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1.
Scand J Trauma Resusc Emerg Med ; 28(1): 106, 2020 Oct 27.
Article in English | MEDLINE | ID: covidwho-2098375

ABSTRACT

BACKGROUND: Novel coronavirus disease 2019 (COVID-19) is a global public health emergency. Here, we developed and validated a practical model based on the data from a multi-center cohort in China for early identification and prediction of which patients will be admitted to the intensive care unit (ICU). METHODS: Data of 1087 patients with laboratory-confirmed COVID-19 were collected from 49 sites between January 2 and February 28, 2020, in Sichuan and Wuhan. Patients were randomly categorized into the training and validation cohorts (7:3). The least absolute shrinkage and selection operator and logistic regression analyzes were used to develop the nomogram. The performance of the nomogram was evaluated for the C-index, calibration, discrimination, and clinical usefulness. Further, the nomogram was externally validated in a different cohort. RESULTS: The individualized prediction nomogram included 6 predictors: age, respiratory rate, systolic blood pressure, smoking status, fever, and chronic kidney disease. The model demonstrated a high discriminative ability in the training cohort (C-index = 0.829), which was confirmed in the external validation cohort (C-index = 0.776). In addition, the calibration plots confirmed good concordance for predicting the risk of ICU admission. Decision curve analysis revealed that the prediction nomogram was clinically useful. CONCLUSION: We established an early prediction model incorporating clinical characteristics that could be quickly obtained on hospital admission, even in community health centers. This model can be conveniently used to predict the individual risk for ICU admission of patients with COVID-19 and optimize the use of limited resources.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Coronavirus Infections/therapy , Hospitalization , Intensive Care Units , Pneumonia, Viral/epidemiology , Pneumonia, Viral/therapy , Adult , Aged , COVID-19 , China , Coronavirus Infections/diagnosis , Female , Humans , Logistic Models , Male , Middle Aged , Nomograms , Pandemics , Pneumonia, Viral/diagnosis , Retrospective Studies , Risk Assessment , SARS-CoV-2
2.
Scand J Trauma Resusc Emerg Med ; 28(1): 66, 2020 Jul 13.
Article in English | MEDLINE | ID: covidwho-2098371

ABSTRACT

BACKGROUND: There is a need for validated clinical risk scores to identify patients at risk of severe disease and to guide decision-making during the covid-19 pandemic. The National Early Warning Score 2 (NEWS2) is widely used in emergency medicine, but so far, no studies have evaluated its use in patients with covid-19. We aimed to study the performance of NEWS2 and compare commonly used clinical risk stratification tools at admission to predict risk of severe disease and in-hospital mortality in patients with covid-19. METHODS: This was a prospective cohort study in a public non-university general hospital in the Oslo area, Norway, including a cohort of all 66 patients hospitalised with confirmed SARS-CoV-2 infection from the start of the pandemic; 13 who died during hospital stay and 53 who were discharged alive. Data were collected consecutively from March 9th to April 27th 2020. The main outcome was the ability of the NEWS2 score and other clinical risk scores at emergency department admission to predict severe disease and in-hospital mortality in covid-19 patients. We calculated sensitivity and specificity with 95% confidence intervals (CIs) for NEWS2 scores ≥5 and ≥ 6, quick Sequential Organ Failure Assessment (qSOFA) score ≥ 2, ≥2 Systemic Inflammatory Response Syndrome (SIRS) criteria, and CRB-65 score ≥ 2. Areas under the curve (AUCs) for the clinical risk scores were compared using DeLong's test. RESULTS: In total, 66 patients (mean age 67.9 years) were included. Of these, 23% developed severe disease. In-hospital mortality was 20%. Tachypnoea, hypoxemia and confusion at admission were more common in patients developing severe disease. A NEWS2 score ≥ 6 at admission predicted severe disease with 80.0% sensitivity and 84.3% specificity (Area Under the Curve (AUC) 0.822, 95% CI 0.690-0.953). NEWS2 was superior to qSOFA score ≥ 2 (AUC 0.624, 95% CI 0.446-0.810, p < 0.05) and other clinical risk scores for this purpose. CONCLUSION: NEWS2 score at hospital admission predicted severe disease and in-hospital mortality, and was superior to other widely used clinical risk scores in patients with covid-19.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Early Warning Score , Hospital Mortality , Patient Admission , Pneumonia, Viral/epidemiology , Adult , Aged , Aged, 80 and over , COVID-19 , Cohort Studies , Female , Humans , Male , Middle Aged , Norway/epidemiology , Pandemics , Risk Assessment , SARS-CoV-2 , Sensitivity and Specificity , Severity of Illness Index
3.
BMC Health Serv Res ; 22(1): 1301, 2022 Oct 29.
Article in English | MEDLINE | ID: covidwho-2098340

ABSTRACT

BACKGROUND: Breast cancer clinics across the UK have long been struggling to cope with high demand. Novel risk prediction tools - such as the PinPoint test - could help to reduce unnecessary clinic referrals. Using early data on the expected accuracy of the test, we explore the potential impact of PinPoint on: (a) the percentage of patients meeting the two-week referral target, and (b) the number of clinic 'overspill' appointments generated (i.e. patients having to return to the clinic to complete their required investigations). METHODS: A simulation model was built to reflect the annual flow of patients through a single UK clinic. Due to current uncertainty around the exact impact of PinPoint testing on standard care, two primary scenarios were assessed. Scenario 1 assumed complete GP adherence to testing, with only non-referred cancerous cases returning for delayed referral. Scenario 2 assumed GPs would overrule 20% of low-risk results, and that 10% of non-referred non-cancerous cases would also return for delayed referral. A range of sensitivity analyses were conducted to explore the impact of key uncertainties on the model results. Service reconfiguration scenarios, removing individual weekly clinics from the clinic schedule, were also explored. RESULTS: Under standard care, 66.3% (95% CI: 66.0 to 66.5) of patients met the referral target, with 1,685 (1,648 to 1,722) overspill appointments. Under both PinPoint scenarios, > 98% of patients met the referral target, with overspill appointments reduced to between 727 (707 to 746) [Scenario 1] and 886 (861 to 911) [Scenario 2]. The reduced clinic demand was sufficient to allow removal of one weekly low-capacity clinic [N = 10], and the results were robust to sensitivity analyses. CONCLUSION: The findings from this early analysis indicate that risk prediction tools could have the potential to alleviate pressure on cancer clinics, and are expected to have increased utility in the wake of heightened pressures resulting from the COVID-19 pandemic. Further research is required to validate these findings with real world evidence; evaluate the broader clinical and economic impact of the test; and to determine outcomes and risks for patients deemed to be low-risk on the PinPoint test and therefore not initially referred.


Subject(s)
Breast Neoplasms , COVID-19 , Humans , Female , Waiting Lists , Breast Neoplasms/diagnosis , Pandemics , Workflow , COVID-19/epidemiology , Referral and Consultation , Risk Assessment
4.
Infect Control Hosp Epidemiol ; 41(8): 968-969, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-2096333

ABSTRACT

To inform the efficient allocation of testing resources, we evaluated the characteristics of those tested for COVID-19 to determine predictors of a positive test. Recent travel and exposure to a confirmed case were both highly predictive of positive testing. Symptom-based screening strategies alone may be inadequate to control the ongoing pandemic.


Subject(s)
Betacoronavirus/isolation & purification , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Polymerase Chain Reaction , Travel , Adult , Asymptomatic Infections , COVID-19 , COVID-19 Testing , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Female , Humans , Logistic Models , Male , Middle Aged , Minnesota , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Risk Assessment , SARS-CoV-2
6.
J Postgrad Med ; 68(4): 199-206, 2022.
Article in English | MEDLINE | ID: covidwho-2080671

ABSTRACT

Background: : Risk assessment with prognostic scoring, though important, is scarcely studied in emergency surgical patients with COVID-19 infection. Methods and Material: We conducted a retrospective cohort study on adult emergency surgical patients with COVID-19 infection in our institute from 1 May 2020 to 31 October 2021 to find the 30-day postoperative mortality and predictive accuracy of prognostic scores. We assessed the demographic data, prognostic risk scores (American Society of Anesthesiologists-Physical Classification (ASA-PS), Sequential Organ Failure Assessment (SOFA), Quick SOFA (qSOFA), Physiologic and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) and Portsmouth-POSSUM (P-POSSUM) scores), surgical and anesthetic factors. We assessed the postoperative morbidity using the Clavien-Dindo scale and recorded the 30-day mortality. Correlation of prognostic scores and mortality was evaluated using Univariate Cox proportional hazards regression, receiver operating characteristic curve (ROC), Youden's index and Hosmer- Lemeshow goodness of fit model. Results: Emergency surgery was performed in 67 COVID-19 patients with postoperative complication and 30-day mortality rate of 33% and 19%, respectively. A positive qSOFA and ASAPS IIIE/IVE had a 9.03- and 12.7-times higher risk of mortality compared to a negative qSOFA and ASA-PS IE/IIE (P < 0.001), respectively. Every unit increase of SOFA, POSSUM and P-POSSUM scores was associated with a 50%, 18% and 17% higher risk of mortality, respectively. SOFA, POSSUM and P-POSSUM AUCROC curves showed good discrimination between survivors and non-survivors (AUC 0.8829, 0.85 and 0.86, respectively). Conclusions: SOFA score has a higher sensitivity to predict 30-day postoperative mortality as compared to POSSUM and P-POSSUM. However, in absence of a control group of non-COVID-19 patients, actual risk attributable to COVID-19 infection could not be determined.


Subject(s)
COVID-19 , Adult , Humans , Retrospective Studies , Prognosis , Postoperative Period , Risk Assessment/methods , ROC Curve , Postoperative Complications/etiology , Severity of Illness Index
7.
Vox Sang ; 116(2): 155-166, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-2078680

ABSTRACT

BACKGROUND AND OBJECTIVE: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a novel coronavirus, first identified in China at the end of 2019 and has now caused a worldwide pandemic. In this review, we provide an overview of the implications of SARS-CoV-2 for blood safety and sufficiency. MATERIAL AND METHOD: We searched the PubMed database, the preprint sites bioRxiv and medRxiv, the websites of the World Health Organization, European Centre for Disease Prevention and Control, the US Communicable Diseases Center and monitored ProMed updates. RESULTS: An estimated 15%-46% of SARS-CoV-2 infections are asymptomatic. The reported mean incubation period is 3 to 7 days with a range of 1-14 days. The blood phase of SARS-CoV-2 appears to be brief and low level, with RNAaemia detectable in only a small proportion of patients, typically associated with more severe disease and not demonstrated to be infectious virus. An asymptomatic blood phase has not been demonstrated. Given these characteristics of SARS-CoV-2 infection and the absence of reported transfusion transmission (TT), the TT risk is currently theoretical. To mitigate any potential TT risk, but more importantly to prevent respiratory transmission in donor centres, blood centres can implement donor deferral policies based on travel, disease status or potential risk of exposure. CONCLUSION: The TT risk of SARS-CoV-2 appears to be low. The biggest risk to blood services in the current COVID-19 pandemic is to maintain the sufficiency of the blood supply while minimizing respiratory transmission of SARS-CoV-19 to donors and staff while donating blood.


Subject(s)
Blood Safety , COVID-19/blood , COVID-19/prevention & control , COVID-19/virology , Transfusion Reaction/prevention & control , Blood Transfusion , Geography , Humans , RNA, Viral/analysis , Risk Assessment , SARS-CoV-2 , Safety Management , World Health Organization
8.
Lancet ; 395(10227): 871-877, 2020 03 14.
Article in English | MEDLINE | ID: covidwho-2076860

ABSTRACT

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) epidemic has spread from China to 25 countries. Local cycles of transmission have already occurred in 12 countries after case importation. In Africa, Egypt has so far confirmed one case. The management and control of COVID-19 importations heavily rely on a country's health capacity. Here we evaluate the preparedness and vulnerability of African countries against their risk of importation of COVID-19. METHODS: We used data on the volume of air travel departing from airports in the infected provinces in China and directed to Africa to estimate the risk of importation per country. We determined the country's capacity to detect and respond to cases with two indicators: preparedness, using the WHO International Health Regulations Monitoring and Evaluation Framework; and vulnerability, using the Infectious Disease Vulnerability Index. Countries were clustered according to the Chinese regions contributing most to their risk. FINDINGS: Countries with the highest importation risk (ie, Egypt, Algeria, and South Africa) have moderate to high capacity to respond to outbreaks. Countries at moderate risk (ie, Nigeria, Ethiopia, Sudan, Angola, Tanzania, Ghana, and Kenya) have variable capacity and high vulnerability. We identified three clusters of countries that share the same exposure to the risk originating from the provinces of Guangdong, Fujian, and the city of Beijing, respectively. INTERPRETATION: Many countries in Africa are stepping up their preparedness to detect and cope with COVID-19 importations. Resources, intensified surveillance, and capacity building should be urgently prioritised in countries with moderate risk that might be ill-prepared to detect imported cases and to limit onward transmission. FUNDING: EU Framework Programme for Research and Innovation Horizon 2020, Agence Nationale de la Recherche.


Subject(s)
Civil Defense , Coronavirus Infections , Epidemics/prevention & control , Health Resources , Models, Theoretical , Pneumonia, Viral , Population Surveillance , Vulnerable Populations , Africa/epidemiology , COVID-19 , China/epidemiology , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Health Planning , Humans , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , Risk Assessment , Travel
9.
Am J Med Qual ; 37(6): 535-544, 2022.
Article in English | MEDLINE | ID: covidwho-2077938

ABSTRACT

The COVID-19 pandemic exposed the need to more effectively harness and leverage digital tools and technology for remote patient monitoring (RPM). RPM gained great popularity given the need to provide effective, safe, efficient, and remote patient care. RPM is based on noninvasive digital technologies aimed at improving the safety and efficiency of health care delivery. We report on an RPM program in which 200 COVID-19 patients were followed remotely to evaluate the effectiveness in treating and monitoring patients in home settings. We analyzed the inherent risks using mixed methods, including failure mode and effect analysis, a prospective, team-based risk management methodology structured to identify high-risk process system failures before they occur in telemonitoring of remote patients. The RPM saved lives and improved decision-making during the pandemic and helped prevent the health system's collapse. The failure mode and effect analysis-based assessment offers important insights and considerations for evaluating future RPM implementation and direction. RPM solutions are technically feasible, staff friendly, and can achieve high adherence rates. Rigorous and ongoing evaluation of devices and platforms is essential to clarifying their value and guiding national health and insurance health coverage decisions and adoption programs.


Subject(s)
COVID-19 , Humans , Pandemics , Prospective Studies , Risk Assessment , Delivery of Health Care
10.
Nutrients ; 14(20)2022 Oct 13.
Article in English | MEDLINE | ID: covidwho-2071661

ABSTRACT

Overweight and obesity are associated with chronic low-grade inflammation and represent risk factors for various diseases, including COVID-19. However, most published studies on COVID-19 defined obesity by the body mass index (BMI), which does not encounter adipose tissue distribution, thus neglecting immunometabolic high-risk patterns. Therefore, we comprehensively analyzed baseline anthropometry (BMI, waist-to-height-ratio (WtHR), visceral (VAT), epicardial (EAT), subcutaneous (SAT) adipose tissue masses and liver fat, inflammation markers (CRP, ferritin, interleukin-6), and immunonutritional scores (CRP-to-albumin ratio (CAR), modified Glasgow prognostic score, neutrophile-to-lymphocyte ratio, prognostic nutritional index)) in 58 consecutive COVID-19 patients of the early pandemic phase with regard to the necessity of invasive mechanical ventilation (IMV). Here, metabolically high-risk adipose tissues represented by increased VAT, liver fat, and WtHR strongly correlated with higher levels of inflammation, pathologic immunonutritional scores, and the need for IMV. In contrast, the prognostic value of BMI was inferior and absent with regard to SAT. Multivariable logistic regression analysis identified an optimized IMV risk prediction model employing liver fat, WtHR, and CAR. In summary, we suggest an immunometabolically risk-adjusted model to predict COVID-19-induced respiratory failure better than BMI-based stratification, which warrants prospective validation.


Subject(s)
COVID-19 , Respiratory Insufficiency , Humans , Body Mass Index , Interleukin-6 , Obesity/complications , Obesity/pathology , Inflammation/complications , Respiratory Insufficiency/complications , Albumins , Ferritins , Risk Assessment , Intra-Abdominal Fat/pathology , Risk Factors
11.
PLoS One ; 17(10): e0274158, 2022.
Article in English | MEDLINE | ID: covidwho-2065118

ABSTRACT

As SARS-CoV-2 infections continue to cause hospital admissions around the world, there is a continued need to accurately assess those at highest risk of death to guide resource use and clinical management. The ISARIC 4C mortality score provides mortality risk prediction at admission to hospital based on demographic and physiological parameters. Here we evaluate dynamic use of the 4C score at different points following admission. Score components were extracted for 6,373 patients admitted to Barts Health NHS Trust hospitals between 1st August 2020 and 19th July 2021 and total score calculated every 48 hours for 28 days. Area under the receiver operating characteristic (AUC) statistics were used to evaluate discrimination of the score at admission and subsequent inpatient days. Patients who were still in hospital at day 6 were more likely to die if they had a higher score at day 6 than others also still in hospital who had the same score at admission. Discrimination of dynamic scoring in those still in hospital was superior with the area under the curve 0.71 (95% CI 0.69-0.74) at admission and 0.82 (0.80-0.85) by day 8. Clinically useful changes in the dynamic parts of the score are unlikely to be associated with subject-level measurements. Dynamic use of the ISARIC 4C score is likely to provide accurate and timely information on mortality risk during a patient's hospital admission.


Subject(s)
COVID-19 , Cohort Studies , Hospital Mortality , Hospitals , Humans , Retrospective Studies , Risk Assessment , SARS-CoV-2
12.
Front Immunol ; 13: 980079, 2022.
Article in English | MEDLINE | ID: covidwho-2065514

ABSTRACT

Treatment of systemic lupus erythematosus (SLE) currently employs agents with relatively unselective immunosuppressive properties. However, two target-specific biological drugs have been approved: belimumab (anti-B-cell-activating factor/BAFF) and anifrolumab (anti-interferon alpha receptor-1/IFNAR1). Here, we performed a comparative risk-benefit assessment for both drugs based on the role of BAFF and IFNAR1 in host defense and the pathogenesis of SLE and by considering the available data on safety and efficacy. Due to differences in target expression sites, anti-IFNAR1, but not anti-BAFF, might elicit organ-specific effects, consistent with clinical efficacy data. The IFNAR1 is specifically involved in innate and adaptive antiviral immunity in most cells of the body. Consistent with this observation, the available safety data obtained from patients negatively selected for LN and neuropsychiatric SLE, primary immunodeficiencies, splenectomy and chronic HIV, HBV, HCV infections suggest an increased risk for some viral infections such as varicella zoster and perhaps influenza. In contrast, BAFF is mainly involved in adaptive immune responses in lymphoid tissues, thus anti-BAFF therapy modulates SLE activity and prevents SLE flares without interfering with local innate host defense mechanisms and should only marginally affect immune memory to previous pathogen exposures consistent with the available safety data from SLE patients without chronic HIV, HBV or HCV infections. When using belimumab and anifrolumab, careful patient stratification and specific precautions may minimize risks and maximize beneficial treatment effects for patients with SLE.


Subject(s)
Biological Products , HIV Infections , Hepatitis C , Lupus Erythematosus, Systemic , Antibodies, Monoclonal, Humanized , Antiviral Agents/therapeutic use , Biological Products/therapeutic use , HIV Infections/drug therapy , Hepatitis C/drug therapy , Humans , Risk Assessment
13.
J Am Heart Assoc ; 9(22): e017364, 2020 11 17.
Article in English | MEDLINE | ID: covidwho-2064368

ABSTRACT

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) utilizes the angiotensin-converting enzyme-2 (ACE-2) receptor to enter human cells. Angiotensin-converting enzyme inhibitors (ACEI) and angiotensin II receptor antagonists (ARB) are associated with ACE-2 upregulation. We hypothesized that antecedent use of ACEI/ARB may be associated with mortality in coronavirus disease 2019 (COVID-19). Methods and Results We used the Coracle registry, which contains data of patients hospitalized with COVID-19 in 4 regions of Italy, and restricted analyses to those ≥50 years of age. The primary outcome was in-hospital mortality. Among these 781 patients, 133 (17.0%) used an ARB and 171 (21.9%) used an ACEI. While neither sex nor smoking status differed by user groups, patients on ACEI/ARB were older and more likely to have hypertension, diabetes mellitus, and congestive heart failure. The overall mortality rate was 15.1% (118/781) and increased with age (PTrend<0.0001). The crude odds ratios (ORs) for death for ACEI users and ARB users were 0.98, 95% CI, 0.60-1.60, P=0.9333, and 1.13, 95% CI, 0.67-1.91, P=0.6385, respectively. After adjusting for age, hypertension, diabetes mellitus, and congestive heart failure, antecedent ACEI administration was associated with reduced mortality (OR, 0.55; 95% CI, 0.31-0.98, P=0.0436); a similar, but weaker trend was observed for ARB administration (OR, 0.58; 95% CI, 0.32-1.07, P=0.0796). Conclusions In those aged ≥50 years hospitalized with COVID-19, antecedent use of ACEI was independently associated with reduced risk of inpatient death. Our findings suggest a protective role of renin-angiotensin-aldosterone system inhibition in patients with high cardiovascular risk affected by COVID-19.


Subject(s)
Angiotensin Receptor Antagonists/therapeutic use , Angiotensin-Converting Enzyme Inhibitors/therapeutic use , COVID-19/therapy , Hospitalization , Age Factors , Aged , Aged, 80 and over , COVID-19/diagnosis , COVID-19/mortality , Female , Hospital Mortality , Humans , Italy , Male , Middle Aged , Protective Factors , Registries , Retrospective Studies , Risk Assessment , Risk Factors , Time Factors , Treatment Outcome
14.
BMC Public Health ; 22(1): 1843, 2022 10 01.
Article in English | MEDLINE | ID: covidwho-2053885

ABSTRACT

BACKGROUND: In response to the COVID-19 outbreak, the Civil Aviation Administration of China (CAAC) has formulated Implementation Measures for Exemption of Crew Duty Periods and Flight Time Restrictions during the COVID-19 Outbreak. This exemption policy imposes temporary deviations from the approved crew duty periods and flight time restrictions for some transport airlines and regulates the use of multiple crews for continuous round-trip flights. However, no research has been conducted on flight crew fatigue under this exemption policy. That is, the exemption policy lacks theoretical analysis and scientific validation. METHODS: Firstly, flight plans for international flights under both the exemption and the CCAR-121 Policy schemes (with three flight departure scenarios: early morning, midday and evening) are designed, and flight plans are simulated based on the SAFE model. The Karolinska Sleepiness Scale (KSS) and the PVT objective test of alertness, both of which are commonly used in the aviation industry, are then selected for use in an empirical experimental study of flight crew fatigue on two flights subject to the exemption and CCAR-121 policies. RESULTS: The SAFE model simulation found that the fatigue risk results based on flight crews for flights departing in the early morning (4:00), at noon (12:00) and in the evening (20:00) indicate that the fatigue risk levels of flight crews operating under the exemption policy are overwhelmingly lower than or similar to those operating under the CCAR-121 policy. However, there were a few periods when the fatigue risk of crews flying under the exemption policy was higher than that of crews flying under the CCAR-121 policy, but at these times, the crews flying under both policies were either at a lower level of fatigue risk or were in the rest phase of their shifts. In the experimental study section, 40 pilots from each of the early morning (4:00), noon (12:00) and evening (20:00) departures operating under the exemption policy were selected to collect KSS scale data and PVT test data during their duty periods, and a total of 120 other pilots operating under the CCAR-121 policy were selected for the same experiment. First, the KSS scale data results found that flight pilots, whether flying under the exemption policy or under the CCAR-121 policy, had overall similar KSS scores, maintained KSS scores below the fatigue risk threshold (i.e., KSS score < 6) during the flights and that the empirical KSS data and the model simulation results from the KSS data were overall identical at the test nodes during the flight and had nearly identical trends. Finally, the results of the PVT objective test indicators showed that the overall change in 1/RT of the crews flying under the exemption policy was less than or similar to that of the crews flying under the CCAR-121 policy, while the maximum change in 1/RT of the crews under both policies was between 1 and 1.5. This indicates that the overall level of alertness of the crew flying under the exemption policy is higher than or similar to that of the crew flying under the CCAR-121 policy, while the change in alertness level of the crew before and after the mission is relatively small when flying under either policy. CONCLUSION: Based on the model simulation results and the results of the empirical study, it was verified that the overall fatigue risk level of flight crews operating under the exemption policy is lower than or similar to the fatigue risk level of flight crews operating under the CCAR-121 policy. Therefore, the exemption policy in response to the COVID-19 outbreak does not result in an overall increase in the level of flight crew fatigue risk compared to the original CCAR-121 policy.


Subject(s)
COVID-19 , Work Schedule Tolerance , Aircraft , Disease Outbreaks , Fatigue/epidemiology , Humans , Policy , Risk Assessment , Sleep/physiology , Sleep Deprivation/epidemiology , Work Schedule Tolerance/physiology
15.
Curr Opin Infect Dis ; 35(6): 605-613, 2022 Dec 01.
Article in English | MEDLINE | ID: covidwho-2051764

ABSTRACT

PURPOSE OF REVIEW: SARS-CoV-2 deeply modified the risk of bacterial infection, bacterial resistance, and antibiotic strategies. This review summarized what we have learned. RECENT FINDINGS: During the COVID-19 pandemic, we observed an increase in healthcare-acquired infection and multidrug-resistant organism-related infection, triggered by several factors: structural factors, such as increased workload and ongoing outbreaks, underlying illnesses, invasive procedures, and treatment-induced immunosuppression. The two most frequently healthcare-acquired infections described in patients hospitalized with COVID-19 were bloodstream infection, related or not to catheters, health-acquired pneumonia (in ventilated or nonventilated patients). The most frequent species involved in bacteremia were Gram-positive cocci and Gram-negative bacilli in health-acquired pneumonia. The rate of Gram-negative bacilli is particularly high in late-onset ventilator-associated pneumonia, and the specific risk of Pseudomonas aeruginosa- related pneumonia increased when the duration of ventilation was longer than 7 days. A specificity that remains unexplained so far is the increase in enterococci bacteremia. SUMMARY: The choice of empiric antibiotimicrobials depends on several factors such as the site of the infection, time of onset and previous length of stay, previous antibiotic therapy, and known multidrug-resistant organism colonization. Pharmacokinetics of antimicrobials could be markedly altered during SARS-CoV-2 acute respiratory failure, which should encourage to perform therapeutic drug monitoring.


Subject(s)
Bacteremia , COVID-19 , Cross Infection , Gram-Negative Bacterial Infections , Humans , COVID-19/drug therapy , Gram-Negative Bacterial Infections/drug therapy , Cross Infection/drug therapy , Cross Infection/epidemiology , Cross Infection/microbiology , Pandemics , SARS-CoV-2 , Gram-Negative Bacteria , Bacteremia/drug therapy , Bacteremia/epidemiology , Bacteremia/microbiology , Anti-Bacterial Agents/therapeutic use , Anti-Bacterial Agents/pharmacology , Risk Assessment
16.
J Clin Psychopharmacol ; 42(6): 565-580, 2022.
Article in English | MEDLINE | ID: covidwho-2051644

ABSTRACT

PURPOSE: Although clozapine was Food and Drug Administration (FDA) approved more than 3 decades ago, major barriers and gaps in knowledge continue to prevent its effective and safe use. We review modern-day problems encountered with clozapine in the United States (US). METHODS: Information surrounding current administrative, clinical, research, and technological gaps or barriers related to clozapine use in the US was reviewed. FINDINGS: The history of how clozapine became FDA approved likely contributes to gaps in knowledge. The frequency of safety warnings added to the FDA prescribing information may add to fears about clozapine, as evidence by numerous published survey studies. The clozapine Risk Evaluation and Mitigation Strategy (REMS) program has been modified several times in the last decade, causing access and safety issues for patients, which are discussed. Evidence may suggest that the FDA REMS requirements for hematologic monitoring are too cumbersome, and there may be ability to safely loosen requirements. The COVID-19 pandemic brought forth the ability for extended interval monitoring but also greater awareness of the clozapine-inflammation interaction. Newer guidelines published describe considerations in personalizing clozapine titration based on principles of ethnopsychopharmacology. Emerging technologies to support the use of clozapine are not widely available. IMPLICATIONS: Clozapine is a unique life-saving drug but it is underused in the US, despite its established efficacy. The 2021 REMS changes led to significant difficulties for providers and patients. We highlight the importance of the clozapine-inflammation interaction, therapeutic drug monitoring, and the ability for individual care based on patient-specific factors. There is an urgent need for advancing technology used for clozapine monitoring, evaluating barriers created by REMS, and establishing consistent practices throughout the US.


Subject(s)
COVID-19 , Clozapine , United States , Humans , Clozapine/adverse effects , Pandemics , Risk Assessment , COVID-19/drug therapy , United States Food and Drug Administration , Inflammation
17.
Sci Rep ; 12(1): 16176, 2022 Sep 28.
Article in English | MEDLINE | ID: covidwho-2050512

ABSTRACT

Patients with SARS-CoV-2 infection are at an increased risk of cardiovascular and thrombotic complications conferring an extremely poor prognosis. COVID-19 infection is known to be an independent risk factor for acute ischemic stroke and myocardial infarction (MI). We developed a risk assessment model (RAM) to stratify hospitalized COVID-19 patients for arterial thromboembolism (ATE). This multicenter, retrospective study included adult COVID-19 patients admitted between 3/1/2020 and 9/5/2021. Among 3531 patients from the training cohort, 15.5% developed acute in-hospital ATE, including stroke, MI, and other ATE, compared to 13.4% in the validation cohort. The 16-item final score was named SARS-COV-ATE (Sex: male = 1, Age [40-59 = 2, > 60 = 4], Race: non-African American = 1, Smoking = 1 and Systolic blood pressure elevation = 1, Creatinine elevation = 1; Over the range: leukocytes/lactate dehydrogenase/interleukin-6, B-type natriuretic peptide = 1, Vascular disease (cardiovascular/cerebrovascular = 1), Aspartate aminotransferase = 1, Troponin-I [> 0.04 ng/mL = 1, troponin-I > 0.09 ng/mL = 3], Electrolytes derangement [magnesium/potassium = 1]). RAM had a good discrimination (training AUC 0.777, 0.756-0.797; validation AUC 0.766, 0.741-0.790). The validation cohort was stratified as low-risk (score 0-8), intermediate-risk (score 9-13), and high-risk groups (score ≥ 14), with the incidence of ATE 2.4%, 12.8%, and 33.8%, respectively. Our novel prediction model based on 16 standardized, commonly available parameters showed good performance in identifying COVID-19 patients at risk for ATE on admission.


Subject(s)
COVID-19 , Ischemic Stroke , Thromboembolism , Adult , Aspartate Aminotransferases , COVID-19/complications , Creatinine , Humans , Interleukin-6 , Ischemic Stroke/etiology , Lactate Dehydrogenases , Magnesium , Male , Natriuretic Peptide, Brain , Potassium , Retrospective Studies , Risk Assessment , Risk Factors , SARS-CoV-2 , Thromboembolism/epidemiology , Thromboembolism/etiology , Troponin I
18.
PLoS One ; 17(9): e0272037, 2022.
Article in English | MEDLINE | ID: covidwho-2043199

ABSTRACT

Preparedness and responses to infectious disease epidemics and pandemics require the understanding of communities' and multisectoral systems' characteristics with regards to diseases transmission and population's vulnerabilities. This study aimed to summarize measurement profiles of existing risk assessment toolkits to inform COVID-19 control at global and national levels. An online search in different databases and online sources was performed to identify all epidemic risk and vulnerability assessment instruments. Medline/PubMed, Web of Science databases, and websites of public health organizations were used for the searching process. Of 14 toolkits, levels of setting were mostly at the global or nation level. Components such as Governance and Legislation, Financing, Health Service Provision, and Human Resources are key domains in almost all toolkits. Some important issues for disease detection and surveillance, such as laboratory or capacity of the community for disease control, were not adequately addressed in several toolkits. Limited studies were found that validated the toolkits. Only five toolkits were used in COVID-19 studies. This study provides a summary of risk assessment toolkits to inform epidemic responses. We call for global and national efforts in developing more contextualized and responsive epidemic risk assessment scales incorporating specific-disease and -country factors to inform operational decisions making and strengthen countries' capacities in epidemic responses.


Subject(s)
COVID-19 , Communicable Diseases , Epidemics , COVID-19/epidemiology , Communicable Diseases/epidemiology , Epidemics/prevention & control , Humans , Pandemics/prevention & control , Public Health , Risk Assessment
19.
Nat Protoc ; 17(1): 1-2, 2022 01.
Article in English | MEDLINE | ID: covidwho-2042330

Subject(s)
Risk Assessment
20.
PLoS One ; 17(9): e0274171, 2022.
Article in English | MEDLINE | ID: covidwho-2039408

ABSTRACT

The clinical course of COVID-19 is highly variable. It is therefore essential to predict as early and accurately as possible the severity level of the disease in a COVID-19 patient who is admitted to the hospital. This means identifying the contributing factors of mortality and developing an easy-to-use score that could enable a fast assessment of the mortality risk using only information recorded at the hospitalization. A large database of adult patients with a confirmed diagnosis of COVID-19 (n = 15,628; with 2,846 deceased) admitted to Spanish hospitals between December 2019 and July 2020 was analyzed. By means of multiple machine learning algorithms, we developed models that could accurately predict their mortality. We used the information about classifiers' performance metrics and about importance and coherence among the predictors to define a mortality score that can be easily calculated using a minimal number of mortality predictors and yielded accurate estimates of the patient severity status. The optimal predictive model encompassed five predictors (age, oxygen saturation, platelets, lactate dehydrogenase, and creatinine) and yielded a satisfactory classification of survived and deceased patients (area under the curve: 0.8454 with validation set). These five predictors were additionally used to define a mortality score for COVID-19 patients at their hospitalization. This score is not only easy to calculate but also to interpret since it ranges from zero to eight, along with a linear increase in the mortality risk from 0% to 80%. A simple risk score based on five commonly available clinical variables of adult COVID-19 patients admitted to hospital is able to accurately discriminate their mortality probability, and its interpretation is straightforward and useful.


Subject(s)
COVID-19 , Adult , COVID-19/diagnosis , Creatinine , Hospital Mortality , Hospitalization , Humans , Lactate Dehydrogenases , Machine Learning , Retrospective Studies , Risk Assessment
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