Trends in Simple and Complex Appendicitis in Children and the Potential Correlation to Common Viral Pathogens-A Retrospective Cohort Study between 2010 and 2019 in The Netherlands.

The aim of this study was to evaluate the annual, seasonal and monthly trends in children with simple and complex appendicitis and their correlation to common viral pathogens in the Netherlands. A consecutive multicenter retrospective cohort study was performed between 2010 and 2019 including children (<18 years) surgically treated for appendicitis. The primary outcome was the distribution of children with simple and complex appendicitis per year, season and month. Relevant seasonal variation was defined as ≥5%. The secondary outcome was a positive correlation of the number of patients with simple and complex appendicitis to common viral pathogens (data anonymously provided by the Dutch Working Group on Clinical Virology from the Dutch Society for Clinical Microbiology (NVMM)). In total, 896 patients were included: N = 524 (58%) patients with simple and N = 372 (42%) with complex appendicitis. Of the children aged 0-5 years, 81% had complex appendicitis, versus 38% in 6-18 years (p < 0.001). An overall decline was demonstrated for both simple and complex appendicitis between 2010 and 2019. No seasonal variation was found for simple appendicitis. For complex appendicitis, the highest number of patients was found in spring, and lowest in summer (N = 372, spring 28.2 ± 5.1% versus summer 21.0 ± 5.8%, p = 0.011), but the variance was regarded as not relevant (<5% from baseline). A positive correlation was found between complex appendicitis with Adenovirus 40.41 (R = 0.356, 95%CI 0.045-0.604, p = 0.026) and simple appendicitis with Adenovirus NON 40.41 (R = 0.332, 95%CI 0.019-0.586, p = 0.039), but these correlations did not remain significant after a Bonferroni correction (p < 0.003). In conclusion, we found no relevant seasonal variation for simple or complex appendicitis, nor positive correlation with common viral pathogens.

Thrombocytopenia is associated with a dysregulated host response in severe COVID-19.

BACKGROUND: Thrombocytopenia is associated with increased mortality in COVID-19 patients. OBJECTIVE: To determine the association between thrombocytopenia and alterations in host response pathways implicated in disease pathogenesis in patients with severe COVID-19. PATIENTS/METHODS: We studied COVID-19 patients admitted to a general hospital ward included in a national (CovidPredict) cohort derived from 13 hospitals in the Netherlands. In a subgroup, 43 host response biomarkers providing insight in aberrations in distinct pathophysiological domains (coagulation and endothelial cell function; inflammation and damage; cytokines and chemokines) were determined in plasma obtained at a single time point within 48 h after admission. Patients were stratified in those with normal platelet counts (150-400 × 109/L) and those with thrombocytopenia (<150 × 109/L). RESULTS: 6.864 patients were enrolled in the national cohort, of whom 1.348 had thrombocytopenia and 5.516 had normal platelets counts; the biomarker cohort consisted of 429 patients, of whom 85 with thrombocytopenia and 344 with normal platelet counts. Plasma D-dimer levels were not different in thrombocytopenia, although patients with moderate-severe thrombocytopenia (<100 × 109/L) showed higher D-dimer levels, indicating enhanced coagulation activation. Patients with thrombocytopenia had lower plasma levels of many proinflammatory cytokines and chemokines, and antiviral mediators, suggesting involvement of platelets in inflammation and antiviral immunity. Thrombocytopenia was associated with alterations in endothelial cell biomarkers indicative of enhanced activation and a relatively preserved glycocalyx integrity. CONCLUSION: Thrombocytopenia in hospitalized patients with severe COVID-19 is associated with broad host response changes across several pathophysiological domains. These results suggest a role of platelets in the immune response during severe COVID-19.

Predictive scoring systems to differentiate between simple and complex appendicitis in children (PRE-APP study).

BACKGROUND: Several clinical prediction rules have been developed for preoperative differentiation between simple and complex appendicitis in children, as potential treatment strategies differ. This study aimed to externally validate applicable clinical prediction rules that could be used to differentiate between simple and complex appendicitis in children. METHODS: Potential clinical prediction rules were identified by a scoping review of the literature. Clinical prediction rules applicable in our daily practice were subsequently externally validated in a multicenter historical cohort consisting of 1 tertiary center and 1 large teaching hospital. All children (<18 years old) with histopathologically confirmed acute appendicitis between 2013 and 2020 were included. Test results of clinical prediction rules were compared to the gold standard of either simple or complex appendicitis consisting of predefined perioperative and histopathological criteria. Areas under the receiver operating characteristic curves were determined for the selected clinical prediction rules. Areas under the receiver operating characteristic curve >0.7 were considered acceptable and potentially useful. RESULTS: In total, 31 clinical prediction rules were identified, of which 12 could be evaluated in our cohort consisting of 550 children. The main reason to exclude clinical prediction rules was the use of variables that were not routinely measured in our cohort. In our cohort, 208/550 (38%) were diagnosed with complex appendicitis according to the gold standard. Clinical prediction rules with areas under the receiver operating characteristic curve >0.7 were: Gorter (0.81), Bogaard (0.79), Bröker (0.79), Graham (0.77), Hansson (0.76), BADCF (0.76), and Eddama (0.75). CONCLUSION: In this study, clinical prediction rules consisting of a combination of clinical and objective variables had the highest discriminative ability. External validation showed that 7 clinical prediction rules were potentially useful. Integration of these clinical prediction rules in daily practice is proposed to guide decision making regarding treatment strategies.