Dalbavancin in catheter-related bloodstream infections: a pilot study.

Background: Catheter-related bloodstream infections (CRBSI) represent a frequent complication of vascular catheterization, with high morbidity, mortality, and associated costs. Most infections are caused by Gram-positive bacteria; thus dalbavancin, a new long-acting lipoglicopeptide, may have a role in early patient discharge strategies optimizing treatment and reducing overall costs. Methods: In this small pilot feasibility study, we assessed the efficacy and safety of a "single step" treatment strategy combining dalbavancin administration (1500 mg IV single dose), catheter removal, and early discharge in adult patients admitted to medical wards in a three-year period. Results: We enrolled sixteen patients with confirmed Gram-positive CRBSI, with a mean age of 68 years and relevant comorbidities (median Charlson Comorbidity index=7). The most frequent causative agents were staphylococci, with 25% of methicillin-resistant strains, and the majority of infected devices were short term central venous catheter (CVC) and peripherally inserted central catheter (PICC). Ten out of sixteen patients had been treated empirically before dalbavancin administration. The mean time from dalbavancin administration to discharge was 2 days; none of the patients had adverse drug-related reactions; at 30- and 90-day follow-up, no patients have been readmitted to the hospital due to bacteraemia recurrence. Conclusions: Our results indicate that single-dose dalbavancin is highly effective, well-tolerated, and cost-saving for Gram-positive CRBSI.

Mortality predictors in hospitalised COVID-19 patients and the role of anti-SARS-CoV-2 IgG antibodies and remdesivir.

Background: In a pre-vaccination era serologic tests may be used to evaluate the seroprevalence and efficacy of containment strategies applied to the community. Subsequently, SARS-CoV-2 vaccination has successfully reduced hospitalization and admission to intensive care. The role of antiviral treatment for COVID-19 remains debated. Objective: We investigated the effect of SARS-CoV-2 IgG Spike (S) antibody responses in hospitalized patients on 30-day mortality. Finally, we assessed whether other predictive factors affected mortality after 30 days. Methods: Observational study on COVID-19 patients admitted from October 1, 2021, to January 30, 2022. Results: 520 patients were studied; 108 died at the 30-day follow-up (21%). A borderline significance for mortality was observed in favour of the high antibody titer group (24% vs 17%, p=0.05). From the univariate Cox regression analysis, a high IgG-S titer was significantly correlated to lower 30-day mortality (p=0.04, HR: 0.7; 95%CI: 0.44-0.98). The administration of remdesivir (p=0.01) and the age <65 years (p=2.3e-05) were found to be protective for the considered outcome (respectively, HR: 0.5, 95%CI: 0.34-0.86, and HR: 0.1, 95%CI: 0.04-0.30). Conclusions: S-antibodies and remdesivir could play a protecting role in increasing the survival of hospitalized COVID-19 patients who are not suffering from a critical disease. Advanced age is a risk factor for poor outcomes among infected people.

Real-life experience with remdesivir for treatment of COVID-19 among older adults: a multicentre retrospective study.

INTRODUCTION: The effect of remdesivir on COVID-19 mortality remains conflicting. Elderly individuals are at risk for poor COVID-19 outcomes. We aimed to assess the effect of remdesivir on COVID-19 mortality among elderly individuals, using real-world data. METHODS: Retrospective multinational cohort of individuals aged ≥65 years, hospitalized with COVID-19 in six medical centres between January 2020 and May 2021. Associations with in-hospital mortality were evaluated using a multivariable logistic regression model with propensity score adjustment for remdesivir therapy and while implementing generalized estimating equations to control for centre effect. Sensitivity analysis was performed by stratification according to the degree of respiratory support. RESULTS: Of 3010 individuals included, 2788 individuals required either oxygen supplementation or non-invasive/invasive mechanical ventilation, 489 (16%) were treated with remdesivir, and 836 (28%) died. Median age was 77 (IQR 70-84) years and 42% were women. Remdesivir was the only therapeutic intervention associated with decreased mortality [adjusted OR (aOR) 0.49, 95% CI 0.37-0.66, P < 0.001]. This protective effect was shown for individuals requiring oxygen support and non-invasive mechanical ventilation, while no association was found among individuals necessitating invasive mechanical ventilation.Risk factors for mortality included invasive ventilation (aOR 5.18, 95% CI 2.46-10.91, P < 0.001), higher serum creatinine (aOR 1.25, 95% CI 1.09-1.43, P = 0.001) and dyspnoea (aOR 1.40, 95% CI 1.07-1.84, P = 0.015) on presentation, and other non-modifiable factors, such as comorbidities. CONCLUSIONS: Among elderly individuals hospitalized with COVID-19, remdesivir carries survival benefit for those with moderate to severe disease. Its role among individuals with critical illness should be further assessed.

Predictors of survival in elderly patients with coronavirus disease 2019 admitted to the hospital: derivation and validation of the FLAMINCOV score.

OBJECTIVE: To identify predictors of 30-day survival in elderly patients with coronavirus disease 2019 (COVID-19). METHODS: Retrospective cohort study including patients with COVID-19 aged ≥65 years hospitalized in six European sites (January 2020 to May 2021). Data on demographics, comorbidities, clinical characteristics, and outcomes were collected. A predictive score (FLAMINCOV) was developed using logistic regression. Regression coefficients were used to calculate the score. External validation was performed in a cohort including elderly patients from a major COVID-19 centre in Israel. Discrimination was evaluated using the area under the receiver operating characteristic curve (AUC) in the derivation and validation cohorts. Survival risk groups based on the score were derived and applied to the validation cohort. RESULTS: Among 3010 patients included in the derivation cohort, 30-day survival was 74.5% (2242/3010). The intensive care unit admission rate was 7.6% (228/3010). The model predicting survival included independent functional status (OR, 4.87; 95% CI, 3.93-6.03), a oxygen saturation to fraction of inspired oxygen (SpO2/FiO2) ratio of >235 (OR, 3.75; 95% CI, 3.04-4.63), a C-reactive protein level of <14 mg/dL (OR, 2.41; 95% CI, 1.91-3.04), a creatinine level of <1.3 (OR, 2.02; 95% CI, 1.62-2.52) mg/dL, and absence of fever (OR, 1.34; 95% CI, 1.09-1.66). The score was validated in 1174 patients. The FLAMINCOV score ranges from 0 to 15 and showed good discrimination in the derivation (AUC, 0.79; 95% CI, 0.77-0.81; p < 0.001) and validation cohorts (AUC, 0.79; 95% CI, 0.76-0.81; p < 0.001). Thirty-day survival ranged from 39.4% (203/515) to 95.3% (634/665) across four risk groups according to score quartiles in the derivation cohort. Similar proportions were observed in the validation set. DISCUSSION: The FLAMINCOV score identifying elderly with higher or lower chances of survival may allow better triage and management, including intensive care unit admission/exclusion.

Home management of COVID-19 symptomatic patients: a safety study on COVID committed home medical teams.

To reduce the overburden in the hospital, during the COVID-19 pandemic, some "COVID Committed Home Medical Teams" (CCHTs) were created in Italy. These units consist of a small pool of general practitioners who aim to evaluate all patients with COVID-19 who require a medical examination directly at home. After the first visit (which can end with patient hospitalisation or home management), CCHTs periodically monitor the patients' clinical conditions and vital signs (usually a revaluation every 24-48 hours, except for a sudden worsening). However, this strategy - which reduces the pressure on hospitals - has never been evaluated for patient safety. Our study aims to determine whether a home-based monitoring and treatment strategy for non-severe COVID-19 patients was safe as direct hospital admission by the emergency department. We conducted a retrospective observational study about 1,182 patients admitted to the hospital for COVID-19 between September 2020 and April 2021, confronting in-hospital and 30-day mortality in both CCHT-referred (n=275) and directly admitted by emergency department (n=907). Patients assessed by the CCHT had lower in-hospital and 30-day mortality (18% vs 28%, p=0.001; and 20% vs 30%, p=0.002); but, in the propensity score matching comparison, there was no characteristic between the two groups turned out significantly different. CCHT did not correlate with in-hospital or 30-day mortality. CCHT is a safe strategy to reduce hospital overburden for COVID-19 during pandemic surges.

Development and Validation of the Acute PNeumonia Early Assessment Score for Safely Discharging Low-Risk SARS-CoV-2-Infected Patients from the Emergency Department.

A continuous demand for assistance and an overcrowded emergency department (ED) require early and safe discharge of low-risk severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected patients. We developed (n = 128) and validated (n = 330) the acute PNeumonia early assessment (aPNea) score in a tertiary hospital and preliminarily tested the score on an external secondary hospital (n = 97). The score's performance was compared to that of the National Early Warning Score 2 (NEWS2). The composite outcome of either death or oral intubation within 30 days from admission occurred in 101 and 28 patients in the two hospitals, respectively. The area under the receiver operating characteristic (AUROC) curve of the aPNea model was 0.86 (95% confidence interval (CI), 0.78-0.93) and 0.79 (95% CI, 0.73-0.89) for the development and validation cohorts, respectively. The aPNea score discriminated low-risk patients better than NEWS2 at a 10% outcome probability, corresponding to five cut-off points and one cut-off point, respectively. aPNea's cut-off reduced the number of unnecessary hospitalizations without missing outcomes by 27% (95% CI, 9-41) in the validation cohort. NEWS2 was not significant. In the external cohort, aPNea's cut-off had 93% sensitivity (95% CI, 83-102) and a 94% negative predictive value (95% CI, 87-102). In conclusion, the aPNea score appears to be appropriate for discharging low-risk SARS-CoV-2-infected patients from the ED.

Artificial neural network model from a case series of COVID-19 patients: a prognostic analysis.

BACKGROUND AND AIM: There is a need to determine which clinical variables predict the severity of COVID-19. We analyzed a series of critically ill COVID-19 patients to see if any of our dataset's clinical variables were associated with patient outcomes. METHODS: We retrospectively analyzed the data of COVID-19 patients admitted to the ICU of the Hospital in Pordenone from March 11, 2020, to April 17, 2020. Patients' characteristics of survivors and deceased groups were compared. The variables with a different distribution between the two groups were implemented in a generalized linear regression model (LM) and in an Artificial Neural Network (NN) model to verify the "robustness" of the association with mortality. RESULTS: In the considered period, we reviewed the data of 22 consecutive patients: 8 died. The causes of death were a severe respiratory failure (3), multi-organ failure (1), septic shock (1), pulmonary thromboembolism (2), severe hemorrhage (1). Lymphocyte and the platelet count were significantly lower in the group of deceased patients (p-value 0.043 and 0.020, respectively; cut-off values: 660/mm3; 280,000/mm3, respectively). Prothrombin time showed a statistically significant trend (p-value= 0.065; cut-off point: 16.8/sec). The LM model (AIC= 19.032), compared to the NN model (Mean Absolute Error, MAE = 0.02), was substantially alike (MSE 0.159 vs. 0.136). CONCLUSIONS: In the context of critically ill COVID-19 patients admitted to ICU, lymphocytopenia, thrombocytopenia, and lengthening of prothrombin time were strictly correlated with higher mortality. Additional clinical data are needed to be able to validate this prognostic score.

Classification and analysis of outcome predictors in non-critically ill COVID-19 patients.

BACKGROUND: Early detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected patients who could develop a severe form of COVID-19 must be considered of great importance to carry out adequate care and optimise the use of limited resources. AIMS: To use several machine learning classification models to analyse a series of non-critically ill COVID-19 patients admitted to a general medicine ward to verify if any clinical variables recorded could predict the clinical outcome. METHODS: We retrospectively analysed non-critically ill patients with COVID-19 admitted to the general ward of the hospital in Pordenone from 1 March 2020 to 30 April 2020. Patients' characteristics were compared based on clinical outcomes. Through several machine learning classification models, some predictors for clinical outcome were detected. RESULTS: In the considered period, we analysed 176 consecutive patients admitted: 119 (67.6%) were discharged, 35 (19.9%) dead and 22 (12.5%) were transferred to intensive care unit. The most accurate models were a random forest model (M2) and a conditional inference tree model (M5) (accuracy = 0.79; 95% confidence interval 0.64-0.90, for both). For M2, glomerular filtration rate and creatinine were the most accurate predictors for the outcome, followed by age and fraction-inspired oxygen. For M5, serum sodium, body temperature and arterial pressure of oxygen and inspiratory fraction of oxygen ratio were the most reliable predictors. CONCLUSIONS: In non-critically ill COVID-19 patients admitted to a medical ward, glomerular filtration rate, creatinine and serum sodium were promising predictors for the clinical outcome. Some factors not determined by COVID-19, such as age or dementia, influence clinical outcomes.

An Unusual Case of Cholestatic Hepatitis due to Light-Chain Deposition Disease.

Light-chain deposition disease (LCDD) is a rare paraproteinaemia characterized by the deposition of monoclonal immunoglobulins with a non-fibrillar structure and hence Congo red negative deposits. Kidney disease is the more frequent manifestation, but other organs may also be involved. A 70-year-old man with hypertension and mild chronic renal failure showed a hepatomegaly without splenomegaly. His renal and liver test rapidly got worse. A serum electrophoresis and immunofixation isolated monoclonal kappa light-chain gammopathy, with serum free kappa light chain excess. The bone marrow biopsy showed the presence of interstitial infiltration of plasma cells like multiple myeloma type at initial phase. Periumbilical fat biopsy was negative. Echocardiography demonstrated an infiltrative cardiac disease. The biopsies of the duodenum small intestine mucosa showed flaps with eosinophil material (Masson's staining) with atrophic crypts and chronic inflammation at chorion level. Amyloid substance was negative. There was a strong positivity for light chains kappa compatible with LCDD. A liver biopsy confirmed this finding. Therapy with dexamethasone and bortezomib improved clinical state and hepatic and renal laboratory tests. Chemotherapy based on novel anti-myeloma agents should be rapidly considered in LCDD patients with severe organ involvement.

Serum complement C3 correlates with insulin resistance in never treated psoriatic arthritis patients.

The objective of this cross-sectional study is to investigate the relationship between inflammatory markers (C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), white blood cell (WBC) count, and complement C3) and insulin resistance (estimated with the surrogate measure homeostasis model assessment of insulin resistance (HOMA-IR)) in Psoriatic arthritis (PsA) patients. Sixty-seven patients with PsA and 138 age- and sex-matched controls were recruited from the Rheumatology Outpatient Clinic of the University of Catanzaro, Catanzaro (Italy). Plasma glucose, insulin, triglycerides, total cholesterol, LDL cholesterol, and high-density lipoprotein (HDL) cholesterol were measured after at least 12-h fasting. CRP was measured by a high-sensitivity turbidimetric immunoassay. ESR was measured by capillary photometry. Serum C3 and C4 were measured by nephelometry. Insulin resistance was estimated using the original HOMA as reported by Matthews et al. (Diabetologia 28(7):412-419, 1985) from overnight fasting insulin and glucose values, with the following formula: HOMA-IR = glucose (in milligrams per deciliter) × insulin (in micro units per milliliter)/405. Patients and controls had similar body mass index (BMI), blood pressure, and fasting glucose, but fasting serum insulin was higher in PsA patients (median (interquartile range (IQR)) 12.96 (6.35-24.65) for PsA and 10.37 (6.97-15.11) for controls; p = 0.005). Consequently, also the surrogate measure of insulin resistance HOMA-IR was significantly higher in patients (median (IQR) 3.77 (1.58-5.18) for PsA and 2.33 (1.67-3.62) for controls; p = 0.008). In univariate analysis, ln(HOMA-IR) correlated positively with BMI, systolic blood pressure (sBP), dBP, ln(TG), WBC, ln(ESR), ln(CRP) and C3, while correlated negatively with total and HDL cholesterol. In multiple linear regression analysis including age, sex and BMI, serum C3 reached the higher standardized ß coefficient, while among other variables only ln(ESR) maintained a weak correlation with ln(HOMA-IR) when sBP was added to the model. When all variables were inserted in a single model, only C3 was independently correlated with ln(HOMA-IR). In a stepwise multiple regression model, serum C3 was selected as the strongest single contributing variable. The model explained 61 % of the variance in ln(HOMA-IR) (R (2) = 0.61). Insulin resistance, estimated with the surrogate measure HOMA-IR, is higher in PsA patients compared to age- and sex-matched controls. Serum C3 could represent a simple marker of insulin resistance in psoriatic arthritis patients.

Usefulness of hemoglobin A1c as a criterion to define the metabolic syndrome in a cohort of italian nondiabetic white subjects.

We compared the performance of hemoglobin A1c (HbA1c) versus the fasting plasma glucose (FPG) in diagnosing the metabolic syndrome and assessed the diagnostic accuracy of the metabolic syndrome definition using HbA1c in identifying insulin-resistant subjects. The cardiometabolic risk factors, HbA1c, and glucose tolerance were analyzed in 774 nondiabetic white subjects. Insulin sensitivity was estimated with an oral glucose tolerance test-derived insulin sensitivity index. Insulin resistance was defined as the lower quartile of insulin sensitivity index. A 90.9% agreement existed between the use of HbA1c and the FPG for diagnosis of the metabolic syndrome (κ coefficient = 0.813); however, the proportion of subjects who met the metabolic syndrome criteria using the HbA1c was greater (42.1% vs 39.7%). Compared to the subjects who met the metabolic syndrome criteria using the FPG alone, those with the metabolic syndrome using the HbA1c-alone criterion were younger, had greater visceral adiposity, greater levels of inflammatory markers and liver enzymes, and lower blood pressure. In a logistic regression analysis with adjustment for age and gender, the subjects with the metabolic syndrome using the HbA1c criterion only had a 3.6-fold increase risk of having insulin resistance, defined as the lowest quartile of the insulin sensitivity index. A similar risk (3.8-fold) was observed in those who met the metabolic syndrome criteria using FPG alone. Insulin-resistant subjects who did not meet the criteria for the metabolic syndrome using the HbA1c had an unfavorable cardiovascular disease risk profile. In conclusion, although a good agreement existed between the HbA1c and FPG criteria for the diagnosis of the metabolic syndrome, appreciably different groups of subjects were classified using each method.

One-hour postload plasma glucose levels are associated with kidney dysfunction.

BACKGROUND AND OBJECTIVES: A cutoff of 155 mg/dl for 1-hour postload plasma glucose (1hPG) during the oral glucose tolerance test (OGTT) is able to identify patients who are at high risk for type 2 diabetes and vascular atherosclerosis. We aimed to examine whether individuals with 1hPG ≥155 mg/dl are also at increased risk for chronic kidney disease (CKD). DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Atherosclerosis risk factors, OGTT, and estimated GFR by Chronic Kidney Disease Epidemiology Collaboration equation were analyzed in 1075 white individuals without diabetes. RESULTS: The area under the receiver operating characteristic curve for 1hPG was the highest (0.700) compared with the areas under the receiver operating characteristic curve of 0, 30-minute, and 2-hour glucose concentrations. Individuals with 1hPG ≥155 mg/dl had a worse cardiometabolic risk profile, exhibiting significantly higher body mass index, BP, triglycerides, and fasting insulin levels and lower HDL, IGF-1 levels, and insulin sensitivity, than individuals with 1hPG <155 mg/dl. Estimated GFR was significantly lower in individuals with 1hPG ≥155 mg/dl. In a logistic regression model adjusted for age and gender, individuals with 1hPG ≥155 mg/dl showed an increased risk for CKD compared with individuals with 1hPG <155 mg/dl. When the logistic regression analysis was restricted to individuals who had normal glucose tolerance, those with 1hPG ≥155 mg/dl showed a higher risk for CKD compared with individuals with 1hPG <155 mg/dl. CONCLUSIONS: These data suggest that a cutoff point of 155 mg/dl for the 1hPG during OGTT may be helpful in the identification of individuals who are at increased risk for CKD.

Positive association between plasma IGF1 and high-density lipoprotein cholesterol levels in adult nondiabetic subjects.

AIMS: Low IGF1 levels have been associated with an increased cardiovascular risk. It is unknown however whether IGF1 mediates the atherosclerotic process by modulating high-density lipoprotein cholesterol (HDL-C) independently from confounders. To address this issue, we evaluated the association between IGF1 levels and HDL-C in nondiabetic subjects. METHODS: A cross-sectional analysis was used in the context of the CAtanzaro MEtabolic RIsk factors Study. One thousand and four participants (aged 20-69 years), for whom HDL-C and IGF1 measurements were available, were eligible for the study. RESULTS: After adjusting for gender and age, IGF1 levels were positively correlated with HDL-C, and negatively correlated with body mass index (BMI), waist circumference, blood pressure (BP), triglyceride, fasting insulin, and homeostasis model assessment (HOMA). In a logistic regression model adjusted for age and gender, IGF1 in the lowest tertile (<125 ng/ml) was associated with an increased risk of having low HDL-C (odds ratio (OR) 2.14, 95% confidence interval (CI) 1.4-3.0; P=4x10(-5)) compared with the highest tertile (>186 ng/ml). When BMI, waist circumference, total cholesterol, triglyceride, and HOMA index were added to the model, IGF1 remained significantly associated with increased risk of low HDL-C (OR 1.52, 95% CI 1.01-2.31; P=0.04). A stepwise multivariate regression analysis in a model including age, gender, BMI, total cholesterol, triglycerides, IGF1, HOMA, and BP showed that the variables significantly associated with HDL-C were gender (P<0.0001), triglycerides (P<0.0001), total cholesterol (P<0.0001), BMI (P<0.0001), IGF1 levels (P<0.0001), and HOMA (P=0.001), accounting for 32.6% of its variation. CONCLUSIONS: These data provide evidence that IGF1 may be an independent modulator for HDL-C in nondiabetic individuals.

Differences in cardiovascular risk profile based on relationship between post-load plasma glucose and fasting plasma levels.

BACKGROUND: It has been shown that subjects with normal glucose tolerance (NGT), whose plasma glucose (PG) levels do not return to their fasting PG level within 2 h during an oral glucose tolerance test (OGTT) (Group I), have a significantly higher risk to develop type 2 diabetes than NGT subjects whose 2-h glucose returns to, or drops below, the fasting level (Group I). However, it is still unsettled whether individuals in Group II have a more atherogenic profile than Group I subjects. METHODS: To address this issue, we examined 266 non-diabetic offspring of type 2 diabetic patients, recruited in the context of EUGENE2 cross-sectional study. All subjects underwent an euglycaemic-hyperinsulinemic clamp to assess glucose tolerance and insulin sensitivity. Furthermore, cardiovascular risk factors and ultrasound measurement of carotid intima-media thickness (IMT) were evaluated. RESULTS: Individuals in Group II exhibited significantly higher waist circumference, blood pressure, triglycerides, 2-h post-load PG, hsC-reactive protein, interleukin-6, insulin-like growth factor-1 (IGF-1), IMT, and lower insulin sensitivity than subjects in Group I. CONCLUSIONS: Subjects with NGT, whose PG concentration does not return to their fasting PG level within 2 h during OGTT, have an atherogenic profile, suggesting that performing OGTT with measurement of PG every 30 min may be useful to assess the risk for cardiovascular disease in glucose-tolerant subjects.