The significance of extreme hyperferritinemia and its association with certain diagnoses and prognoses are not well characterized. We performed a retrospective analysis of adult patients with at least one total serum ferritin (TSF) measurement ≥ 5000 µg/L over 2 years, in three university hospitals. Conditions associated with hyperferritinemia were collected, and patients were classified into 10 etiological groups. Intensive care unit (ICU) transfer and mortality rates were recorded. A total of 495 patients were identified, of which 56% had a TSF level between 5000 and 10,000 µg/L. There were multiple underlying causes in 81% of the patients. The most common causes were infections (38%), hemophagocytic lymphohistiocytosis (HLH, 18%), and acute hepatitis (14%). For TSF levels > 10,000 µg/L, there were no solid cancer or hematological malignancy without another cause of hyperferritinemia. Isolated iron-overload syndromes never exceeded TSF levels > 15,000 µg/L. Extreme hyperferritinemia (TSF levels > 25,000 µg/L) was associated with only four causes: HLH, infections, acute hepatitis and cytokine release syndromes. A total of 32% of patients were transferred to an ICU, and 28% died. Both ICU transfer rate and mortality were statistically associated with ferritin levels. An optimized threshold of 13,405 μg/L was the best predictor for the diagnosis of HLH, with a sensitivity of 76.4% and a specificity of 79.3%. Hyperferritinemia reflects a variety of conditions, but only four causes are associated with extreme hyperferritinemia, in which HLH and acute hepatitis are the most common. Extreme hyperferritinemia has a poor prognosis with increased mortality.

Hemophagocytic lymphohistiocytosis is a hyperinflammatory syndrome characterized by uncontrolled activation of immune cells and mediators. Two diagnostic tools are widely used in clinical practice: the HLH-2004 criteria and the Hscore. Despite their good diagnostic performance, these scores were constructed after a selection of variables based on expert consensus. We propose here a machine learning approach to build a classification model for HLH in a cohort of patients selected by glycosylated ferritin dosage in our tertiary center in Lyon, France. On a dataset of 207 adult patients with 26 variables, our model showed good overall diagnostic performances with a sensitivity of 71.4% and high specificity, and positive and negative predictive values which were 100%, 100%, and 96.9%, respectively. Although generalization is difficult on a selected population, this is the first study to date to provide a machine-learning model for HLH detection. Further studies will be required to improve the machine learning model performances with a large number of HLH cases and with appropriate controls.

Background and aim: Granulomatous hepatitis (GH) is associated with various aetiologies, especially inflammatory and infectious disorders. Sarcoidosis is a granulomatous disease in which the liver is the fourth most affected organ. Since epithelioid cell granulomas are not specific to sarcoidosis and since most patients with hepatic sarcoidosis are asymptomatic, valuable diagnostic biomarkers are needed to support the diagnosis of sarcoidosis. This study proposes to assess the diagnostic value of serum angiotensin converting enzyme (sACE) and lymphopenia in GH for sarcoidosis. Method: We retrospectively analyzed the records of 90 patients referred to the internal medicine or hepatogastroenterology departments of the Lyon University Hospital (Lyon, France) between March 2002 and January 2020 in a context of GH. Results: In our tertiary center, 38 patients with sarcoidosis were identified among 73 patients with GH. Lymphopenia had a high specificity (88.9%), which increased when combined with elevated sACE (90.9%). Interestingly, specificity increased in patients under 50 years old (100%). Conclusions: Those results suggests that lymphopenia and sACE may be valuable biomarkers for sarcoidosis diagnosis in GH when combined, especially in younger patients.