"Inhibitory immune checkpoints predict 7-day, in-hospital and 1-year mortality of internal medicine patients admitted with bacterial sepsis".

BACKGROUND: Sepsis is a life-threatening syndrome with complex pathophysiology and great clinical heterogeneity which complicates the delivery of personalized therapies. Our goals were to demonstrate that some biomarkers identified as regulatory immune checkpoints in preclinical studies could 1)improve sepsis prognostication based on clinical variables and 2)guide the stratification of septic patients in subgroups with shared characteristics of immune response or survival outcomes. METHODS: We assayed the soluble counterparts of 12 biomarkers of immune response in 113 internal medicine patients with bacterial sepsis. RESULTS: IL-1 receptor-associated kinase M (IRAK-M) exhibited the highest hazard ratios (HRs) for increased 7-day (1.94 [1.17-3.20]) and 30-day mortality (1.61 [1.14-2.28]). HRs of IRAK-M and Galectin-1 for predicting 1-year mortality were 1.52 (1.20-1.92) and 1.64 (1.13-2.36), respectively. A prognostic model including IRAK-M, Galectin-1, and clinical variables (Charlson Comorbidty Index, multiple source of sepsis, and SOFA score) had high discrimination for death at 7 days and 30 days (area under the curve 0.90 [0.82-0.99]) and 0.86 [0.79-0.94], respectively). Patients with elevated serum levels of IRAK-M and Galectin-1 had clinical traits of immune suppression and low survival rates. None of the 12 biomarkers were independent predictors of 2-year mortality. CONCLUSIONS: Two inhibitory immune checkpoint biomarkers (IRAK-M and Galectin-1) helped identify 3 distinct sepsis phenotypes with distinct prognoses. These biomarkers shed light on the interplay between immune dysfunction and prognosis in patients with bacterial sepsis and may prove to be useful prognostic markers, therapeutic targets, and biochemical markers for targeted enrollment in targeted therapeutic trials.

Derivation and Validation of a Biomarker-Based Clinical Algorithm to Rule Out Sepsis From Noninfectious Systemic Inflammatory Response Syndrome at Emergency Department Admission: A Multicenter Prospective Study.

OBJECTIVES: To derive and validate a predictive algorithm integrating a nomogram-based prediction of the pretest probability of infection with a panel of serum biomarkers, which could robustly differentiate sepsis/septic shock from noninfectious systemic inflammatory response syndrome. DESIGN: Multicenter prospective study. SETTING: At emergency department admission in five University hospitals. PATIENTS: Nine-hundred forty-seven adults in inception cohort and 185 adults in validation cohort. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A nomogram, including age, Sequential Organ Failure Assessment score, recent antimicrobial therapy, hyperthermia, leukocytosis, and high C-reactive protein values, was built in order to take data from 716 infected patients and 120 patients with noninfectious systemic inflammatory response syndrome to predict pretest probability of infection. Then, the best combination of procalcitonin, soluble phospholipase A2 group IIA, presepsin, soluble interleukin-2 receptor α, and soluble triggering receptor expressed on myeloid cell-1 was applied in order to categorize patients as "likely" or "unlikely" to be infected. The predictive algorithm required only procalcitonin backed up with soluble phospholipase A2 group IIA determined in 29% of the patients to rule out sepsis/septic shock with a negative predictive value of 93%. In a validation cohort of 158 patients, predictive algorithm reached 100% of negative predictive value requiring biomarker measurements in 18% of the population. CONCLUSIONS: We have developed and validated a high-performing, reproducible, and parsimonious algorithm to assist emergency department physicians in distinguishing sepsis/septic shock from noninfectious systemic inflammatory response syndrome.

Lung ultrasound may support internal medicine physicians in predicting the diagnosis, bacterial etiology and favorable outcome of community-acquired pneumonia.

To assess the usefulness of lung ultrasound (LUS) for identifying community-acquired pneumonia (CAP) among adult patients with suspected lower respiratory tract infection (LRTI) and for discriminating between CAP with different cultural statuses, etiologies, and outcomes. LUS was performed at internal medicine ward admission. The performance of chest X-ray (CXR) and LUS in diagnosing CAP in 410 patients with suspected LRTI was determined. All possible positive results for pneumonia on LUS were condensed into pattern 1 (consolidation + / - alveolar-interstitial syndrome) and pattern 2 (alveolar-interstitial syndrome). The performance of LUS in predicting culture-positive status, bacterial etiology, and adverse outcomes of CAP was assessed in 315 patients. The area under the receiver operating characteristic curve for diagnosing CAP by LUS was significantly higher than for diagnosis CAP by CXR (0.93 and 0.71, respectively; p < 0.001). Pattern 1 predicted CAP with bacterial and mixed bacterial and viral etiologies with positive predictive values of 99% (95% CI, 94-100%) and 97% (95% CI, 81-99%), respectively. Pattern 2 ruled out mortality with a negative predictive value of 95% (95% CI, 86-98%), respectively. In this study, LUS was useful in predicting a diagnosis of CAP, the bacterial etiology of CAP, and favorable outcome in patients with CAP.

Ruling Out Coronavirus Disease 2019 in Patients with Pneumonia: The Role of Blood Cell Count and Lung Ultrasound.

Coronavirus disease 2019 (COVID-19) is characterized by a distinctive blood leucocyte pattern and B-lines on lung ultrasound (LUS) as marker of alveolar-interstitial syndrome. We aimed to evaluate the accuracy of blood leucocyte count alone or in combination with LUS for COVID-19 diagnosis. We retrospectively enrolled consecutive patients diagnosed with community acquired pneumonia (CAP) at hospital admission to derive and validate cutoff values for blood cell count that could be predictive of COVID-19 before confirmation by the nucleic acid amplification test (NAAT). Cutoff values, generated and confirmed in inception (41/115, positive/negative patients) and validation (100/180, positive/negative patients) cohorts, were ≤17 and ≤10 cells/mm3 for basophils and eosinophils, respectively. Basophils and/or eosinophils below cutoff were associated with sensitivity of 98% (95%CI, 94-100) and negative likelihood ratio of 0.04 (95%CI, 0.01-0.11). In a subgroup of 265 subjects, the sensitivity of B-line on LUS was 15% lower (p < 0.001) than that of basophils and/or eosinophils below cutoff. The combination of B-lines with basophils and eosinophils below cutoff was associated with a moderate increase of the positive likelihood ratio: 5.0 (95%CI, 3.2-7.7). In conclusion, basophil and eosinophil counts above the generated cutoff virtually rule out COVID-19 in patients with CAP. Our findings can help optimize patient triage pending the NAAT results.

The Integration of qSOFA with Clinical Variables and Serum Biomarkers Improves the Prognostic Value of qSOFA Alone in Patients with Suspected or Confirmed Sepsis at ED Admission.

BACKGROUND: The prognostic value of quick sepsis-related organ failure assessment (qSOFA) outside intensive care units has been criticized. Therefore, we aimed to improve its ability in predicting 30-day all-cause mortality, and in ruling out the cases at high risk of death among patients with suspected or confirmed sepsis at emergency department (ED) admission. METHODS: This study is a secondary analysis of a prospective multicenter study. We built three predictive models combining qSOFA with the clinical variables and serum biomarkers that resulted in an independent association with 30-day mortality, in both 848 undifferentiated patients (Group 1) and in 545 patients definitively diagnosed with sepsis (Group 2). The models reaching the highest negative predictive value (NPV) with the minimum expenditure of biomarkers in Group 1 and in Group 2 were validated in two cohorts of patients initially held out due to missing data. RESULTS: In terms of the area under the receiver-operating characteristic curve, all six models significantly exceeded qSOFA in predicting prognosis. An "extended" qSOFA (eqSOFA1) in Group 1 and an eqSOFA2 integrated with C-reactive protein and mid-regional proadrenomedullin (eqSOFA2+CRP+MR-proADM) in Group 2 reached the best NPV (0.94 and 0.93, respectively) and ease of use. eqSOFA1 and eqSOFA2+CRP+MR-proADM performed equally well in both the inception and validation cohorts. CONCLUSIONS: We have derived and validated two prognostic models that outweigh qSOFA in predicting mortality and in identifying the low risk of death among patients with suspected or confirmed sepsis at ED admission.

Septic Shock with Multi Organ Failure Due to Fluoroquinolones Resistant Campylobacter Jejuni.

BACKGROUND Campylobacter jejuni infections are typically self-limited, and severe extra-intestinal complications are uncommon. CASE REPORT We report a case of a man with septic shock due to fluoroquinolones resistant Campylobacter jejuni. CONCLUSIONS This manuscript emphasizes the potential lethality of fluorquinolones resistant Campylobacter jejuni bacteremia.

Heterogeneous models for an early discrimination between sepsis and non-infective SIRS in medical ward patients: a pilot study.

The objective of the study was to determine the accuracy of phospholipase A2 group II (PLA2-II), interferon-gamma-inducible protein 10 (IP-10), angiopoietin-2 (Ang-2), and procalcitonin (PCT) plasma levels in early ruling in/out of sepsis among systemic inflammatory response syndrome (SIRS) patients. Biomarker levels were determined in 80 SIRS patients during the first 4 h of admission to the medical ward. The final diagnosis of sepsis or non-infective SIRS was issued according to good clinical practice. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for sepsis diagnosis were assessed. The optimal biomarker combinations with clinical variables were investigated by logistic regression and decision tree (CART). PLA2-II, IP-10 and PCT, but not Ang-2, were significantly higher in septic (n = 60) than in non-infective SIRS (n = 20) patients (P ≤ 0.001, 0.027, and 0.002, respectively). PLA2-II PPV and NPV were 88 and 86%, respectively. The corresponding figures were 100 and 31% for IP-10, and 93 and 35% for PCT. Binary logistic regression model had 100% PPV and NPV, while manual and software-generated CART reached an overall accuracy of 95 and 98%, respectively, both with 100% NPV. PLA2-II and IP-10 associated with clinical variables in regression or decision tree heterogeneous models may be valuable biomarkers for sepsis diagnosis in SIRS patients admitted to medical ward (MW). Further studies are needed to introduce them into clinical practice.

Invasive filamentous fungus infection with secondary cerebral vasculitis in a patient with no obvious immune suppression.

Invasive mold infections represent an emerging and important diagnostic challenge, especially in immunocompetent patients when microscopy and cultures of the biological fluids remain negative. A central nervous system localization is not common and the clinical presentation is aspecific.

Disseminated tuberculosis in an immunocompetent patient.

Miliary tuberculosis refers to the clinical disease resulting from the hematogenous dissemination of Mycobacterium tuberculosis. A tuberculous aneurysm of the aorta is exceedingly rare. Contiguous tuberculosis in the form of lymphadenitis is generally responsible for the aortic involvement. We report a case of tuberculous mycotic aneurysm in patient with miliary disease, not affected by a cellular immunodeficiency and with no other common risk factor for infection. He received anti-tubercular therapy and endovascular stenting before the identification of Mycobacterium tuberculosis in lung, lymph nodes, and gastric lavage. The clinician should be aware that a mycotic abdominal aortic aneurysm could be caused by M. tuberculosis, even if microbiological confirmation is lacking or is negative, especially if a contiguous focus of tubercular infection is detected.