method(s): Using hospital records, records of 83 patients hospitalized in the ICU with a diagnosis of Covid-19 between 11.03.2020 and 01.01.2021 were retrospectively analyzed . Patients were divided into two groups discharged (Group I) and exits (ex) group (Group II). CAR and PLR were recorded during the first 24 hours of ICU admission, and APACHE II and SOFA scores were computed. The calculated CAR and PLR were correlated with APACHE II and SOFA scores and their association with mortality was investigated. Result(s): SOFA, APACHE II, PLO, and age were higher, and albumin was lower in patients in the mortal course (p<0.05). ROC analysis revealed that APACHE II and SOFA scores could be employed to estimate mortality. Conclusion(s): We believe that APACHE II and SOFA scores can be used to predict mortality in patients admitted to the ICU due to Covid-19, whereas CRP/Albumin and Platelet/Lymphocyte ratios cannot. Copyright © 2023 by The Cardiovascular Thoracic Anaesthesia and Intensive Care.
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A mortality prediction model can be a great tool to assist physicians in decision making in the intensive care unit (ICU) in order to ensure optimal allocation of ICU resources according to the patient's health conditions. The entire world witnessed a severe ICU patient capacity crisis a few years ago during the COVID-19 pandemic. Various widely utilized machine learning (ML) models in this research field can provide poor performance due to a lack of proper feature selection. Despite the fact that nature-based algorithms in other sectors perform well for feature selection, no comparative study on the performance of nature-based algorithms in feature selection has been conducted in the ICU mortality prediction field. Therefore, in this research, a comparison of the performance of ML models with and without feature selection was performed. In addition, explainable artificial intelligence (AI) was used to examine the contribution of features to the decision-making process. Explainable AI focuses on establishing transparency and traceability for statistical black-box machine learning techniques. Explainable AI is essential in the medical industry to foster public confidence and trust in machine learning model predictions. Three nature-based algorithms, namely the flower pollination algorithm (FPA), particle swarm algorithm (PSO), and genetic algorithm (GA), were used in this study. For the classification job, the most widely used and diversified classifiers from the literature were used, including logistic regression (LR), decision tree (DT) classifier, the gradient boosting (GB) algorithm, and the random forest (RF) algorithm. The Medical Information Mart for Intensive Care III (MIMIC-III) dataset was used to collect data on heart failure patients. On the MIMIC-III dataset, it was discovered that feature selection significantly improved the performance of the described ML models. Without applying any feature selection process on the MIMIC-III heart failure patient dataset, the accuracy of the four mentioned ML models, namely LR, DT, RF, and GB was 69.9%, 82.5%, 90.6%, and 91.0%, respectively, whereas with feature selection in combination with the FPA, the accuracy increased to 71.6%, 84.8%, 92.8%, and 91.1%, respectively, for the same dataset. Again, the FPA showed the highest area under the receiver operating characteristic (AUROC) value of 83.0% with the RF algorithm among all other algorithms utilized in this study. Thus, it can be concluded that the use of feature selection with FPA has a profound impact on the outcome of ML models. Shapley additive explanation (SHAP) was used in this study to interpret the ML models. SHAP was used in this study because it offers mathematical assurances for the precision and consistency of explanations. It is trustworthy and suitable for both local and global explanations. It was found that the features that were selected by SHAP as most important were also most common with the features selected by the FPA. Therefore, we hope that this study will help physicians to predict ICU mortality for heart failure patients with a limited number of features and with high accuracy.
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Introduction: The COVID-19 pandemic has imposed a large burden on our global medical systems, particularly in patients that would require emergency surgery. Method(s): This single centre study determined the perioperative outcomes of patients who underwent emergency surgery before and during the COVID-19 pandemic after using a propensity score matching analysis. Result(s): A decrease in the number of emergency surgeries performed during the pandemic was noted at 47.9%. Data showed that severe complications arose more frequently during the pandemic (pvalue<0.05). Furthermore, it arose more frequently in patients who had a concomitant COVID-19 infection. Age was directly proportional to the likelihood of developing of severe postoperative complications (pvalue<0.05). Undergoing cancer surgery and being classified as ASA IV increased the likelihood of developing severe postoperative complications (pvalue<0.05). Preoperative time was a significant factor for patients who underwent trauma and can- cer surgery during the pandemic since it was noted to be directly proportional to the likelihood of developing severe postoperative complications (pvalue<0.05). The mortality rate was significantly pronounced during the pandemic for patients who underwent benign and trauma surgeries (pvalue<0.05). Conclusion(s): Severe complications arose more frequently during the pandemic. Undergoing cancer surgery and being classified as ASA IV increased the likelihood of developing of severe postoperative complications. Age and Preoperative time were noted to be directly proportional to the development of severe postoperative complications particularly in trauma and cancer surgeries. The mortality rate was significantly more pronounced during the pandemic for patients who underwent benign and trauma surgeries especially with longer preoperative time.
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Aim: To determine the intraoperative Ramsay sedation score after dexmedetomidine infusion in patients undergoing perineal surgery. Study design: Descriptive study. Place and duration of study: Department of Anaesthesia, JPMC, Karachi from 13th February 2021 to 13th August 2021. Methodology: One hundred and seventy four patients who met the diagnostic criteria were enrolled. Result(s): The mean age was 46.51 years with the standard deviation of +/-10.87. 66 (37.9%) were male and 108 (62.1%) were female. Whereas, mean duration of surgery, Ramsay sedation score at 5 minutes, 15 minutes, 30 minutes, height, weight and BMI in our study was 1.41+/-0.40 hours, 1.72+/-0.44, 3.51+/-0.60, 4.57+/-0.62, 165.62+/-8.23 cm, 68.34+/-8.23 kg and 24.85+/-3.34 kg/m2 respectively. Conclusion(s): Intraoperative dexmedetomidine proved beneficial in perineal surgeries and could be served as a potent sedative drug.Copyright © 2023 Lahore Medical And Dental College. All rights reserved.
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Objectives: Implementation of venovenous extracorporeal membrane oxygenation (VVECMO) allowed survival of patients with severe respiratory failure associated with SARS-CoV-2 infection. However, VVECMO treatment is usually associated with long ICU stays, prolonged sedation, and neuromuscular blockage days. Functional disability, due to delirium and acquired muscle weakness, is frequently an inevitable burden causing long term disability. This study aims to analyse main characteristics of patients under ECMO due to COVID-19 pneumonia, their outcomes and functional status six months after ICU discharge. Method(s): Retrospective review of a prospectively collected database in an ECMO referral centre. All patients receiving VVECMO for SARS-CoV-2 infection were included. Epidemiological and clinical data were reviewed. Functional status at 6 months after ICU discharge was assessed with modified Rankin Scale (mRS). Result(s): Ninety-three patients were included (29% female). Median age was 54+/-12 years, mean SOFA was 5.7+/-2.9, mean SAPS II was 35.6+/-13.6. Mean time from intubation to cannulation was 5+/-5.6 days in 91 patients;awake-ECMO was performed in 2 patients. Mean ECMO run duration was 33.1+/-30 days (longest ECMO run was 194 days). A period of awake-ECMO was performed on 36.5% of patients, during 16.4+/-21.2 days. ICU-acquired weakness was diagnosed on 64.5% of patients and delirium on 63.4%. Mortality was 24.7% (23 patients) with only 1 patient deceased in hospital after ICU discharge. At 6 months follow-up, all patients were still alive and most of them (65.1%) were independent on all daily activities (mRS <= 2). Conclusion(s): Patients with severe COVID-19 treated with VVECMO support had very good functional outcomes at six-month follow-up. Despite long ICU length-of-stay, high incidence of delirium and acquired muscle weakness, full recovery at six-month post-ICU discharge was achievable in most patients.
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The novel coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).Mortality attributable to COVID-19 remains considerably high, with case fatality rates as high as 8-11%. Early medical intervention in patients who are seriously and critically ill with COVID-19 reduces fatal outcomes. Thus, there is an urgent need to identify biomarkers that could help clinicians determine which patients with SARS-CoV-2 infection are at a higher risk of developing the most adverse outcomes, which include intensive care unit (ICU) admission, invasive ventilation, and death. In COVID-19 patients experiencing the most severe form of the disease, tests of liver function are frequently abnormal and liver enzymes are found to be elevated. For this reason, we examine the most promising liver biomarkers for COVID-19 prognosis in an effort to help clinicians predict the risk of ARDS, ICU admission, and death at hospital admission. In patients meeting hospitalization criteria for COVID-19, serum albumin < 36 g/L is an independent risk factor for ICU admission, with an AUC of 0.989, whereas lactate dehydrogenase (LDH) values > 365 U/L accurately predict death with an AUC of 0.943.The clinical scores COVID-GRAM and SOFA that include measures of liver function such as albumin, LDH, and total bilirubin are also good predictors of pneumonia development, ICU admission, and death, with AUC values ranging from 0.88 to 0.978.Thus, serum albumin and LDH, together with clinical risk scores such as COVID-GRAM and SOFA, are the most accurate biomarkers in the prognosis of COVID-19.Copyright © 2021 Sociedad Medica del Hospital General de Mexico. Published by Permanyer.
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Background: The coronavirus disease 2019 (COVID-19) pandemic and its associated morbidities are a great global concern. Diabetes mellitus (DM) is associated with adverse clinical outcomes and high mortality in patients with COVID-19. Objective(s): This study examined the frequency of BM, newly diagnosed hyperglycemia, and their impacts on hospitalized patients with COVID-19. Method(s): This retrospective study examined 810 medical records of PCR-confirmed COVID-19 patients admitted to Razi Hospital, Ahvaz, Iran. The clinical presentations, severity, and impacts of COVID-19 were compared between patients with and without DM. Disease severity was determined based on the NEWS2 scoring system. Result(s): This study included 810 medical records of COVID-19 patients, of whom 326 had pre-existing DM, and 484 were non-DM. The rates of diabetes and newly diagnosed hyperglycemia were 40.2% and 11.2%, respectively. The most common underlying diseases were hypertension (35.3%), ischemic heart disease (17.9%), and chronic kidney disease (11.9%), which were higher in people with diabetes than non-diabetics. The rate of acute kidney injury was higher in patients with diabetes than in non-diabetics (30.7% vs. 19.2%;P < 0.001) and in patients with severe COVID-19 than in those whose disease was not severe (27.8% vs. 21.5%;P = 0.04). The rates of severe COVID-19 (46.3% vs. 34.7%;P = 0.093), ICU admission (40.7% vs. 27.4%;P = 0.012), and mortality (18.5% vs. 10.5%;P = 0.079) were higher in patients with newly diagnosed hyperglycemia than in euglycemic patients. Conclusion(s): This study showed that COVID-19 infection is linked with newly diagnosed hyperglycemia and pre-existing DM, both associated with severe COVID-19, more need for ICU admission, and mortality.Copyright © 2023, Author(s).
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Objectives: In patients with severe respiratory failure, invasive ventilation may deteriorate the pneumomediastinum and hypoxia. This study aimed to compare the mortality and the complications of the patients with coronavirus disease 2019 (COVID-19) related severe ARDS treated with invasive ventilation or veno-venous ECMO (VV-ECMO) to avoid intubation. We hypothesized that VV-ECMO support without prior intubation is a feasible alternative strategy to invasive ventilation. Method(s): This retrospective study evaluated patients with COVID-19 related severe respiratory failure and radiological evidence of pneumomediastinum. The primary outcome was intensive care unit (ICU) survival at 90 days. Result(s): Out of 347 patients with COVID-19 disease treated in our unit, 22 patients developed spontaneous pneumomediastinum associated with deterioration of respiratory function. In 13 patients (59%), invasive ventilation was chosen as initial respiratory support;in 9 patients (41%), VV-ECMO was chosen as initial respiratory support. The median age of the patients in the invasive ventilation group was 62 years (IQR: 49-69) compared to 53 years (IQR: 46-62) in ECMO group (P=0.31). No statistically significant difference in SAPS II score between the groups was observed (39.7 (IQR: 33.2-45.3) vs. 28.9 (IQR:28.4-34.6), P=0.06). No elevated fluid balance within the first 4 days was observed in the ECMO group compared to the invasive ventilation group (162 mL (IQR: -366-2000) vs. 3905 mL (IQR: 2068-6192), P=0.07). VV-ECMO as the initial strategy for supporting patients with severe respiratory failure and pneumomediastinum, was associated with lower 90 days mortality (HR: 0.33 95%-CI: 0.11-0.97, P= 0.04) compared to patients treated with invasive ventilation (Figure). Conclusion(s): VV-ECMO can be an alternative strategy to invasive ventilation for treating patients with severe respiratory failure and spontaneous pneumomediastinum. (Figure Presented).
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This paper describes my work for the Information Retrieval from Microblogs during Disasters.This track is divided into two sub-tasks. Task 1 is to build an effective classifier for 3-class classification on tweets with respect to the stance reflected towards COVID-19 vaccines.Task 2 is to devise an effective classifier for 4-class classification on tweets that can detect tweets that report someone experiencing COVID-19 symptoms.This paper proposes a classification method based on MLP classifier model.The evaluation shows the performance of our approach, which achieved 0.304 on F-Score in Task 1 and 0.239 on F-Score in Task 2. © 2022 Copyright for this paper by its authors.
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This paper aims to visualise three financial distress outlooks using computer simulations. The financial distress exposure for airport operations in Malaysia between 1991 and 2021 is given by Altman Z”-score and modelled by the multivariate generalized linear model (MGLM). Seven determinants contributing to the financial distress from literature are examined. The determinant series are fitted individually by using linear model with time series components and autoregressive integrated moving average models to forecast values for the next 10 financial years. Future short- to long-term memory effects following COVID-19 are apparent in time series plots. In the simulations, the MGLM procedure utilised Gaussian, gamma, and Cauchy probability distributions associated with expectations and challenges of doing business as well as uncertainties in the economy. The underlying trends of realistic, optimistic, and pessimistic financial distress outlooks insinuate that the increasing risk of financial distress of airport operations in Malaysia is expected to continue for the next decade.
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Happiness is vague and multifaceted, with a plethora of philosophers who have sought to define and understand how it works through the ages. This is the go-to phrase for many people when encouraging someone to live their best life within their means. This article uses the machine learning approach to explain and predict happiness scores. The contribution of this work has three parts: data understanding and cleaning, data analysis and visualization, and modeling and prediction. The following five prediction models are used: linear regression, random forest regressor, decision tree, Bayesian linear model, and Lasso Lars. GDP per capita, freedom to make life choices, and Life expectancy are significant determinants of happiness scores to predict future scores. This is not conclusive as unforeseen occurrences like pandemic, natural disasters, and economic meltdowns happen, even to the most stable countries. Thus, these scores change. Family is also important as we see a reasonable correlation between Social status and Happiness score, so, hold your loved ones dear. © 2023 Author(s).
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The study investigates the role of corporate sustainability disclosures in moderating the link between country-level uncertainties (economic policy uncertainty, political uncertainty and uncertainty due to climate change) and firms' risks (total risk, market risk, and default risk) in the worldwide tourism firms. We consider the volume of ESG (environmental, social and governance) activities disclosures by the firms as a proxy of corporate sustainability disclosures. The study also explores the link between sustainability disclosures and firms' risks to validate the risk-reduction hypothesis. The study further highlights the relevance of country-level uncertainties in increasing firms' risks. The findings indicate that corporate sustainability disclosures can assist in mitigating tourism firms' risks during periods of heightened country-level uncertainties. The study also documents the significance of sustainability disclosures in reducing the effect of uncertainties on tourism firms' risks during the COVID-19 period. The results validate the risk-reduction hypothesis indicating that firms' engagement in corporate sustainability practices facilitates risk mitigation efforts during periods of escalated external uncertainties. By demonstrating that firms that engage in sustainability practices and provide required disclosures are better equipped to manage risks during periods of increased uncertainty, the study provides valuable insights for industry stakeholders, including investors, policymakers, and firms themselves. [ FROM AUTHOR] Copyright of Journal of Sustainable Tourism is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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Introduction: Mucormycosis is a rare, severe fungal infection with an incidence of 0.005 to 0.17 per million.1 but incidence has risen recently, particularly in the Asian subcontinent, due to use of immunosuppression for Covid19.2 Presentations can vary and are classified into: rhino-orbito-cerebral, pulmonary, cutaneous, disseminated, renal and gastrointestinal. Risk factors include diabetes, immunosuppression, iron overload, malnutrition, and prematurity.1,3 Although mucormycosis has an extremely high mortality rate and disseminated infection is usually fatal, treatment options exist if diagnosed early and surgical debridement may be curative. Objective(s): We present a case of mucormycois in a female patient in her 40s who was immunosuppressed with methotrexate for rheumatoid disease. This case is discussed to increase awareness of critical illness caused by opportunistic invasive fungal infections in immunosuppressed patients and promote timely identification and management. Method(s): We detail the clinical context and management of a patient with mucormycosis and discuss relevant literature. Result(s): A female patient in her 40s who had been experiencing upper respiratory tract symptoms for several weeks, including cough and brown sputum, was admitted with a presumptive diagnosis of methotrexate toxicity after a full blood count performed by the general practitioner demonstrated pancytopenia. Initially, National Early Warning System 2 score (NEWS2) was 2 but became intensely hypertensive during blood transfusion and then profoundly shocked with an escalating NEWS2. Broad-spectrum antibiotics and fluconazole were commenced for neutropenic sepsis and the patient was referred to critical care in multiple organ failure. Computerised tomography (CT) scan of the chest, abdomen and pelvis showed "left upper lobe consolidation, which with neutropenia might represent an angioinvasive aspergillosis". She had multiple areas of skin discolouration and desquamation. Haematology and Infectious Diseases opinions were sought, and a bone marrow biopsy was performed which showed severe toxic effects consistent with sepsis/life threatening infection. Progressive proptosis was noted, and CT scan of her head was requested. Sadly, she was never stable enough for CT transfer. Beta D Glucan and aspergillus antigen serology was negative. Broncho-alveolar lavage demonstrated Candida albicans and then, later, Rhizopus arrhizus was isolated and anti-fungal treatment changed to voriconazole and then amphotericin B. Upon reviewing the notes in light of the positive culture for Rhizopus, the patient had likely been exhibiting symptomatic Mucormycosis sinus infection for some time prior to this admission with disseminated infection. The patient's condition continued to deteriorate and she sadly died. Conclusion(s): * The Early Warning Score significantly underestimated how unwell the patient was upon arrival in ED, a systems-based assessment would have demonstrated that the patient had multiple system dysfunction and significant potential to deteriorate suddenly despite having stable observations * The methotrexate level has no clinical value in diagnosing or refuting a diagnosis of methotrexate toxicity * A full examination of the immunosuppressed patient including ENT is a necessity when searching for a source of infection * Invasive fungal infections can cause multi-system symptoms and atypical presentations * As a greater proportion of patients have received systemic immunosuppression for Covid-19, vigilance for more unusual pathogens, including Mucormycosis by clinicians is advised.
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The picture fuzzy set (PFS) is a more frequent platform for describing the degree of positive, neutral, and negative membership functions that generalizes the concept of fuzzy sets (FSs) and intuitionistic fuzzy sets (IFSs). Neutrality is a crucial component of PFS, and the score function plays a crucial role in ranking the alternatives in decision-making situations. In the decision-making process, some researchers concentrate on the various aggregation operators' development while ignoring the development of score functions. This factor causes several errors in the existing score function. If there are two separate picture fuzzy numbers (PFNs), there should be two different scores or accuracy values. Some researchers failed to rank the alternatives when the score and accuracy values for various PFNs were equal. To overcome the shortcomings, we proposed the perfect score function in this paper for ranking PFNs and introduced strong and weak PFSs. The shortcoming of the existing score function in PFNs has been highlighted in this paper. Furthermore, the decision-making approach has been depicted based on the proposed score function, and real-world applications have been shown by ranking the COVID-19 affected regions to demonstrate its efficacy. [ FROM AUTHOR] Copyright of Journal of Intelligent & Fuzzy Systems is the property of IOS Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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Objectives: Severe acute respiratory syndrome-coronavirus 2/COVID-19 infection is still a global concern, with pregnant women are considered as vulnerable population. Until now, the characteristics of pregnant women in Indonesia who are infected with COVID-19, as well as pregnancy and neonatal outcomes, are still unknown. This study aims to obtain national data, which are expected to be useful for the prevention and management of COVID-19 in pregnant women in Indonesia. Method(s): There were 1,427 patients recruited in this retrospective multicenter study. This study involved 11 hospitals in 10 provinces in Indonesia and was carried out using secondary patient data from April 2020 to July 2021. COVID-19 severity was differentiated into asymptomatic-to-mild symptoms and moderate-to-severe symptoms. The collected data include maternal characteristics, laboratory examinations, imaging, pregnancy outcomes, and neonatal outcomes. Result(s): Leukocyte, platelets, basophil, neutrophils segment, lymphocytes, monocytes, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, alanine aminotransferase (ALT), aspartate aminotransferase (AST), C-reactive protein (CRP), urea, and creatinine were found to be significantly associated with severity differences (p < 0.05). Moderate-severe symptoms of COVID-19 also shown to have suggestive pneumonia findings on chest X-ray findings. Patients with asymptomatic-to-mild symptoms had significantly (p < 0.001) higher recovery rate, shorter hospital stay, less intensive care unit (ICU) admission, and had more vaginal delivery. Neonates from mother with mild symptoms also had significantly (p < 0.001) higher survival rate, higher birth weight, and higher APGAR score. Conclusion(s): Several laboratory and radiology components, as well as maternal and neonatal outcomes are related to the severity of COVID-19 in pregnant women in Indonesia.Copyright © The Author(s). 2023.