Predicting Hospital Readmission for Campylobacteriosis from Electronic Health Records: A Machine Learning and Text Mining Perspective

(1) Background: This study investigates influential risk factors for predicting 30-day readmission to hospital for Campylobacter infections (CI). (2) Methods: We linked general practitioner and hospital admission records of 13,006 patients with CI in Wales (1990–2015). An approach called TF-zR (term frequency-zRelevance) technique was presented to evaluates how relevant a clinical term is to a patient in a cohort characterized by coded health records. The zR is a supervised term-weighting metric to assign weight to a term based on relative frequencies of the term across different classes. Cost-sensitive classifier with swarm optimization and weighted subset learning was integrated to identify influential clinical signals as predictors and optimal model for readmission prediction. (3) Results: From a pool of up to 17,506 variables, 33 most predictive factors were identified, including age, gender, Townsend deprivation quintiles, comorbidities, medications, and procedures. The predictive model predicted readmission with 73% sensitivity and 54% specificity. Variables associated with readmission included male gender, recurrent tonsillitis, non-healing open wounds, operation for in-gown toenails. Cystitis, paracetamol/codeine use, age (21–25), and heliclear triple pack use, were associated with a lower risk of readmission. (4) Conclusions: This study gives a profile of clustered variables that are predictive of readmission associated with campylobacteriosis.

698. Contemporary Clinical Epidemiology of Pediatric Shigella and Campylobacter Infections in Houston, TX, 2019 and 2020

Background Infections due to Gram-negative, diarrheal pathogens are a significant cause of morbidity in children. Clinical features of pediatric Shigella and Campylobacter infections in urban cities in the United States are not well described. Methods We used a retrospective chart review of records (0-18 years of age) from a network of hospitals in Houston, TX. Only patients with Shigella spp. or Campylobacter spp. isolated from clinical samples in 2019 and 2020 were included. Demographic, clinical, and microbiological data were extracted from the medical record. Results We identified a total of 59 and 16 pediatric patients with Shigella spp. and Campylobacter spp. infections, respectively. Hospital admission occurred in 27.1% (16/59) of Shigella and 25% (4/16) of Campylobacter. Length of stay ranged between 1 and 2 days for both pathogens (Table 1). Of cases with available clinical data, Shigella infections were more likely to report fever during their illness compared to Campylobacter (80% versus 45.4%) (Table 2). Seizures were observed in 4 Shigella infected patients. No episodes of Shigella or Campylobacter bacteremia were identified. Among patients with an identified exposure, daycare attendance and contact with individuals experiencing similar symptoms were most common (Table 2). The vast majority of Shigella species were S. sonnei (96.6%) and all Campylobacter were C. jejuni (Table 3). Resistance to trimethoprim-sulfamethoxazole (TMP-SMX) was common (40/55, 72.7%) among Shigella isolates tested. No resistance to fluoroquinolones or third generation cephalosporins in any of the Shigella spp. isolates was observed. Susceptibility testing was not performed in Campylobacter due to lack of isolates. The most frequent antibiotic used was azithromycin (in 73.3% and 75% of patients with Shigella and Campylobacter, respectively). Major complications included urinary tract infection (n=1), rectal prolapse (n=1) and splenomegaly (n=1). Conclusion Infections due to Shigella and Campylobacter were a significant burden among pediatric patients between 2019 and 2020 in Houston, TX. The observed high frequency of resistance to TMP-SMX and emergence of multi-drug resistant Shigella in other countries warrants continued surveillance. Disclosures Anthony R. Flores, MD, MPH, PhD, Nothing to disclose Cesar A. Arias, M.D., MSc, Ph.D., FIDSA, Entasis Therapeutics (Grant/Research Support)MeMed Diagnostics (Grant/Research Support)Merk (Grant/Research Support)

A Review of Campylobacter Infections in Dogs

Campylobacter spp. are important bacterial enteropathogens that cause diarrhea in dogs with the predominant species being Campylobacter jejuni, C. helveticus, and C. upsaliensis. Although campylobacteriosis is subclinical in many dogs, some may develop moderate to mild enteritis. Puppies, kenneled dogs, and dogs with concurrent conditions are highly susceptible to Campylobacter-associated diarrhea. Diagnosis of suspected Campylobacter-associated diarrhea in dogs poses a challenge to veterinarians as the fecal enteric panels are costly, require technical knowledge, and are time consuming, however molecular approaches for diagnosing the Campylobacter spp. infections are becoming readily available and can help in accurate and fast diagnosis. Campylobacter spp. are amongst the prioritized human and animal pathogens with regards to antimicrobial resistance. The rise and spread of antimicrobial resistance threatens the effective treatment and control of Campylobacter infections. Multi-drug resistance Campylobacter spp. have been isolated from dogs therefore treatment should only be administered where necessary. In conclusion, understanding the epidemiology, diagnosis, treatment and zoonotic potential of Campylobacter spp. will enable small animal practitioners include them among the differential diagnoses of diarrheic diseases in dogs.

264Antibiotic use associated with acute gastroenteritis in Australian primary care

Background Inappropriate antibiotic use is a global health concern as it increases antibiotic resistance. Antibiotics are not routinely recommended for treating acute gastroenteritis, non-typhoidal salmonella and campylobacter infections. We investigated adherence to these recommendations in primary care. Methods We used a large electronic database of primary care records to identify presentations for acute gastroenteritis, non-typhoidal salmonella and campylobacter infections and antibiotic prescribing from 1st Jan 2013 to 31 December 2018. We estimated the proportions of cases prescribed antibiotics according to various characteristics and examined the antibiotics prescribed. Results A total of 86998, 1106, and 1952 participants were identified with acute gastroenteritis, non-typhoidal salmonella, and campylobacter infections and correspondingly 10% (8720/86998), 40% (437/1106), and 57% (1118/1952) of these cases were prescribed antibiotics in the period up to 5 days post-diagnosis. Patients residing in outer regional/remote areas and those from Northern Territory and Queensland were more likely to be prescribed antibiotics than those residing in major cities and those from other states (p < =0.04). No dominant antibiotic class was prescribed for acute gastroenteritis. Quinolones (28.6%) and macrolides (27.0%) were the most frequently prescribed antibiotics for non-typhoidal salmonella, and macrolides (69%) were the predominant antibiotics prescribed for campylobacter. Conclusion The high proportion of antibiotics dispensed in the general population with acute gastroenteritis, non-typhoidal salmonella and campylobacter infections suggests that antimicrobial stewardship needs to include better education and awareness around treatment guidelines for such infections. Key messages Antibiotics use was common for Australian population with acute gastroenteritis, particularly those with non-typhoidal salmonella and campylobacter infections.

Foodborne Pathogen Campylobacter

Campylobacter is the most common bacterial cause of human gastroenteritis in the world, with the species Campylobacter jejuni being responsible for over 80% of Campylobacter infections [...]

Seasonal Associations Between Foodborne Campylobacter Infections and Ambient Temperature in US, 2010–2019

Objectives In order to effectively mitigate the effects of climate change on human health, spatiotemporal relationships between Campylobacter infections and environmental drivers have to be systematically examined to determine whether common seasonal summer peaks observed in Campylobacter infections are well aligned with peaks in raising ambient temperatures. This study aims to evaluate the seasonal relationship between monthly ambient temperature and the monthly Campylobacter infections routinely collected by the CDC Foodborne Diseases Active Surveillance Network (FoodNet) in the United States in 2010–2019. Methods We created time series of monthly Campylobacter infection rates from the FoodNet Fast platform for ten participating states from January 2010 to December 2019 (120 months). We estimated average monthly temperatures for the ten states for the study period using the National Climate and Data Center's Global Summary of the Day database. To assess the seasonal synchronization and determine the lag effect, we used serial cross-correlation analysis. To examine the associations between Campylobacter rates with ambient temperature and adjust for seasonality and trend, we applied a harmonic negative binomial mixed-effects regression model. We also estimated peak timing and amplitude for infections and temperature using the δ-method. Results Serial synchronization between monthly Campylobacter infection rates and ambient temperature was observed in all FoodNet Surveillance states except for California. A one-month delay in peak infection after the peak in temperature was detected in Colorado, Connecticut, Maryland, Minnesota, New Mexico, New York, and Oregon. After adjusting for seasonality and trend across ten states, the relative risk of infection rates increased by 5% with the increase in monthly average temperature by 5.45°C equivalent to a shift from 75th to 95th percentile (95%CI: 1.02–1.09, p < 0.002). Conclusions An increase in monthly average temperature is associated with an increased risk of Campylobacter infection after adjusting for common summer seasonal patterns. Knowledge of the relationship will potentially improve the reliability and accuracy of integrated early warning outbreak forecasts and could guide climate mitigation strategies. Funding Sources None.