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Objective To investigate the distribution and antimicrobial resistance of pathogens causing pneumonia in acute stroke patients,and guide clinical antimicrobial use.Methods Patients with stroke-associated pneumonia (SAP)admitted to a tertiary first-class hospital from 2008 to 2013 were investigated retrospectively,distribution and antimicrobial susceptibility testing results of pathogens from sputum were analyzed.Results A total of 98 pa-tients with SAP were investigated,124 stains were isolated from sputum specimens,75 strains (60.48% )were gram-negative bacteria,44 (35.49% )were gram-positive bacteria,and 5 (4.03% )were fungi. There were 21 cases of mixed infection (21.43% ),bacterial alterations during treatment process existed among 23 cases(23.47% ).The top 4 isolated pathogens were Staphylococcus aureus (S. aureus,n= 43,34.68% ),Klebsiella pneumoniae (K. pneumoniae,n= 19,15.32% ),Pseudomonasaeruginosa(P. aeruginosa,n= 18,14.52% ),and Acinetobacterbau-mannii(A. baumannii,n= 18,14.52% ). Antimicrobial resistance rates of K. pneumoniae were all 80% ,resistance rates of P.aeruginosa to imipenem was 33 .33% . No resistant strains were detected among fungi.Conclusion The main pathogens causing SAP in this hospital are S.au-reus,K.pneumoniae,A.baumannii,and P.aeruginosa,except K.pneumoniae,the other strains are severely re-sistant to antimicrobial agents,clinicians should choose antimicrobial agents according to the distribution character-istics and antimicrobial susceptibility testing results.
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Objective To study the risk factors for children with acute central nervous system(CNS)viral in-fection,so that pediatrician may identify children with poor prognosis at early stages of the disease,and provide them with a theoretical basis for clinical treatment. Methods The clinical data of a cohort patients of acute CNS viral infec-tion who were hospitalized at the First Affiliated Hospital of Fujian Medical University between January 2010 and June 2013 were retrospectively collected and analyzed. According to Glasgow outcome scale on discharge,children were di-vided into good prognosis group and poor prognosis group. Clinical data and outcomes were analyzed by using univariate analysis and binary Logistic regression multivariate analysis. Results Three hundred and one cases were enrolled,278 (92. 36% )patients were assigned to the good prognosis group,and 23(7. 64% )patients were assigned to the poor prognosis group. By univariate analysis,the patients in the poor prognosis group had longer duration of sickness before admission,longer time of fever,lower white blood cell count in cerebrospinal fluid,a relatively lower calcium level,con-scious disturbance at the early stage,multiple seizures,convulsive status epilepticus,meningeal irritation sign,muscle weakness,severe changes in electroencephalogram(EEG),and abnormal neuroimaging findings(computed tomography or magnetic resonance imaging,or both)had significant differences between the good prognosis group and the poor short - term outcome groups(all P < 0. 05). By binary Logistic regression multivariate analysis,factors indicating a poor prognosis during the early stage were conscious disturbance at the early stage(0R = 4. 885,95% CI:1. 523 - 15. 670, P = 0. 008),multiple seizures(0R = 6. 352,95% CI:1. 905 - 21. 178,P = 0. 003),severe changes in EEG( 0R =4. 269,95% CI:1. 708 - 10. 666,P = 0. 002),and abnormal neuroimaging findings( 0R = 9. 740,95% CI:2. 360 -40. 192,P = 0. 002). Conclusions Conscious disturbance at the early stage,multiple seizures,severe changes in EEG and abnormal neuroimaging findings are risk factors for acute viral infection of CNS in children.