ABSTRACT
Background: The coronavirus disease 2019 (COVID-19) pandemic has found the whole world unprepared for its correct management. Italy was the first European country to experience the spread of the SARS-CoV-2 virus at the end of February 2020. As a result of hospital overcrowding, the quality of care delivered was not always optimal. A substantial number of patients admitted to non-ICU units could have been treated at home. It would have been extremely useful to have a score that, based on personal and clinical characteristics and simple blood tests, could have predicted with sufficient reliability the probability that a patient had or did not have a disease that could have led to their death. This study aims to develop a scoring system to identify which patients with COVID-19 are at high mortality risk upon hospital admission, to expedite and enhance clinical decision making. Methods: A retrospective analysis was performed to develop a multivariable prognostic prediction model. Results: Derivation and external validation cohorts were obtained from two Italian University Hospital databases, including 388 (10.31% deceased) and 1357 (7.68% deceased) patients with confirmed COVID-19, respectively. A multivariable logistic model was used to select seven variables associated with in-hospital death (age, baseline oxygen saturation, hemoglobin value, white blood cell count, percentage of neutrophils, platelet count, and creatinine value). Calibration and discrimination were satisfactory with a cumulative AUC for prediction mortality of 0.924 (95% CI: 0.893-0.944) in derivation cohorts and 0.808 (95% CI: 0.886-0.828) in external validation cohorts. The risk score obtained was compared with the ISARIC 4C Mortality Score, and with all the other most important scores considered so far, to evaluate the risk of death of patients with COVID-19. It performed better than all the above scores to evaluate the predictability of dying. Its sensitivity, specificity, and AUC were higher than the other COVID-19 scoring systems when the latter were calculated for the 388 patients in our derivation cohort. Conclusions: In conclusion, the CZ-COVID-19 Score may help all physicians by identifying those COVID-19 patients who require more attention to provide better therapeutic regimens or, on the contrary, by identifying those patients for whom hospitalization is not necessary and who could therefore be sent home without overcrowding healthcare facilities. We developed and validated a new risk score based on seven variables for upon-hospital admission of COVID-19 patients. It is very simple to calculate and performs better than all the other similar scores to evaluate the predictability of dying.
ABSTRACT
BACKGROUND: Despite the rising number of people living with human immunodeficiency virus (HIV), there is a lack of knowledge about the factors that lead to PLWHs being hospitalized in worldwide literature. Our study aimed to investigate PLWH admissions in Sicily (Italy) between January 2010 and September 2021 and to analyze the characteristics and risk factors for in-hospital mortality and differences between Italians and foreigners. METHODS: Data from the hospital discharge forms of all people living with HIV (PLWH) hospitalized in Sicilian hospitals were retrospectively collected. Age, sex, nationality, length of stay, acquired immunodeficiency syndrome (AIDS), and non-AIDS-related diseases were evaluated using univariate analysis according to in-hospital mortality rates. The factors associated with mortality were included in the logistic regression model. RESULTS: In total, 5281 admissions from 2726 PLWHs occurred, most of which were related to non-AIDS diseases. Approximately 20 % regarded foreign patients, mainly from Africa. Logistic regression analysis revealed an association between in-hospital mortality and some AIDS- and non-AIDS-related diseases (wasting syndrome, lymphomas, Kaposi sarcomas, progressive multifocal leukoencephalopathy, cryptococcosis, abscesses, sepsis, cardiovascular disease, nephropathy, and respiratory diseases). African patient admissions were significantly associated with tuberculosis, toxoplasmosis, Burkitt lymphoma, and hepatitis B diagnoses. CONCLUSIONS: Our study showed that most hospitalizations were related to non-AIDS-defining diseases, with differences between Italian and foreign patients, mainly from Africa.
ABSTRACT
Clostridioides difficile infection (CDI) is a significant cause of morbidity and mortality, mostly in frail patients. Notification is not mandatory in Italy, and data on incidence, risk of death, and recurrence are lacking. The purpose of this study was to determine CDI incidence and risk factors for mortality and recurrence. The "ICD-9 00845" code in hospital-standardized discharged forms (H-SDF) and microbiology datasets were used to retrieve CDI cases at Policlinico Hospital, Palermo between 2013 and 2022. Incidence, ward distribution, recurrence rate, mortality, and coding rate were considered. The risk of death and recurrence was predicted through multivariable analysis. There were 275 CDIs, 75% hospital-acquired, the median time between admission and diagnosis was 13 days, and the median stay was 21 days. Incidence increased from 0.3 to 5.6% (an 18.7-fold increase) throughout the decade. Only 48.1% of cases were coded in H-SDF. The rate of severe/severe-complicated cases increased 1.9 times. Fidaxomicin was used in 17.1% and 24.7% of cases overall and since 2019. Overall and attributable mortalities were 11.3% and 4.7%, respectively. Median time between diagnosis and death was 11 days, and recurrence rate was 4%. Bezlotoxumab was administered in 64% of recurrences. Multivariable analysis revealed that only hemodialysis was associated with mortality. No statistically significant association in predicting recurrence risk emerged. We advocate for CDI notification to become mandatory and recommend coding CDI diagnosis in H-SDF to aid in infection rate monitoring. Maximum attention should be paid to preventing people on hemodialysis from getting CDI.
