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1.
Medicine (Baltimore) ; 100(41): e27418, 2021 Oct 15.
Article in English | MEDLINE | ID: covidwho-1501202

ABSTRACT

ABSTRACT: The occurrence of COVID-19 pandemic had a significant negative effect on health care systems over the last year. Health care providers were forced to focus mainly on COVID-19 patients, neglecting in many cases equally important diseases, both acute and chronic. Therefore, also screening and diagnostic strategies for HIV could have been significantly impaired.This retrospective, multicenter, observational study aimed at assessing the number and characteristics of new HIV/AIDS diagnoses during COVID-19 pandemic in Italy and compared characteristics of people living with HIV at diagnosis between pre- and post-COVID-19 era (2019 vs 2020).Our results showed a significant reduction of HIV diagnoses during pandemic. By contrast, people living with HIV during pandemic were older and were diagnosed in earlier stage of disease (considering CD4+ T cell count) compared to those who were diagnosed the year before. Moreover, there was a significant decrease of new HIV diagnoses among men who have sex with men, probably for the impact of social distancing and restriction applied by the Italian Government. Late presentation incidence, if numbers in 2020 were lower than those in 2019, is still an issue.Routinely performing HIV testing in patients with suspected SARS-CoV-2 infection is identifying and linking to care underdiagnosed people living with HIV earlier. Thus, combined tests (HIV and SARS-CoV-2) should be implemented in patients with SARS-CoV-2 symptoms overlapping HIV's ones. Lastly, our results lastly showed how urgent implementation of a national policy for HIV screening is necessary.


Subject(s)
Delivery of Health Care/organization & administration , HIV Infections/epidemiology , Mass Screening/statistics & numerical data , Adult , CD4 Lymphocyte Count/statistics & numerical data , COVID-19/epidemiology , Cross-Sectional Studies , Female , HIV Infections/diagnosis , Humans , Italy/epidemiology , Male , Mass Screening/organization & administration , Middle Aged , Pandemics , Retrospective Studies , Risk Factors , SARS-CoV-2
2.
Open Forum Infect Dis ; 8(7): ofab283, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1324646

ABSTRACT

We compared 90-90-90 targets in 2020, during the coronavirus disease 2019 (COVID-19) pandemic, with the targets across the period 2017-2019 in people with HIV. We observed a significant loss in the 90-90-90 objectives in 2020 when compared with 2017-2019 that might be attributable to the COVID-19 crisis.

3.
PLoS One ; 15(11): e0239172, 2020.
Article in English | MEDLINE | ID: covidwho-922701

ABSTRACT

AIMS: The aim of this study was to estimate a 48 hour prediction of moderate to severe respiratory failure, requiring mechanical ventilation, in hospitalized patients with COVID-19 pneumonia. METHODS: This was an observational prospective study that comprised consecutive patients with COVID-19 pneumonia admitted to hospital from 21 February to 6 April 2020. The patients' medical history, demographic, epidemiologic and clinical data were collected in an electronic patient chart. The dataset was used to train predictive models using an established machine learning framework leveraging a hybrid approach where clinical expertise is applied alongside a data-driven analysis. The study outcome was the onset of moderate to severe respiratory failure defined as PaO2/FiO2 ratio <150 mmHg in at least one of two consecutive arterial blood gas analyses in the following 48 hours. Shapley Additive exPlanations values were used to quantify the positive or negative impact of each variable included in each model on the predicted outcome. RESULTS: A total of 198 patients contributed to generate 1068 usable observations which allowed to build 3 predictive models based respectively on 31-variables signs and symptoms, 39-variables laboratory biomarkers and 91-variables as a composition of the two. A fourth "boosted mixed model" included 20 variables was selected from the model 3, achieved the best predictive performance (AUC = 0.84) without worsening the FN rate. Its clinical performance was applied in a narrative case report as an example. CONCLUSION: This study developed a machine model with 84% prediction accuracy, which is able to assist clinicians in decision making process and contribute to develop new analytics to improve care at high technology readiness levels.


Subject(s)
Computer Simulation , Coronavirus Infections/complications , Machine Learning , Pneumonia, Viral/complications , Respiratory Insufficiency/diagnosis , Aged , Betacoronavirus , Blood Gas Analysis , COVID-19 , Female , Humans , Italy , Male , Middle Aged , Models, Statistical , Pandemics , Prospective Studies , Respiration, Artificial , Respiratory Insufficiency/etiology , SARS-CoV-2
4.
Lancet Rheumatol ; 2(8): e474-e484, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-612713

ABSTRACT

Background: No therapy is approved for COVID-19 pneumonia. The aim of this study was to assess the role of tocilizumab in reducing the risk of invasive mechanical ventilation and death in patients with severe COVID-19 pneumonia who received standard of care treatment. Methods: This retrospective, observational cohort study included adults (≥18 years) with severe COVID-19 pneumonia who were admitted to tertiary care centres in Bologna and Reggio Emilia, Italy, between Feb 21 and March 24, 2020, and a tertiary care centre in Modena, Italy, between Feb 21 and April 30, 2020. All patients were treated with the standard of care (ie, supplemental oxygen, hydroxychloroquine, azithromycin, antiretrovirals, and low molecular weight heparin), and a non-randomly selected subset of patients also received tocilizumab. Tocilizumab was given either intravenously at 8 mg/kg bodyweight (up to a maximum of 800 mg) in two infusions, 12 h apart, or subcutaneously at 162 mg administered in two simultaneous doses, one in each thigh (ie, 324 mg in total), when the intravenous formulation was unavailable. The primary endpoint was a composite of invasive mechanical ventilation or death. Treatment groups were compared using Kaplan-Meier curves and Cox regression analysis after adjusting for sex, age, recruiting centre, duration of symptoms, and baseline Sequential Organ Failure Assessment (SOFA) score. Findings: Of 1351 patients admitted, 544 (40%) had severe COVID-19 pneumonia and were included in the study. 57 (16%) of 365 patients in the standard care group needed mechanical ventilation, compared with 33 (18%) of 179 patients treated with tocilizumab (p=0·41; 16 [18%] of 88 patients treated intravenously and 17 [19%] of 91 patients treated subcutaneously). 73 (20%) patients in the standard care group died, compared with 13 (7%; p<0·0001) patients treated with tocilizumab (six [7%] treated intravenously and seven [8%] treated subcutaneously). After adjustment for sex, age, recruiting centre, duration of symptoms, and SOFA score, tocilizumab treatment was associated with a reduced risk of invasive mechanical ventilation or death (adjusted hazard ratio 0·61, 95% CI 0·40-0·92; p=0·020). 24 (13%) of 179 patients treated with tocilizumab were diagnosed with new infections, versus 14 (4%) of 365 patients treated with standard of care alone (p<0·0001). Interpretation: Treatment with tocilizumab, whether administered intravenously or subcutaneously, might reduce the risk of invasive mechanical ventilation or death in patients with severe COVID-19 pneumonia. Funding: None.

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