[Clinical features and antimicrobial resistance of invasive non-typhoid Salmonella infection in children at Xiamen].

Objective: To investigate the clinical characteristics, serogroups and antimicrobial resistance of invasive non-typhoid Salmonella infection in children at Xiamen. Methods: Retrospective cohort study. The clinical manifestations, treatment, prognosis, serogroups and antimicrobial resistance of 29 hospitalized children with invasive non-typhoid Salmonella infection confirmed by blood, cerebrospinal fluid, bone marrow and other sterile body fluids or deep pus culture at the Department of Infectious Diseases, the Department of Orthopedics and the Department of General Surgery in Xiamen Children's Hospital from January 2016 to December 2021 were analyzed. According to the clinical diagnosis criteria, the patients were divided into sepsis group and non-sepsis group (bacteremia and local suppurative infection). The inflammatory markers, serogroups distribution and drug resistance were compared between the two groups. Comparison between groups using Mann-Whitney U test and χ2 test. Results: Among the 29 cases, there were 17 males and 12 females, with an onset age of 14 (9, 25) months, and 10 cases (34%) of patients were younger than 1 year old, 15 cases (52%) under 1 to 3 years old, and 4 cases (14%) greater than or equal 3 years old. The onset time of 25 cases (86%) was from April to September. The diseases included 19 cases (66%) septicemia (2 of which were combined with suppurative meningitis), 10 cases (34%) non-sepsis group, including 7 cases bacteremia and 3 cases local suppurative infection (2 cases of osteomyelitis, 1 case of appendicitis with peritonitis). The clinical manifestations were fever in 29 cases (100%), diarrhea and abdominal pain in 18 cases (62%), cough and runny nose in 10 cases (34%). Eighteen cases (62%) were cured and 11 cases (38%) were improved by effective antibiotics treatment. C-reactive protein in sepsis group was significantly higher than that in non-sepsis group (25.2 (16.1, 56.4) vs. 3.4 (0.5, 7.5) mg/L, Z=-3.81, P<0.001).The serogroups of C, B and E were the most prevalent among non-typhoid Salmonella isolates, accounting for 10 cases (34%), 9 cases (31%) and 7 cases (24%) respectively. Antibacterial drug sensitivity test showed that the sensitivity rates of imipenem, ertapenem and piperaciratazobactam were all 100% (31/31), those of ceftazidime, ceftriaxone, and cefepime were 94% (29/31), 94% (29/31) and 97% (30/31) respectively. The drug resistance rates of ampicillin, ampicillin-sulbactam and trimethoprim-sulfamethoxazole were 51% (16/31), 48% (15/31) and 48% (15/31) respectively, those of cefazolin, cefotetan, tobramycin, gentamicin and amikacinwere all 100% (31/31). There were no significant differences in the drug resistance rates of ceftazidime, ceftriaxone, aztreonam, ampicillin-sulbactam, ampicillin, trimethoprim-sulfamethoxazole and ciprofloxacin between the sepsis group and the non-sepsis group (χ2=0.31,0.31,0.00,0.02,0.02,0.02,0.26, all P>0.05). Conclusions: Invasive non-typhoid Salmonella infection in children at Xiamen mainly occurred in infants younger than 3 years old.The main clinical manifestations are fever, abdominal pain and diarrhea. C-reactive protein can be served as the laboratory indicators for indicating sepsis. The third generation of cephalosporins is recommended as the first choice for treatment.

Polychotomous multivariate models for coronary heart disease simulation. II. Comparisons of risk functions.

This is the second in a series of papers dealing with models of coronary heart disease. Three different types of statistical models are considered as risk functions: the multivariate logistic model, the Cox proportional hazard model and the Neyman exponential risk avoidance model. The types of models differ in the form hypothesized for the probability of occurrence of coronary heart disease outcomes: incident myocardial infarct, cardiac death, and death from other causes. Although the three risk functions are strikingly different, they can all be tested using the CRISPERS chronic disease simulation system. Simulations were performed using data from North Karelia, Finland. The polychotomous multivariate logistic risk function is convenient for studies involving increasing numbers of risk factors. The Cox proportional hazard regression model is shown to be unsuitable for the cohort dataset used as well as for some of the intended uses of the simulation models. The Neyman exponential risk avoidance model involves time in a quite different fashion. It has the inherent advantage of being easier to relate to underlying biological mechanisms because it is the integral of first order rate equations. It is concluded that more than one risk function should be evaluated for simulations of coronary heart disease.

Polychotomous multivariate models for coronary heart disease simulation. III. Model sensitivities and risk factor interventions.

This is the third in a series of papers dealing with models of coronary heart disease. Sensitivity analyses of the logistic risk function and the Neyman risk function are reported. The resulting response surfaces are also used to investigate the optimality of the set of values for the risk coefficients. It is shown that the coefficients estimated by maximum likelihood are preferable to the sets from an optimisation procedure. Two different sets of risk coefficients estimated using short periods and entire epochs for the logistic risk function are shown to lead to similar conclusions concerning simulated primary intervention strategies. However, the corresponding risk factor reductions using the Neyman risk function lead to somewhat different effects. Additional information is needed to distinguish between these two assumptions of the risk function used to model coronary heart disease. This underscores the need to understand the effects of the underlying risk function assumed when interpreting simulated outcomes of intervention strategies.

Polychotomous multivariate models for coronary heart disease simulation. I. Tests of a logistic model.

Stochastic compartmental modeling techniques have been employed to simulate coronary heart disease morbidity and mortality. In the current paper, polychotomous logistic models are used to describe the relationship between risk of disease and multiple risk factors, effect modification and confounding variables. The process of estimating the parameters for two risk factors and three types of outcomes is described for a population followed for five years. A Statistical Analysis System (SAS) procedure was used to estimate risk factor coefficients based on two partial periods and on the entire five year epoch. Most of the estimated coefficients were found to be statistically significant. The model performance was evaluated by comparing the observational data with simulated outcomes using a micropopulation and Monte Carlo techniques. Two different tests of goodness of fit were used. Satisfactory fits were obtained both for the risk coefficients based on two partial periods and those based on the entire epoch. This indicates that the model is suitable for simulation of the effects of intervention strategies. The use of the entire epoch involved estimates of one half as many parameters as did the use of two partial periods. Accordingly, it is concluded that only the entire epoch need be considered for future studies of this population.