Liver biomarkers for prognosis in COVID-19

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.

Demo Abstract: Implementing a COVID-19 Risk Assessment System for User-Informed Travel Planning in Harris County

The COVID-19 pandemic has forced people worldwide to modify their daily activities, including travel plans. To help individuals make informed decisions about visiting public places, Cheng [2] first proposed a real-time COVID-19 risk assessment system called RT-CIRAM and implemented prototypes for two U.S. metropolitan locations. The system calculates a COVID-19 risk score and categorizes the risk levels into high, medium, and low, recommends the safe travel destination using the users' location and the specified distance the user is willing to travel, thereby helping users make informed decisions about their travel plans. © 2023 ACM.

28th Italian Melanoma Intergroup National Congress

The proceedings contain 35 papers. The topics discussed include: germline variants and prognostic factors for cutaneous melanoma in children and adolescents;association between polygenic risk score and multiple primary melanoma;Porocarcinoma: an epidemiological, clinical, and dermoscopic 20-year study;primary cutaneous melanoma and COVID-19: a hospital-based study;atypical spitz tumors: an epidemiological, clinical and dermoscopic multicenter study with 16 years of follow-up;pediatric melanoma: an epidemiological, clinical and dermoscopic multicenter study;recurrence-free survival prediction in melanoma patients by exploiting artificial intelligence techniques on melanoma whole slide images;ultra-high frequency ultrasound and machine learning approaches for the differential diagnosis of melanocytic lesions;and genetic determinants of response to therapy in a real-world setting of advanced/metastatic melanoma patients: whole-exome sequencing and CFDNA analysis.

Validation of the russian version of the 4C Mortality Score and prediction of outcomes of severe COVID-19

The aim of the study is to validate the Russian version of the 4C Mortality Score scale and evaluate its accuracy in predicting the outcomes of severe COVID-19. Material and methods. The staff of the Center for Validation of International Scales and Questionnaires of the Research Center of Neurology received official permission from the authors to conduct a validation study of the 4C Mortality Score scale in Russia. In the course of the work, the linguistic and cultural ratification of the scale was carried out and its Russian-language version was prepared. Psychometric properties (reliability and validity) The Russian-language version was evaluated on a group of 78 patients (37 of whom were men, aged 34 to 88 years) with a confirmed diagnosis of COVID-19, hospitalized in the City Clinical Hospital No. 15 named after O.M. Filatov (Moscow) in the period from June to August 2021. Results. The linguocultural adaptation of the 4C Mortality Score scale was successfully carried out. High levels of reliability were obtained (Spearman correlation coefficient rho=0.91, p<0.0001;Cronbach's alpha alpha=0.73, p=0.0002;Cohen's kappa kappa=0.85, p<0.0001). It is shown that the 4C Mortality Score scores have a significant correlation with the COVID-GRAM scores (r=0.72, p=0.002) and NEWS2 (r=0.54, p=0.004). Conclusion. As a result of the validation study, the official Russian version of the 4C Mortality Score scale was developed. It is recommended for use by medical professionals of various specialties at all stages of providing medical care to patients with COVID-19. The scale is available for download on the website of the Center for Validation of International Scales and Questionnaires of the Research Center of Neurology (https://www.neurology.ru/reabilitaciya/centr-validacii-mezhdunarodnyh-shkal-i-oprosnikov).Copyright © 2022 by the authors.

Host Genetic Factors, Comorbidities and the Risk of Severe COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was varied in disease symptoms. We aim to explore the effect of host genetic factors and comorbidities on severe COVID-19 risk. METHODS: A total of 20,320 COVID-19 patients in the UK Biobank cohort were included. Genome-wide association analysis (GWAS) was used to identify host genetic factors in the progression of COVID-19 and a polygenic risk score (PRS) consisted of 86 SNPs was constructed to summarize genetic susceptibility. Colocalization analysis and Logistic regression model were used to assess the association of host genetic factors and comorbidities with COVID-19 severity. All cases were randomly split into training and validation set (1:1). Four algorithms were used to develop predictive models and predict COVID-19 severity. Demographic characteristics, comorbidities and PRS were included in the model to predict the risk of severe COVID-19. The area under the receiver operating characteristic curve (AUROC) was applied to assess the models' performance. RESULTS: We detected an association with rs73064425 at locus 3p21.31 reached the genome-wide level in GWAS (odds ratio: 1.55, 95% confidence interval: 1.36-1.78). Colocalization analysis found that two genes (SLC6A20 and LZTFL1) may affect the progression of COVID-19. In the predictive model, logistic regression models were selected due to simplicity and high performance. Predictive model consisting of demographic characteristics, comorbidities and genetic factors could precisely predict the patient's progression (AUROC = 82.1%, 95% CI 80.6-83.7%). Nearly 20% of severe COVID-19 events could be attributed to genetic risk. CONCLUSION: In this study, we identified two 3p21.31 genes as genetic susceptibility loci in patients with severe COVID-19. The predictive model includes demographic characteristics, comorbidities and genetic factors is useful to identify individuals who are predisposed to develop subsequent critical conditions among COVID-19 patients.

Clinical risk score for early prediction of recurring SARS-CoV-2 positivity in non-critical patients.

Introduction: Recurrent positive results in quantitative reverse transcriptase-PCR (qRT-PCR) tests have been commonly observed in COVID-19 patients. We aimed to construct and validate a reliable risk stratification tool for early predictions of non-critical COVID-19 survivors' risk of getting tested re-positive within 30 days. Methods: We enrolled and retrospectively analyzed the demographic data and clinical characters of 23,145 laboratory-confirmed cases with non-critical COVID-19. Participants were followed for 30 days and randomly allocated to either a training (60%) or a validation (40%) cohort. Multivariate logistic regression models were employed to identify possible risk factors with the SARS-CoV-2 recurrent positivity and then incorporated into the nomogram. Results: The study showed that the overall proportion of re-positive cases within 30 days of the last negative test was 24.1%. In the training cohort, significantly contributing variables associated with the 30-day re-positivity were clinical type, COVID-19 vaccination status, myalgia, headache, admission time, and first negative conversion, which were integrated to build a nomogram and subsequently translate these scores into an online publicly available risk calculator (https://anananan1.shinyapps.io/DynNomapp2/). The AUC in the training cohort was 0.719 [95% confidence interval (CI), 0.712-0.727] with a sensitivity of 66.52% (95% CI, 65.73-67.30) and a specificity of 67.74% (95% CI, 66.97-68.52). A significant AUC of 0.716 (95% CI, 0.706-0.725) was obtained for the validation cohort with a sensitivity of 62.29% (95% CI, 61.30-63.28) and a specificity of 71.26% (95% CI, 70.34-72.18). The calibration curve exhibited a good coherence between the actual observation and predicted outcomes. Conclusion: The risk model can help identify and take proper management in high-risk individuals toward the containment of the pandemic in the community.

Endpoint Device Risk-Scoring Algorithm Proposal for Zero Trust

The rapid expansion of remote work following the COVID-19 pandemic has necessitated the development of more robust and secure endpoint device security solutions. Companies have begun to adopt the zero trust security concept as an alternative to traditional network boundary security measures, which requires that every device and user be considered untrustworthy until proven otherwise. Despite the potential benefits of implementing zero trust, the stringent security measures can inadvertently lead to low availability by denying access to legitimate users or limiting their ability to access necessary resources. To address this challenge, we propose a risk-scoring algorithm that balances confidentiality and availability by evaluating the user's impact on resources. Our contributions include (1) summarizing the limitations of existing risk scoring systems in companies that implement zero trust, (2) proposing a dynamic importance metric that measures the importance of resources accessible to users within zero trust systems, and (3) introducing a risk-scoring algorithm that employs the dynamic importance metric to enhance both security and availability in zero trust environments. By incorporating the dynamic importance metric, our proposed algorithm provides a more accurate representation of risk, leading to better security decisions and improved resource availability for legitimate users. This proposal aims to help organizations achieve a more balanced approach to endpoint device security, addressing the unique challenges posed by the increasing prevalence of remote work.

Comparison of three prognostic and predictive scores in 10 patients with COVID-19 pneumonia caused by nosocomial infection

Introduction: A nosocomial outbreak of coronavirus disease (COVID-19) occurred in the Toda Chuo General Hospital in Toda City, Saitama Prefecture, Japan in December 2020. The purpose of this study was to compare the accuracy of three prognostic indices for predicting the outcome of COVID-19 in patents with COVID-19 pneumonia. Patients and Methods: Patients in the Department of Urology and Transplant Surgery at Toda Chuo General Hospital with nosocomially acquired COVID-19 confirmed by a positive polymerase chain reaction test were included in the study. We used the COVID-GRAM, International Severe Acute Respiratory and Emerging Infections Consortium's World Health Organization 4C Mortality Score, and COVID-19 Registry Japan to independently predict the prognoses of 10 patients and identify common prognostic factors. All three indices include age, dyspnea, and comorbidities as prognostic factors. Result(s): Ten patients were included in the study, of which two patients died. According to the COVID-GRAM both patients were "high risk," whereas the 4C Mortality Score predicted "high risk" and "very high risk." Conclusion(s): The prognostic scores of all three indices were useful for predicting illness severity.Copyright © 2023 The Authors

ICD2Vec: Mathematical representation of diseases.

BACKGROUND: The International Classification of Diseases (ICD) codes represent the global standard for reporting disease conditions. The current ICD codes connote direct human-defined relationships among diseases in a hierarchical tree structure. Representing the ICD codes as mathematical vectors helps to capture nonlinear relationships in medical ontologies across diseases. METHODS: We propose a universally applicable framework called "ICD2Vec" designed to provide mathematical representations of diseases by encoding corresponding information. First, we present the arithmetical and semantic relationships between diseases by mapping composite vectors for symptoms or diseases to the most similar ICD codes. Second, we investigated the validity of ICD2Vec by comparing the biological relationships and cosine similarities among the vectorized ICD codes. Third, we propose a new risk score called IRIS, derived from ICD2Vec, and demonstrate its clinical utility with large cohorts from the UK and South Korea. RESULTS: Semantic compositionality was qualitatively confirmed between descriptions of symptoms and ICD2Vec. For example, the diseases most similar to COVID-19 were found to be the common cold (ICD-10: J00), unspecified viral hemorrhagic fever (ICD-10: A99), and smallpox (ICD-10: B03). We show the significant associations between the cosine similarities derived from ICD2Vec and the biological relationships using disease-to-disease pairs. Furthermore, we observed significant adjusted hazard ratios (HR) and area under the receiver operating characteristics (AUROC) between IRIS and risks for eight diseases. For instance, the higher IRIS for coronary artery disease (CAD) can be the higher probability for the incidence of CAD (HR: 2.15 [95% CI 2.02-2.28] and AUROC: 0.587 [95% CI 0.583-0.591]). We identified individuals at substantially increased risk of CAD using IRIS and 10-year atherosclerotic cardiovascular disease risk (adjusted HR: 4.26 [95% CI 3.59-5.05]). CONCLUSIONS: ICD2Vec, a proposed universal framework for converting qualitatively measured ICD codes into quantitative vectors containing semantic relationships between diseases, exhibited a significant correlation with actual biological significance. In addition, the IRIS was a significant predictor of major diseases in a prospective study using two large-scale datasets. Based on this clinical validity and utility evidence, we suggest that publicly available ICD2Vec can be used in diverse research and clinical practices and has important clinical implications.

Predictive value of multiple variable models including nutritional risk score (NRS 2002) on mortality and length of stay of patients with covid-19 infections. The INCOVO study.

BACKGROUND AND AIMS: This study aimed at evaluating associations between nutritional status and outcomes in patients with Covid-19 and to identify statistical models including nutritional parameters associated with in-hospital mortality and length of stay. METHODS: Data of 5707 adult patients hospitalized in the University Hospital of Lausanne between March 2020 and March 2021 were screened retrospectively 920 patients (35% female) with confirmed Covid-19 and complete data including nutritional risk score (NRS 2002), were included. This cohort was divided into three subgroups: NRS <3: no risk of malnutrition; NRS ≥3 to <5: moderate risk malnutrition; and NRS ≥5: severe risk of malnutrition. The primary outcome was the percentage of in-hospital deaths in the different NRS subgroups. The secondary outcomes were the length of hospital stay (LOS), the percentage of admissions to intensive care units (ICU), and the length of stay in the ICU (ILOS). Logistic regression was performed to identify risk factors associated with in-hospital mortality and hospital stay. Multivariate clinical-biological models were developed to study predictions of mortality and very long length of stay. RESULTS: The mean age of the cohort was 69.7 years. The death rate was 4 times higher in the subgroup with a NRS ≥ 5 (44%), and 3 times higher with a NRS ≥ 3 to <5 (33%) compared to the patients with a NRS<3 (10%) (p < 0.001). LOS was significantly higher in the NRS ≥ 5 and NRS ≥ 3 to <5 subgroups (26.0 days; CI [21; 30.9]; and 24.9; CI [22.5; 27.1] respectively) versus 13.4; CI [12; 14.8] for NRS<3 (p < 0.001). The mean ILOS was significantly higher in the NRS ≥ 5 (5.9 days; versus 2.8 for NRS ≥ 3 to <5, and 1.58 for NRS<3 (p < 0.001)). In logistic regression, NRS ≥ 3 was significantly associated with the risk of mortality (OR: 4.8; CI [3.3; 7.1]; p < 0.001) and very long in-hospital stay (>12 days) (OR: 2.5; CI [1.9; 3.3]; p < 0.001). Statistical models that included a NRS ≥ 3 and albumin revealed to be strong predictors for mortality and LOS (area under the curve 0.800 and 0.715). CONCLUSION: NRS was found to be an independent risk factor for in-hospital death and LOS in hospitalized Covid-19 patients. Patients with a NRS ≥ 5 had a significant increase in ILOS and mortality. Statistical models including NRS are strong predictors for an increased risk of death and LOS.

Association of Different Risk Scores and 30-Day Mortality in Kidney Transplant Recipients with COVID-19.

Background and Objectives: Clinical risk scores were poorly examined in kidney transplant recipients (KTR) with COVID-19. Materials and Methods: This observational study compared the association and discrimination of clinical risk scores (MEWS, qCSI, VACO, PSI/PORT, CCI, MuLBSTA, ISTH-DIC, COVID-GRAM and 4C) with 30-day mortality in 65 hospitalized KTRs with COVID-19. Cox regression was used to derive hazard ratios (HR) and 95% confidence intervals (95% CI), and discrimination was assessed by Harrell's C. Results: A significant association with 30-day mortality was demonstrated for MEWS (HR 1.65 95% CI 1.21-2.25, p = 0.002); qCSI (HR 1.32 95% CI 1.15-1.52, p < 0.001); PSI/PORT (HR 1.04 95% CI 1.02-1.07, p = 0.001); CCI (HR 1.79 95% CI 1.13-2.83, p = 0.013); MuLBSTA (HR 1.31 95% CI 1.05-1.64, p = 0.017); COVID-GRAM (HR 1.03 95% CI 1.01-1.06, p = 0.004); and 4C (HR 1.79 95% CI 1.40-2.31, p < 0.001). After multivariable adjustment, significant association persisted for qCSI (HR 1.33 95% CI 1.11-1.59, p = 0.002); PSI/PORT (HR 1.04 95% CI 1.01-1.07, p = 0.012); MuLBSTA (HR 1.36 95% CI 1.01-1.85, p = 0.046); and 4C Mortality Score (HR 1.93 95% CI 1.45-2.57, p < 0.001) risk scores. The best discrimination was observed with the 4C score (Harrell's C = 0.914). Conclusions: Risk scores such as qCSI, PSI/PORT and 4C showed the best association with 30-day mortality amongst KTRs with COVID-19.

Top 20 Research Studies of 2021 for Primary Care Physicians

This article summarizes the top 20 research studies of 2021 identified as POEMs (patient-oriented evidence that matters) that did not address the COVID-19 pandemic. Sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide-1 receptor agonists prevent adverse cardiovascular and renal outcomes in patients with type 2 diabetes mellitus and also reduce all-cause and cardiovascular mortality. Most older adults (mean age, 75 years) with prediabetes do not progress to diabetes. Among patients in this age group with type 2 diabetes treated with medication, an A1C level of less than 7% is associated with increased risk of hospitalization for hypoglycemia, especially when using a sulfonylurea or insulin. For patients with chronic low back pain, exercise, nonsteroidal anti-inflammatory drugs, duloxetine, and opioids were shown to be more effective than control in achieving a 30% reduction in pain, but self-discontinuation of duloxetine and opioids was common. There is no clinically important difference between muscle relaxants and placebo in the treatment of nonspecific low back pain. In patients with chronic pain, low- to moderate-quality evidence supports exercise, yoga, massage, and mindfulness-based stress reduction. For acute musculoskeletal pain, acetaminophen, 1,000 mg, plus ibuprofen, 400 mg, without an opioid is a good option. Regarding screening for colorectal cancer, trial evidence supports performing fecal immunochemical testing every other year. For chronic constipation, evidence supports polyethylene glycol, senna, fiber supplements, magnesium-based products, and fruit-based products. The following abdominal symptoms carry a greater than 3% risk of cancer or inflammatory bowel disease: dysphagia or change in bowel habits in men;rectal bleeding in women;and abdominal pain, change in bowel habits, or dyspepsia in men and women older than 60 years. For secondary prevention in those with established arteriosclerotic cardiovascular disease, 81 mg of aspirin daily appears to be effective. The Framingham Risk Score and the Pooled Cohort Equations both overestimate the risk of cardiovascular events. Over 12 years, no association between egg consumption and cardiovascular events was demonstrated. Gabapentin, pregabalin, duloxetine, and venlafaxine provide clinically meaningful improvements in chronic neuropathic pain. In patients with moderate to severe depression, initial titration above the minimum starting dose of antidepressants in the first eight weeks of treatment is not more likely to increase response. In adults with iron deficiency anemia, adding vitamin C to oral iron has no effect. In children with pharyngitis, rhinosinusitis, acute bronchitis, or acute otitis media, providing education combined with a take-and-hold antibiotic prescription results in 1 in 4 of those children eventually taking an antibiotic.Copyright © 2022 American Academy of Family Physicians.

Haematological Indices Predictive Role In Post Contrast Induced Acute Kidney Injury

Contrast-induced acute kidney injury (CI-AKI) is a frequent complication in cardiac patients after percutaneous coronary intervention (PCI). Thus, the early prediction of such cases is essential to improve outcomes and prevent complications. Hemogram-derived indices provide a cheap, easy, and non-invasive test. Systemic immune inflammation index (SII) is a novel marker that can be calculated easily from a complete blood count test. It can be an important indicator in determining the balance between systemic inflammation and immune status and can predict CI-AKI better than neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR).Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

External validation of the ADA score for predicting thrombosis among acutely ill hospitalized medical patients from the APEX Trial.

The ADA (Age-D-dimer-Albumin) score was developed to identify hospitalized patients at an increased risk for thrombosis in the coronavirus infectious disease-19 (COVID-19) setting. The study aimed to validate the ADA score for predicting thrombosis in a non-COVID-19 medically ill population from the APEX trial. The APEX trial was a multinational, randomized trial that evaluated the efficacy and safety of betrixaban vs. enoxaparin among acutely ill hospitalized patients at risk for venous thromboembolism. The study endpoints included the composite of arterial or venous thrombosis and its components. Metrics of model calibration and discrimination were computed for assessing the performance of the ADA score as compared to the IMPROVE score, a well-validated VTE risk assessment model. Among 7,119 medical inpatients, 209 (2.9%) had a thrombosis event up to 77 days of follow-up. The ADA score demonstrated good calibration for both arterial and venous thrombosis, whereas the IMPROVE score had adequate calibration for venous thrombosis (p > 0.05 from the Hosmer-Lemeshow test). For discriminating arterial and venous thrombosis, there was no significant difference between the ADA vs. IMPROVE score (c statistic = 0.620 [95% CI: 0.582 to 0.657] vs. 0.590 [95% CI: 0.556 to 0.624]; ∆ c statistic = 0.030 [95% CI: -0.022 to 0.081]; p = 0.255). Similarly, for discriminating arterial thrombosis, there was no significant difference between the ADA vs. IMPROVE score (c statistic = 0.582 [95% CI: 0.534 to 0.629] vs. 0.609 [95% CI: 0.564 to 0.653]; ∆ c statistic = -0.027 [95% CI: -0.091 to 0.036]; p = 0.397). For discriminating venous thrombosis, the ADA score was modestly superior to the IMPROVE score (c statistic = 0.664 [95% CI: 0.607 to 0.722] vs. 0.573 [95% CI: 0.521 to 0.624]; ∆ c statistic = 0.091 [95% CI: 0.011 to 0.172]; p = 0.026). The ADA score had a higher sensitivity (0.579 [95% CI: 0.512 to 0.646]; vs. 0.440 [95% CI: 0.373 to 0.507]) but lower specificity (0.625 [95% CI: 0.614 to 0.637] vs. 0.747 [95% CI: 0.737 to 0.758]) than the IMPROVE score for predicting thrombosis. Among acutely ill hospitalized medical patients enrolled in the APEX trial, the ADA score demonstrated good calibration but suboptimal discrimination for predicting thrombosis. The findings support the use of either the ADA or IMPROVE score for thrombosis risk assessment. The applicability of the ADA score to non-COVID-19 populations warrants further research.Clinical Trial Registration: http://www.clinicaltrials.gov . Unique identifier: NCT01583218.

Prediction of intensive care admission and hospital mortality in COVID-19 patients using demographics and baseline laboratory data.

INTRODUCTION: Optimized allocation of medical resources to patients with COVID-19 has been a critical concern since the onset of the pandemic. METHODS: In this retrospective cohort study, the authors used data from a Brazilian tertiary university hospital to explore predictors of Intensive Care Unit (ICU) admission and hospital mortality in patients admitted for COVID-19. Our primary aim was to create and validate prediction scores for use in hospitals and emergency departments to aid clinical decisions and resource allocation. RESULTS: The study cohort included 3,022 participants, of whom 2,485 were admitted to the ICU; 1968 survived, and 1054 died in the hospital. From the complete cohort, 1,496 patients were randomly assigned to the derivation sample and 1,526 to the validation sample. The final scores included age, comorbidities, and baseline laboratory data. The areas under the receiver operating characteristic curves were very similar for the derivation and validation samples. Scores for ICU admission had a 75% accuracy in the validation sample, whereas scores for death had a 77% accuracy in the validation sample. The authors found that including baseline flu-like symptoms in the scores added no significant benefit to their accuracy. Furthermore, our scores were more accurate than the previously published NEWS-2 and 4C Mortality Scores. DISCUSSION AND CONCLUSIONS: The authors developed and validated prognostic scores that use readily available clinical and laboratory information to predict ICU admission and mortality in COVID-19. These scores can become valuable tools to support clinical decisions and improve the allocation of limited health resources.

Clinical Frailty Scale (CFS) indicated frailty is associated with increased in-hospital and 30-day mortality in COVID-19 patients: a systematic review and meta-analysis.

BACKGROUND: The concept of frailty provides an age-independent, easy-to-use tool for risk stratification. We aimed to summarize the evidence on the efficacy of frailty tools in risk assessment in COVID-19 patients. METHODS: The protocol was registered (CRD42021241544). Studies reporting on frailty in COVID-19 patients were eligible. The main outcomes were mortality, length of hospital stay (LOH) and intensive care unit (ICU) admission in frail and non-frail COVID-19 patients. Frailty was also compared in survivors and non-survivors. Five databases were searched up to 24th September 2021. The QUIPS tool was used for the risk of bias assessment. Odds ratios (OR) and weighted mean differences (WMD) were calculated with 95% confidence intervals (CI) using a random effect model. Heterogeneity was assessed using the I2 and χ2 tests. RESULTS: From 3640 records identified, 54 were included in the qualitative and 42 in the quantitative synthesis. Clinical Frailty Scale (CFS) was used in 46 studies, the Hospital Frailty Risk Score (HFRS) by 4, the Multidimensional Prognostic Index (MPI) by 3 and three studies used other scores. We found that patients with frailty (CFS 4-9 or HFRS ≥ 5) have a higher risk of mortality (CFS: OR: 3.12; CI 2.56-3.81; HFRS OR: 1.98; CI 1.89-2.07). Patients with frailty (CFS 4-9) were less likely to be admitted to ICU (OR 0.28, CI 0.12-0.64). Quantitative synthesis for LOH was not feasible. Most studies carried a high risk of bias. CONCLUSIONS: As determined by CFS, frailty is strongly associated with mortality; hence, frailty-based patient management should be included in international COVID-19 treatment guidelines. Future studies investigating the role of frailty assessment on deciding ICU admission are strongly warranted.

A real opportunity to modify cardiovascular risk through primary care and prevention: A pilot study.

Cardiovascular diseases (CVDs) represent a major threat to health and primary prevention outstands as the most effective instrument to face this issue, addressing multiple risk factors at a time and influencing behavioral patterns. Community nurses have been involved in many interdisciplinary prevention activities, resulting in effective control of CV risk factors. We conducted a pilot study aiming at describing the impact on the CV risk profile of an 18-month interdisciplinary intervention on lifestyle habits. From September 2018 to May 2020, four general practitioners (GPs) working in the Roman neighborhood of Torresina recruited patients having a cardiovascular risk score (CRS) equal to or higher than 3% and lower than 20%; those patients were included in a nutritional, physical, and psychological counseling program. Assessments of patients' health status were led at baseline, 6, 12, and 18 months by a nutritionist, a physiotherapist, a psychologist, their GPs, and a community nurse. The CRS was estimated at every examination, based on the Italian Progetto Cuore algorithm. A total of 76 patients were included (mean age of 54.6 years; 33 men and 43 women). Mean CRS showed a significant reduction between baseline and 12 months (from 4.9 to 3.8); both total cholesterol and systolic blood pressure (SBP) significantly decreased at 6 months of follow-up (respectively, from 211.1 to 192 and from 133.1 to 123.1). Nonetheless, the reduction was later maintained only for SBP. However, during the last 6 months of the intervention, the COVID-19 pandemic broke out, thus, it is not possible to know how much the results achieved at 18 months were influenced by the restrictive measures introduced by the Italian government. When stratifying according to the presence of hypertension/diabetes and physical activity, no differences in the CRS could be highlighted between the two groups. Our pilot study proved that an interdisciplinary counseling intervention program can improve CV risk profile and could be further spread to people that, according to their CRS, would benefit more from changes in lifestyles.

Characterizing and Predicting Post-Acute Sequelae of SARS CoV-2 Infection (PASC) in a Large Academic Medical Center in the US.

BACKGROUND: A growing number of Coronavirus Disease-2019 (COVID-19) survivors are affected by post-acute sequelae of SARS CoV-2 infection (PACS). Using electronic health record data, we aimed to characterize PASC-associated diagnoses and develop risk prediction models. METHODS: In our cohort of 63,675 patients with a history of COVID-19, 1724 (2.7%) had a recorded PASC diagnosis. We used a case-control study design and phenome-wide scans to characterize PASC-associated phenotypes of the pre-, acute-, and post-COVID-19 periods. We also integrated PASC-associated phenotypes into phenotype risk scores (PheRSs) and evaluated their predictive performance. RESULTS: In the post-COVID-19 period, known PASC symptoms (e.g., shortness of breath, malaise/fatigue) and musculoskeletal, infectious, and digestive disorders were enriched among PASC cases. We found seven phenotypes in the pre-COVID-19 period (e.g., irritable bowel syndrome, concussion, nausea/vomiting) and sixty-nine phenotypes in the acute-COVID-19 period (predominantly respiratory, circulatory, neurological) associated with PASC. The derived pre- and acute-COVID-19 PheRSs stratified risk well, e.g., the combined PheRSs identified a quarter of the cohort with a history of COVID-19 with a 3.5-fold increased risk (95% CI: 2.19, 5.55) for PASC compared to the bottom 50%. CONCLUSIONS: The uncovered PASC-associated diagnoses across categories highlighted a complex arrangement of presenting and likely predisposing features, some with potential for risk stratification approaches.

Thromboprophylaxis in gynaecology: a review of current evidence

Key content: Thromboembolism is a major cause of preventable morbidity and mortality. Hospital acquired thrombosis (HAT) accounts for 50-60% of all thromboembolic events. As well as effects on patient safety, there are considerable cost implications to both prophylaxis and treatment. While guidance exists on thromboprophylaxis for patients in obstetrics and those undergoing general surgery, there is a paucity of guidance relating to gynaecological practice. Increasing prevalence of risk factors and multimorbidity is paralleled by higher risk of thromboembolic events. Gynaecological surgery presents some unique risk factors for thrombosis. Learning objectives: To understand the basic pathophysiology of thrombosis in relation to risk factors particularly relevant to gynaecology and pelvic surgery. To know the current evidence in key areas relevant to gynaecological practice: early pregnancy;day case surgery;minimally invasive gynaecological surgery;open and complex benign gynaecology and gynaecological oncology. To be aware of proposed guidance on risk assessment and prophylaxis in thrombosis as relevant to the gynaecologist based on current evidence. Ethical issues: Problems with thromboprophylaxis in high-risk patients include noncompliance and refusing animal products/injections. Clinicians may be reluctant to institute thromboprophylaxis, most times because of the possible risks of bleeding. Copyright © 2022 Royal College of Obstetricians and Gynaecologists.