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1.
JHEP Rep ; 6(1): 100952, 2024 Jan.
Article in English | MEDLINE | ID: mdl-38192539

ABSTRACT

Background & Aims: Primary biliary cholangitis (PBC) may lead to portal hypertension (PH). Spleen stiffness measurement (SSM) by vibration-controlled transient elastography accurately predicts PH. We aimed to assess SSM role in stratifying the risk of liver decompensation in PBC. Methods: In this monocentric, prospective, cross-sectional study, we included 114 patients with PBC who underwent liver stiffness measurement (LSM) and SSM. In total, 78 and 33 patients underwent two and three sequential vibration-controlled transient elastography examinations, respectively (longitudinal study). Screening for high-risk oesophageal varices by oesophagogastroduodenoscopy was performed according to guidelines and proposed to all patients with SSM >40 kPa. Results: Among the 114 patients, 20 (17%) had LSM ≥10 kPa, whereas 17 (15%) had SSM >40 kPa. None of the patients with SSM ≤40 kPa had high-risk oesophageal varices, compared with three of 14 patients with SSM >40 kPa (21%; three refused endoscopy); any-size oesophageal varices were found in nine of 14 patients (64%). During a median follow-up of 15 months (IQR 10-31 months), five (4%) patients developed liver decompensation. The probability of liver decompensation was significantly higher among patients with both LSM ≥10 kPa and SSM >40 kPa: 41% at 24 months vs. 0% in other patient groups (i.e. LSM <10 kPa and SSM ≤40 kPa, or LSM ≥10 kPa and SSM ≤40 kPa, or LSM <10 kPa and SSM >40 kPa) (p <0.0001). Among the 78 patients undergoing longitudinal evaluation, four of nine patients (44%) with SSM increase during follow-up experienced liver decompensation, whereas none of those with stable LSM and SSM had liver decompensation. Conclusions: Both LSM and SSM predict liver decompensation in patients with PBC. SSM ≤40 kPa rules out high-risk oesophageal varices and might be used in combination with LSM to improve the prediction of PH-related complications. Impact and implications: Spleen stiffness measurement by vibration-controlled transient elastography accurately predicts portal hypertension in patients with chronic viral hepatitis. The present study is the first to demonstrate that in primary biliary cholangitis the combination of liver stiffness and spleen stiffness measurement can significantly improve risk stratification by predicting liver decompensation. Moreover, when spleen stiffness is combined with liver stiffness measurement and platelet count, it aids in identifying individuals with a low probability of having high-risk oesophageal varices, thereby allowing the avoidance of unnecessary endoscopy examinations. Further validation of our results in larger cohorts of patients with primary biliary cholangitis is needed to implement spleen stiffness measurement in clinical practice.

2.
Dis Markers ; 2021: 8863053, 2021.
Article in English | MEDLINE | ID: mdl-34055104

ABSTRACT

INTRODUCTION: The clinical course of Coronavirus Disease 2019 (COVID-19) is highly heterogenous, ranging from asymptomatic to fatal forms. The identification of clinical and laboratory predictors of poor prognosis may assist clinicians in monitoring strategies and therapeutic decisions. MATERIALS AND METHODS: In this study, we retrospectively assessed the prognostic value of a simple tool, the complete blood count, on a cohort of 664 patients (F 260; 39%, median age 70 (56-81) years) hospitalized for COVID-19 in Northern Italy. We collected demographic data along with complete blood cell count; moreover, the outcome of the hospital in-stay was recorded. RESULTS: At data cut-off, 221/664 patients (33.3%) had died and 453/664 (66.7%) had been discharged. Red cell distribution width (RDW) (χ 2 10.4; p < 0.001), neutrophil-to-lymphocyte (NL) ratio (χ 2 7.6; p = 0.006), and platelet count (χ 2 5.39; p = 0.02), along with age (χ 2 87.6; p < 0.001) and gender (χ 2 17.3; p < 0.001), accurately predicted in-hospital mortality. Hemoglobin levels were not associated with mortality. We also identified the best cut-off for mortality prediction: a NL ratio > 4.68 was characterized by an odds ratio for in-hospital mortality (OR) = 3.40 (2.40-4.82), while the OR for a RDW > 13.7% was 4.09 (2.87-5.83); a platelet count > 166,000/µL was, conversely, protective (OR: 0.45 (0.32-0.63)). CONCLUSION: Our findings arise the opportunity of stratifying COVID-19 severity according to simple lab parameters, which may drive clinical decisions about monitoring and treatment.


Subject(s)
Blood Cell Count , COVID-19/blood , COVID-19/mortality , Clinical Decision Rules , Hospital Mortality , Severity of Illness Index , Adult , Aged , Aged, 80 and over , COVID-19/diagnosis , Female , Humans , Italy/epidemiology , Male , Middle Aged , Multivariate Analysis , Prognosis , Retrospective Studies
3.
Sci Rep ; 10(1): 20731, 2020 11 26.
Article in English | MEDLINE | ID: mdl-33244144

ABSTRACT

Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk.


Subject(s)
COVID-19/epidemiology , COVID-19/mortality , Pandemics , SARS-CoV-2/genetics , Age Factors , Aged , Aged, 80 and over , COVID-19/virology , Comorbidity , Female , Humans , Italy/epidemiology , Length of Stay , Male , Middle Aged , Retrospective Studies , Reverse Transcriptase Polymerase Chain Reaction , Risk Factors , Sex Factors , Smoking , Survival Rate
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