ABSTRACT
Background: One of the main challenges in the management of COVID-19 patients is to early assess and stratify them according to their risk of developing severe pneumonia. The alveolar−arterial oxygen gradient (D(A-a)O2) is defined as the difference between the alveolar and arteriolar concentration of oxygen, an accurate index of the ventilatory function. The aim of this study is to evaluate D(A-a)O2 as a marker for predicting severe pneumonia in COVID-19 patients, in comparison to the PaO2/FiO2. Methods: This retrospective, multicentric cohort study included COVID-19 patients admitted to two Italian hospitals between April and July 2020. Clinical and laboratory data were retrospectively collected at the time of hospital admission and during hospitalization. The presence of severe COVID-19 pneumonia was evaluated, as defined by the Infectious Diseases Society of America (IDSA) criteria for community-acquired pneumonia (CAP). Patients were divided in severe and non-severe groups. Results: Overall, 53 COVID-19 patients were included in the study: male were 30/53 (57%), and 10/53 (19%) had severe pneumonia. Patients with severe pneumonia reported dyspnea more often than non-severe patients (90% vs. 39.5%; p = 0.031). A history of chronic obstructive pulmonary disease (COPD) was recalled by 5/10 (50%) patients with severe pneumonia, and only in 6/43 (1.4%) of non-severe cases (p = 0.023). A ROC curve, for D(A-a)O2 >60 mmHg in detecting severe pneumonia, showed an area under the curve (AUC) of 0.877 (95% CI: 0.675−1), while the AUC of PaO2/FiO2 < 263 mmHg resulted 0.802 (95% CI: 0.544−1). D(A-a)O2 in comparison to PaO2/FiO2 had a higher sensibility (77.8% vs. 66.7%), positive predictive value (75% vs. 71.4%), negative predictive value (94% vs. 91%), and similar specificity (94.4% vs. 95.5%). Conclusions: Our study suggests that the D(A-a)O2 is more appropriate than PaO2/FiO2 to identify COVID-19 patients at risk of developing severe pneumonia early.
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During the Coronavirus Disease 2019 (COVID-19) pandemic, an increasing number of fungal infections associated with SARS-CoV-2 infection have been reported. Among them, cryptococcosis could be a life-threatening disease. We performed a Systematic Review (PRISMA Statement) of cryptococcosis and COVID-19 co-infection, case report/series were included: a total of 34 cases were found, then we added our case report. We collected patients' data and performed a statistical analysis comparing two groups of patients sorted by outcome: "dead" and "alive". Three cases were excluded for lack of information. To compare categorical data, we used a Fisher-exact test (α=0.05). To compare quantitative variables a U Mann-Whitney test was used (α=0.05), with a 95% Confidence Interval. A total of 32 co-infected patients were included in the statistical analysis. Mortality rate was 17/32 (53.1%): these patients were included in "dead" group, and 15/32 (46.9%) patients survived and were included in "alive" group. Overall, males were 25/32 (78.1%), the median age was 60 years (IQR 53-70) with non-statistically significant difference between groups (p=0.149 and p=0.911, respectively). Three variables were associated with mortality: ARDS, ICU admission and inadequate treatment. Overall, 21 out of 24 (87.5%) patients were in ARDS with a statistically significant difference among two groups (p=0.028). ICU admission for COVID-19 was observed in 18/26 (69.2%), more frequently among dead group (p=0.034). Finally, 15/32 (46.9%) patients had adequate treatment (amphotericin B + flucytosine for invasive cryptococcosis) mostly among alive patients (p=0.039). In conclusion, mortality due to cryptococcal infection among COVID-19 patients remains high but an early diagnosis and appropriate treatment could reduce mortality.
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AIM: The authors examined a cohort of HIV-positive outpatients at the AIDS Center of Palermo University in Italy in order to identify factors related to the frequency of their visits to the outpatient facility for health care services. METHODS: Two hundred and twenty-four HIV-infected subjects were enrolled in the study. Demographic and HIV disease characteristics were recorded and assessed with the number of days accessed to our outpatients unit in univariate and multivariate analyses. The potential relationship with immunological status was also analyzed stratifying the patients into groups according to their CD4(+) T-cell counts (≥500 vs <500/mm(3), and ≥200 vs <200/mm(3)). RESULTS: Both univariate and multivariate analyses showed that duration of antiretroviral therapy <5 years and hypertension were significantly associated with a CD4(+) T-cell count of <500/mm(3), whereas geographic origin (Africa) was associated with a CD4(+) T-cell count of <200/mm(3). Mean number of days the patients sought access to day-care services for laboratory tests was negatively associated with CD4(+) T-cell count. CONCLUSION: Patients with low CD4(+) T-cell counts showed higher use of health care services, demonstrating how early HIV diagnosis can help to reduce health care costs. The CD4(+) T-cell cut-off of 200 cells emphasizes the importance of identifying and managing HIV infection among hard-to-reach groups like vulnerable migrants. In our sample, the illegal status of immigrants does not influence the management of their HIV/AIDS condition, but the lack of European health card that documents the current antiretroviral status, could interfere with the efforts to eradicate AIDS. A better understanding of the major determinants of HIV treatment costs has led to appropriate large-scale actions, which in turn has increased resources and expanded intervention programs. Further guidance should be offered to hard-to-reach groups in order to improve early AIDS diagnosis, and procedures for identifying and managing these vulnerable subjects should be made available to care commissioners and service providers.
ABSTRACT
INTRODUCTION: The increased life expectancy of HIV patients in the era of highly active antiretroviral therapy has had profound consequences for the healthcare systems that provide their care. It is useful to assess whether healthcare resources need to be adapted to the different stages of HIV infection or to patient characteristics [1]. To study how patient features influence utilization of out patient services, we retrospectively analyzed the electronic health record of HIV-positive patients who had followed day-care programs at the AIDS Center of the University of Palermo, Italy. MATERIALS AND METHODS: 223 HIV-infected subjects were recruited and divided into two groups according to CD4 cell counts (117 with a CD4 count ≤500/mm(3) and 106 with CD4 count ≥500/mm(3)). Data on age, gender, race, lifestyle habits (including educational level, drug abuse history, smoking status, alcohol consumption, sexual behaviour) BMI, HIV-RNA, CD4+ T-cell count, antiretroviral therapy (ART), comorbidities such as HCV co-infection, osteoporosis biomarker, dyslipidemia, diabetes, renal function and systolic and diastolic blood pressure were recorded in a purposely designed database and were analyzed in relation to AIN by uni- and multivariable logistic regression. RESULTS: Table 1 shows the characteristics of enrolled patients; the average age of the recruited patients was 45.4±9.5 years. 163 individuals were male (73%), 26 were immigrants (12%) and 91 (40%) were treatment-naïve. Mean day care access for laboratory tests to evaluate stage of HIV and for treatment monitoring was 6.5 days for CD4 cell count measurements and 9.6 for HIV RNA/drug-resistance testing. When patients were stratified according to CD4 count, mean day care access for laboratory tests to evaluate HIV stage and to monitor treatment was negatively correlated with CD4 cell counts. CONCLUSIONS: Only patients with CD4 counts ≤500/mm(3) showed higher rates of healthcare utilization; these data may be useful for monitoring and revising implementation plans for the different phases of HIV disease.
