New clinical prediction model for early recognition of sepsis in adult primary care patients:a prospective diagnostic cohort study of development and external validation

Background Recognising patients who need immediate hospital treatment for sepsis while simultaneously limiting unnecessary referrals is challenging for GPs.Aim To develop and validate a sepsis prediction model for adult patients in primary care.Design and setting This was a prospective cohort study in four out-of-hours primary care services in the Netherlands, conducted between June 2018 and March 2020.Method Adult patients who were acutely ill and received home visits were included. A total of nine clinical variables were selected as candidate predictors, next to the biomarkers C-reactive protein, procalcitonin, and lactate. The primary endpoint was sepsis within 72 hours of inclusion, as established by an expert panel. Multivariable logistic regression with backwards selection was used to design an optimal model with continuous clinical variables. The added value of the biomarkers was evaluated. Subsequently, a simple model using single cut-off points of continuous variables was developed and externally validated in two emergency department populations.Results A total of 357 patients were included with a median age of 80 years (interquartile range 71–86), of which 151 (42%) were diagnosed with sepsis. A model based on a simple count of one point for each of six variables (aged >65 years; temperature >38°C; systolic blood pressure ≤110 mmHg; heart rate >110/min; saturation ≤95%; and altered mental status) had good discrimination and calibration (C-statistic of 0.80 [95% confidence interval = 0.75 to 0.84]; Brier score 0.175). Biomarkers did not improve the performance of the model and were therefore not included. The model was robust during external validation.Conclusion Based on this study’s GP out-of-hours population, a simple model can accurately predict sepsis in acutely ill adult patients using readily available clinical parameters

Risk Factors Associated with Indeterminate Gamma Interferon Responses in the Assessment of Latent Tuberculosis Infection in a High-Incidence Environment

Immunogenetics and cellular immunology of bacterial infectious disease

Cardiovascular malformations caused by NOTCH1 mutations do not keep left:data on 428 probands with left-sided CHD and their families

Purpose: We aimed to determine the prevalence and phenotypic spectrum of NOTCH1 mutations in left-sided congenital heart disease (LS-CHD). LS-CHD includes aortic valve stenosis, a bicuspid aortic valve, coarctation of the aorta, and hypoplastic left heart syndrome. Methods: NOTCH1 was screened for mutations in 428 nonsyndromic probands with LS-CHD, and family histories were obtained for all. When a mutation was detected, relatives were also tested. Results: In 148/428 patients (35%), LS-CHD was familial. Fourteen mutations (3%; 5 RNA splicing mutations, 8 truncating mutations, 1 whole-gene deletion) were detected, 11 in familial disease (11/148 (7%)) and 3 in sporadic disease (3/280 (1%)). Forty-nine additional mutation carriers were identified among the 14 families, of whom 12 (25%) were asymptomatic. Most of these mutation carriers had LS-CHD, but 9 (18%) had right-sided congenital heart disease (RS-CHD) or conotruncal heart disease (CTD). Thoracic aortic aneurysms (TAAs) occurred in 6 mutation carriers (probands included 6/63 (10%)). Conclusion: Pathogenic mutations in NOTCH1 were identified in 7% of familial LS-CHD and in 1% of sporadic LS-CHD. The penetrance is high; a cardiovascular malformation was found in 75% of NOTCH1 mutation carriers. The phenotypic spectrum includes LS-CHD, RS-CHD, CTD, and TAA. Testing NOTCH1 for an early diagnosis in LS-CHD/RS-CHD/CTD/TAA is warranted