Internal and emergency medicine
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Observational Study
Phenobarbital use in benzodiazepine and z-drug detoxification: a single-centre 15-year observational retrospective study in clinical practice.
Given the increase in benzodiazepine (BZD) and Z-drug (ZD) use disorder, this study described the use of phenobarbital (PHB) as detoxification in clinical practice. A 15-year observational retrospective study was performed on medical records of BZD-ZD use disorder patients detoxified with PHB at the Toxicology Unit and Poison Centre, Careggi University Hospital, Florence (Italy). A multivariate logistic regression was used to estimate odd ratios (ORs) and related 95% confidence intervals (CI) of "treatment failure" considering demographic and pharmacological characteristics. "Hospitalisation length", "PHB discharge dose", and "BZD-ZD free status" at discharge were also calculated. ⋯ Analysis showed a higher probability to be BZD-ZD free at discharge for subjects who reported to be employed (OR 2.29; CI 95% 1.00-5.24), for those who abused oral drops of BZD-ZD (OR 2.16, CI 1.30-3.59), and for those treated with trazodone (OR 2.86, CI 1.14-7.17) during hospital stay. A hospitalisation length of > 7 days was observed for patients with opioid maintenance therapy (OR 2.07, CI 1.20-3.58) for substance use disorder, and for those treated with more than 300 mg/day of PHB equivalents at hospital admission (OR 1.68, CI 1.03-2.72). Our results suggested that PHB can be considered a valuable detoxification option for different types of BZD and ZD use disorder patients.
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Review Meta Analysis
High-dose versus low-dose venous thromboprophylaxis in hospitalized patients with COVID-19: a systematic review and meta-analysis.
Hospitalized COVID-19 patients are at high risk of venous thromboembolism (VTE). Standard doses of anticoagulant prophylaxis may not be sufficiently effective for the prevention of VTE. The objective of this systematic-review and meta-analysis was to compare the efficacy and safety of high-dose versus low-dose thromboprophylaxis in hospitalized patients with COVID-19. ⋯ In hospitalized patients with COVID-19, high-dose thromboprophylaxis is more effective than low-dose for the prevention of VTE but increases the risk of major bleeding.
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Machine learning (ML) techniques may improve readmission prediction performance in heart failure (HF) patients. This study aimed to assess the ability of ML algorithms to predict unplanned all-cause 30-day readmissions in HF elderly patients, and to compare them with conventional LACE (Length of hospitalization, Acuity, Comorbidities, Emergency department visits) index. All patients aged ≥ 65 years discharged alive between 2010 and 2019 after a hospitalization for acute HF were included in this retrospective cohort study. ⋯ Among elderly patients, the rate of all-cause unplanned 30-day readmissions after hospitalization due to an acute HF was high. ML models performed better than the conventional LACE index for predicting readmissions. ML models can be proposed as promising tools for the identification of subjects at high risk of hospitalization in this clinical setting, enabling care teams to target interventions for improving overall clinical outcomes.
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The CHA2DS2-VASc score incorporates several comorbidities which have prognostic implications in COVID-19. We assessed whether a modified score (M-R2CHA2DS2-VASc), which includes pre-admission kidney function and male sex, could be used to classify mortality risk among people hospitalized with COVID-19. This retrospective study included adults admitted for COVID-19 between March and December 2020. ⋯ Higher category was also associated with increased need for mechanical ventilation and renal replacement therapy. All-cause 90-day mortality remained significantly associated with M-R2CHA2DS2-VASc. The M-R2CHA2DS2-VASc score is associated with 30-day mortality rates among patients hospitalized with COVID-19, and adds predictive value when combined with initial COVID-19 severity.