Nonattendance in pediatric pulmonary clinics: an ambulatory survey

<p>Abstract</p> <p>Background</p> <p>Nonattendance for scheduled appointments disturbs the effective management of pediatric pulmonary clinics. We hypothesized that the reasons for non-attendance and the necessary solutions might be different in pediatric pulmonary medicine than in other pediatric fields. We therefore investigated the factors associated with nonattendance this field in order to devise a corrective strategy.</p> <p>Methods</p> <p>The effect of age, gender, ethnic origin, waiting time for an appointment and the timing of appointments during the day on nonattendance proportion were assessed. Chi-square tests were used to analyze statistically significant differences of categorical variables. Logistic regression models were used for multivariate analysis.</p> <p>Results</p> <p>A total of 1190 pediatric pulmonology clinic visits in a 21 month period were included in the study. The overall proportion of nonattendance was 30.6%. Nonattendance was 23.8% when there was a short waiting time for an appointment (1–7 days) and 36.3% when there was a long waiting time (8 days and above) (p-value < 0.001). Nonattendance was 28.7% between 8 a.m. to 3 p.m. and 37.5% after 3 p.m. (p = 0.007). Jewish rural patients had 15.4% nonattendance, Jewish urban patients had 31.2% nonattendance and Bedouin patients had 32.9% nonattendance (p < 0.004). Age and gender were not significantly associated with nonattendance proportions. A multivariate logistic regression model demonstrated that the waiting time for an appointment, time of the day, and the patients' origin was significantly associated with nonattendance.</p> <p>Conclusion</p> <p>The factors associated with nonattendance in pediatric pulmonary clinics include the length of waiting time for an appointment, the hour of the appointment within the day and the origin of the patient.</p

Broadening of Neutralization Activity to Directly Block a Dominant Antibody-Driven SARS-Coronavirus Evolution Pathway

Phylogenetic analyses have provided strong evidence that amino acid changes in spike (S) protein of animal and human SARS coronaviruses (SARS-CoVs) during and between two zoonotic transfers (2002/03 and 2003/04) are the result of positive selection. While several studies support that some amino acid changes between animal and human viruses are the result of inter-species adaptation, the role of neutralizing antibodies (nAbs) in driving SARS-CoV evolution, particularly during intra-species transmission, is unknown. A detailed examination of SARS-CoV infected animal and human convalescent sera could provide evidence of nAb pressure which, if found, may lead to strategies to effectively block virus evolution pathways by broadening the activity of nAbs. Here we show, by focusing on a dominant neutralization epitope, that contemporaneous- and cross-strain nAb responses against SARS-CoV spike protein exist during natural infection. In vitro immune pressure on this epitope using 2002/03 strain-specific nAb 80R recapitulated a dominant escape mutation that was present in all 2003/04 animal and human viruses. Strategies to block this nAb escape/naturally occurring evolution pathway by generating broad nAbs (BnAbs) with activity against 80R escape mutants and both 2002/03 and 2003/04 strains were explored. Structure-based amino acid changes in an activation-induced cytidine deaminase (AID) “hot spot” in a light chain CDR (complementarity determining region) alone, introduced through shuffling of naturally occurring non-immune human VL chain repertoire or by targeted mutagenesis, were successful in generating these BnAbs. These results demonstrate that nAb-mediated immune pressure is likely a driving force for positive selection during intra-species transmission of SARS-CoV. Somatic hypermutation (SHM) of a single VL CDR can markedly broaden the activity of a strain-specific nAb. The strategies investigated in this study, in particular the use of structural information in combination of chain-shuffling as well as hot-spot CDR mutagenesis, can be exploited to broaden neutralization activity, to improve anti-viral nAb therapies, and directly manipulate virus evolution

Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements

Background: Recent assays for individual-specific genome-wide DNA methylation profiles have enabled epigenome-wide association studies to identify specific CpG sites associated with a phenotype. Computational prediction of CpG site-specific methylation levels is important, but current approaches tackle average methylation within a genomic locus and are often limited to specific genomic regions. Results: We characterize genome-wide DNA methylation patterns, and show that correlation among CpG sites decays rapidly, making predictions solely based on neighboring sites challenging. We built a random forest classifier to predict CpG site methylation levels using as features neighboring CpG site methylation levels and genomic distance, and co-localization with coding regions, CGIs, and regulatory elements from the ENCODE project, among others. Our approach achieves 91% -- 94% prediction accuracy of genome-wide methylation levels at single CpG site precision. The accuracy increases to 98% when restricted to CpG sites within CGIs. Our classifier outperforms state-of-the-art methylation classifiers and identifies features that contribute to prediction accuracy: neighboring CpG site methylation status, CpG island status, co-localized DNase I hypersensitive sites, and specific transcription factor binding sites were found to be most predictive of methylation levels. Conclusions: Our observations of DNA methylation patterns led us to develop a classifier to predict site-specific methylation levels that achieves the best DNA methylation predictive accuracy to date. Furthermore, our method identified genomic features that interact with DNA methylation, elucidating mechanisms involved in DNA methylation modification and regulation, and linking different epigenetic processes

The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease