The streptococcal toxic shock syndrome is a severe complication associated with invasive infections by group A streptococci. In spite of medical progresses in the care of patients with septic shock during the last decades, this condition has remained associated with a high mortality. Early recognition and multidisciplinary management are key to the care of patients with streptococcal toxic shock syndrome, with intensive and appropriate intensive support of failing organs, rapid diagnosis of infectious source(s), and surgical management. The epidemiology and risk factors for streptococcal toxic shock syndrome remain to be better studied, including the possible causal role of exposure to nonsteroidal anti-inflammatory drugs. In this review article, the authors review the current knowledge of streptococcal toxic shock syndrome and discuss the pathophysiology as well as its supportive and specific treatment.

Diagnosing pneumonia in emergency departments is challenging because the accuracy of symptoms, signs and laboratory tests is limited. As a confirmation test, chest X-ray has significant limitations and is outperformed by CT-scan. However, obtaining a CT-scan in all cases of suspected pneumonia has significant drawbacks. We used a cohort of 200 consecutive elderly patients admitted to the hospital for suspected pneumonia to build a simple prediction score, which was used to determine indication for performing a CT-scan. The reference diagnosis was adjudicated by experts considering all available data, including evolution until discharge and CT scan in all patients. Results were externally validated in a second cohort of 319 patients. Pneumonia was confirmed in 133 patients (67%). Area under the receiver operator curve (AUROC) of physician evaluation was 0.55 (0.46–0.64). The score incorporated four variables independently predicting confirmed pneumonia: male gender, acute cough, C-reactive protein >70 mg/L, and urea <7 mmol/L. AUROC of the score was 0.68 (95% confidence interval (CI) 0.60–0.76). When a CT-scan was obtained for patients at low or intermediate predicted risk (108 patients, 54% of the cohort), AUROC was 0.71 (0.63–0.80) and 0.69 (0.64–0.74) in the derivation and validation cohort, respectively. A simple prediction score for pneumonia had moderate accuracy and could guide the performance of a CT-scan.

Background: Age alone is not a robust predictor of mortality in critically ill elderly patients. Chronic health status and functional status before admission could be better predictors. This study aimed to determine whether functional status, assessed using the Functional Independence Measure (FIM), could be an independent predictor of mortality in a geriatric population admitted to an intermediate care unit (IMCU). Methods: A monocentric, retrospective, observational study of all patients aged ≥75 years old admitted to Geneva University Hospitals’ geriatric IMCU between 01.01.2012 and 31.05.2016. The study’s primary outcome metrics were one-year mortality’s associations with a pre-admission FIM score and other relevant prospectively recorded prognostic variables. Results: A total of 345 patients were included (56% female, mean age 85 +/− 6.5 years). Mean FIM score was 66 +/− 26. One-year mortality was 57%. Dichotomized low (≤ 63) and high FIM (> 63) scores were associated with one-year mortalities of 68 and 44%, respectively. Logistic regression calculations found an association between pre-admission FIM score and one-year mortality (p < 0.0001), including variables usually associated with mortality (e.g., age, sex, comorbidities, mini-mental health state score, renal function). Multivariate survival analysis showed a significant difference between groups, with a hazard ratio of 0.29 (95% CI: 0.13–0.65) for patients with high FIM scores. Conclusions: In the present study, higher functional status, assessed using the FIM tool before admission to an IMCU, was significantly and independently associated with lower one-year mortality. This opens up perspectives on the potential value of FIM for establishing a finer prognosis and better triage of critically ill older patients.

The diagnosis of pneumonia based on semiology and chest X-rays is frequently inaccurate, particularly in elderly patients. Older (C-reactive protein (CRP); procalcitonin (PCT)) or newer (Serum amyloid A (SAA); neopterin (NP)) biomarkers may increase the accuracy of pneumonia diagnosis, but data are scarce and conflicting. We assessed the accuracy of CRP, PCT, SAA, NP and the ratios CRP/NP and SAA/NP in a prospective observational cohort of elderly patients with suspected pneumonia. We included consecutive patients more than 65 years old, with at least one respiratory symptom and one symptom or laboratory finding suggestive of infection, and a working diagnosis of pneumonia. Low-dose CT scan and comprehensive microbiological testing were done in all patients. The index tests, CRP, PCT, SAA and NP, were obtained within 24 hours. The reference diagnosis was assessed a posteriori by a panel of experts considering all available data, including patients’ outcome. We used area under the curve (AUROC) and Youden index to assess the accuracy and obtain optimal cut-off of the index tests. 200 patients (median age 84 years) were included; 133 (67%) had pneumonia. AUROCs for the diagnosis of pneumonia was 0.64 (95% CI: 0.56–0.72) for CRP; 0.59 (95% CI: 0.51–0.68) for PCT; 0.60 (95% CI: 0.52–0.69) for SAA; 0.41 (95% CI: 0.32–0.49) for NP; 0.63 (95% CI: 0.55–0.71) for CRP/NP; and 0.61 (95% CI: 0.53–0.70) for SAA/NP. No cut-off resulted in satisfactory sensitivity or specificity. Accuracy of traditional (CRP, PCT) and newly proposed biomarkers (SAA, NP) and ratios of CRP/NP and SAA/NP was too low to help diagnosing pneumonia in the elderly. CRP had the highest AUROC. NCT 02467092

Background: Pneumonia has an impact on long-term mortality in elderly patients. The risk factors associated with poor long-term outcomes are understated. We aimed to assess the ability of scores that evaluate patients’ comorbidities (cumulative illness rating scale—geriatric, CIRS-G), malnutrition (mini nutritional assessment, MNA) and functionality (functional independence measure, FIM) to predict 1-year mortality in a cohort of older patients having a suspicion of pneumonia. Methods: Our prospective study included consecutive patients over 65 years old and hospitalized with a suspicion of pneumonia enrolled in a monocentric cohort from May 2015 to April 2016. Each score was analysed in univariate and multivariate models and logistic regressions were used to identify contributors to 1-year mortality. Results: 200 patients were included (51% male, mean age 83.8 ± 7.7). Their 1-year mortality rate was 30%. FIM (p < 0.01), CIRS-G (p < 0.001) and MNA (p < 0.001) were strongly associated with poorer long-term outcomes in univariate analysis. CIRS-G (p < 0.05) and MNA (p < 0.05) were significant predictors of 1-year mortality in multivariate analysis. Conclusion: Long-term prognosis of patients hospitalized for pneumonia was poor and we identified that scores assessing comorbidities and malnutrition seem to be important predictors of 1-year mortality. This should be taken into account for evaluating elderly patients’ prognosis, levels and goals of care.

Objectives Long term mortality is increased in elderly patients with pneumonia. We aimed to test if residual inflammation is predictive of one-year mortality after pneumonia. Methods Inflammation biomarkers (CRP, Interleukin (IL)-6 and -8, TNFα, Serum Amyloid A, Neopterin, Myeloperoxidase, anti-Apolipoprotein A-1, and anti-Phosphorylcholine IgM) were measured at admission and discharge in elderly patients hospitalized for pneumonia in a prospective study. Univariate and multivariate analysis were conducted using absolute level at discharge and relative and absolute differences between admission and discharge for all biomarkers, along with usual prognostic factors. Results 133 patients (median age 83 years (IQR: 78-89)) were included; one-year mortality was 26%. In univariate analysis, the relative difference of CRP levels had the higher AUC (0.70 (95% CI 0.60-0.80)). A decrease of CRP levels more than 67% between admission and discharge had 68% sensitivity and 68% specificity to predict survival. In multivariate analysis, lower BMI (HR=0.87 (CI 95% 0.79-0.96), p= 0.01), higher IL-8 (HR=1.02 (CI 95% 1.00-1.04), p=0.02) and higher CRP (1.01 [95% CI: 1.00-1.02] p=0.01) at discharge were independently associated with mortality. Conclusion Higher IL-8 and CRP levels at discharge were independently associated with one-year mortality. The relative CRP difference during hospitalization was the best individual biomarker to predict one-year mortality.