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Abstract Background Sepsis is a leading cause of death and serious illness that requires early recognition and therapeutic management to improve survival. The quick-SOFA score helps in its recognition, but its diagnostic performance is insufficient. To develop a score that can rapidly identify a community acquired septic situation at risk of clinical complications in patients consulting the emergency department (ED). Methods We conducted a monocentric, prospective cohort study in the emergency department of a university hospital between March 2016 and August 2018 (NCT03280992). All patients admitted to the emergency department for a suspicion of a community-acquired infection were included. Predictor variables of progression to septic shock or death within the first 90 days were selected using backward stepwise multivariable logistic regression to develop a clinical score. Receiver operating characteristic (ROC) curves were constructed to determine the discriminating power of the area under the curve (AUC). We also determined the threshold of our score that optimized the performance required for a sepsis-worsening score. We have compared our score with the NEWS-2 and qSOFA scores. Results Among the 21,826 patients admitted to the ED, 796 patients were suspected of having community-acquired infection and 461 met the sepsis criteria; therefore, these patients were included in the analysis. The median [interquartile range] age was 72 [54–84] years, 248 (54%) were males, and 244 (53%) had respiratory symptoms. The clinical score ranged from 0 to 90 and included 8 variables with an area under the ROC curve of 0.85 (confidence interval [CI] 95% 0.81–0.89). A cut-off of 26 yields a sensitivity of 88% (CI 95% 0.79–0.93), a specificity of 62% (CI 95% 57–67), and a negative predictive value of 95% (CI 95% 91–97). The area under the ROC curve for our score was 0.85 (95% CI, 0.81–0.89) versus 0.73 (95% CI, 0.68–0.78) for qSOFA and 0.66 (95% CI, 0.60–0.72) for NEWS-2. Conclusions Our study provides an accurate clinical score for identifying septic patients consulting the ED early at risk of worsening disease. This score could be implemented at admission.

Background: Thermography can be used in pre-operative planning of free perforator flap surgeries. Thermography assesses skin temperature by measuring the quantity of infrared radiation observed. In this meta-analysis, authors assess the sensitivity of smartphone-based thermal imaging (SBTI) in the detection of perforators and analyze the difference between static and dynamic imaging. Materials and methods: Authors followed the PRISMA guidelines for systematic reviews and meta-analyses. The meta package in R was used to conduct the meta-analysis. The “metaprop” function was used to calculate the overall sensitivity estimate and 95% confidence interval. The “metaprop.one” function was used to calculate subgroup estimates for static and dynamic study types. The “metareg” function was used to conduct meta-regression analyses to explore sources of heterogeneity. Results: This study includes seven articles with 1429 perforators being evaluated. The overall proportion of the sensitivities was estimated to be 0.8754 (95% CI: 0.7542; 0.9414) using a random effects model. The heterogeneity of the studies was high, as indicated by the tau^2 value of 1.2500 (95% CI: 0.4497; 8.4060) and the I^2 value of 92.6% (95% CI: 88.1%; 95.4%). The pooled sensitivity for static imaging was 0.8636 (95%CI: 0.6238–0.9603) with a tau^2 of 2.0661 and a tau of 1.4374, while the pooled sensitivity for dynamic imaging was slightly higher (p = 0.7016) at 0.8993 (95%CI: 0.7412–0.9653) with a smaller tau^2 of 0.8403 and a tau of 0.9167. Conclusion: Further studies need to confirm that SBTI is a reliable and convenient technique for detecting perforators for the pre-operative planning of free perforator flap surgeries.