scholarly journals A chain-binomial model for intra-household spread of Mycobacterium tuberculosis in a low socio-economic setting in Pakistan

2006 ◽  
Vol 135 (1) ◽  
pp. 27-33 ◽  
Author(s):  
S. AKHTAR ◽  
T. E. CARPENTER ◽  
S. K. RATHI
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Antibiotic Therapy ◽  
Goodness Of Fit ◽  
Index Case ◽  
Substantial Reduction ◽  
Educational Programme ◽  
Maximum Likelihood Estimates ◽  
Binomial Model ◽  
Goodness Of Fit Test ◽  
Household Contacts

A simulation study using Greenwood's chain-binomial model was carried out to elucidate the spread and control of Mycobacterium tuberculosis among the household contacts of infectious pulmonary tuberculosis (TB) patients. Based on the observed data, the maximum-likelihood estimates (±S.E.) of chain-binomial probabilities of intra-household M. tuberculosis transmission from an index case in 3-person and 4-person households were 0·313±0·008 and 0·325±0·009 respectively. The χ2 goodness-of-fit test of observed and simulated mean expected frequencies of cases revealed good fit for 3-person (P=0·979) and 4-person (P=0·546) households. With the assumption of varying risk of M. tuberculosis transmission across the households under β-distribution, goodness-of-fit tests of observed and mean simulated expected frequencies revealed the inadequacy of Greenwood's chain-binomial model both for 3-person (P=0·0185) and 4-person (P<0·001) households. Simulated M. tuberculosis control strategy comprising efficient diagnosis, segregation and prompt antibiotic therapy of index pulmonary TB patients showed a substantial reduction of new cases among the household contacts in both household sizes. In conclusion, segregation coupled with prompt antibiotic therapy of the index case, chemoprophylaxis of M. tuberculosis-exposed household contacts, and the assessment of household environmental risks to devise and implement an educational programme may help reduce the TB burden in this and similar settings.

scholarly journals Intra-abdominal infections: the role of different classifications on the selection of the best antibiotic treatment.

2019 ◽  
Author(s):  
João Silva Nunes ◽  
Teresa Maria Costa Cardoso
Keyword(s):  
Hospital Mortality ◽  
Antibiotic Therapy ◽  
Antibiotic Treatment ◽  
Goodness Of Fit ◽  
Individual Characteristics ◽  
Empiric Antibiotic Therapy ◽  
Operating Characteristics ◽  
Goodness Of Fit Test ◽  
Abdominal Infections ◽  
Selection Of

Abstract Background: Intra-abdominal infections (IAIs) represent a serious cause of morbimortality. A full classification, including all facets of IAIs, does not exist. Two classifications are used to subdivide IAIs: uncomplicated or complicated, considering infection extent; and community-acquired, healthcare-associated or hospital-acquired, regarding the place of acquisition. Inadequate antibiotic therapy is associated with treatment failure and increased mortality. This study was designed to determine accuracy of different classifications of IAIs to identify infections by pathogens sensitive to current treatment guidelines helping the selection of the best antibiotic therapy. Methods: A retrospective cohort study including all adult patients discharged from hospital with a diagnosis of IAI between 1st of January and 31st of October 2016. All variables potentially associated with pre-defined outcomes: infection by a pathogen sensitive to non-pseudomonal cephalosporin or ciprofloxacin plus metronidazole (ATB 1, primary outcome), sensitive to piperacillin-tazobactam (ATB 2) and hospital mortality (secondary outcomes) were studied through logistic regression. Accuracy of the models was assessed by area under receiver operating characteristics (AUROC) curve and calibration was tested using the Hosmer-Lemeshow goodness-of-fit test. Results: Of 1804 patients screened 154 met inclusion criteria. Sensitivity to ATB 1 was independently associated with male gender (adjusted OR=2.612) and previous invasive procedures in the last year (adjusted OR=0.424) (AUROC curve=0,65). Sensitivity to ATB 2 was independently associated with liver disease (adjusted OR=3.580) and post-operative infections (adjusted OR=2.944) (AUROC curve=0.604). Hospital mortality was independently associated with age≥70 (adjusted OR=4.677), solid tumour (adjusted OR=3.127) and sensitivity to non-pseudomonal cephalosporin or ciprofloxacin plus metronidazole (adjusted OR=0.368). The accuracy of pre-existing classifications to identify infection by a pathogen sensitive to ATB 1 was 0.59 considering place of acquisition, 0.61 infection extent and 0.57 local of infection, for ATB 2 it was 0.66, 0.50 and 0.57, respectively. Conclusion: None of existing classifications had a good discriminating power to identify IAIs caused by pathogens sensitive to current antibiotic treatment recommendations. A new classification, including patients’ individual characteristics like those included in the current model, might have a higher potential to distinguish IAIs by resistant pathogens allowing a better choice of empiric antibiotic therapy. Keywords: intra-abdominal infections; classification; antibiotic therapy; hospital mortality.

scholarly journals Intra-abdominal infections: the role of different classifications on the selection of the best antibiotic treatment

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
João Silva-Nunes ◽  
Teresa Cardoso
Keyword(s):  
Hospital Mortality ◽  
Antibiotic Therapy ◽  
Antibiotic Treatment ◽  
Goodness Of Fit ◽  
Individual Characteristics ◽  
Empiric Antibiotic Therapy ◽  
Operating Characteristics ◽  
Goodness Of Fit Test ◽  
Abdominal Infections ◽  
Selection Of

Abstract Background Intra-abdominal infections (IAIs) represent a most frequent gastrointestinal emergency and serious cause of morbimortality. A full classification, including all facets of IAIs, does not exist. Two classifications are used to subdivide IAIs: uncomplicated or complicated, considering infection extent; and community-acquired, healthcare-associated or hospital-acquired, regarding the place of acquisition. Adequacy of initial empirical antibiotic therapy prescribed is an essential need. Inadequate antibiotic therapy is associated with treatment failure and increased mortality. This study was designed to determine accuracy of different classifications of IAIs to identify infections by pathogens sensitive to current treatment guidelines helping the selection of the best antibiotic therapy. Methods A retrospective cohort study including all adult patients discharged from hospital with a diagnosis of IAI between 1st of January and 31st of October, 2016. All variables potentially associated with pre-defined outcomes: infection by a pathogen sensitive to non-pseudomonal cephalosporin or ciprofloxacin plus metronidazole (ATB 1, primary outcome), sensitive to piperacillin-tazobactam (ATB 2) and hospital mortality (secondary outcomes) were studied through logistic regression. Accuracy of the models was assessed by area under receiver operating characteristics (AUROC) curve and calibration was tested using the Hosmer-Lemeshow goodness-of-fit test. Results Of 1804 patients screened 154 met inclusion criteria. Sensitivity to ATB 1 was independently associated with male gender (adjusted OR = 2.612) and previous invasive procedures in the last year (adjusted OR = 0.424) (AUROC curve = 0,65). Sensitivity to ATB 2 was independently associated with liver disease (adjusted OR = 3.580) and post-operative infections (adjusted OR = 2.944) (AUROC curve = 0.604). Hospital mortality was independently associated with age ≥ 70 (adjusted OR = 4.677), solid tumour (adjusted OR = 3.127) and sensitivity to non-pseudomonal cephalosporin or ciprofloxacin plus metronidazole (adjusted OR = 0.368). The accuracy of pre-existing classifications to identify infection by a pathogen sensitive to ATB 1 was 0.59 considering place of acquisition, 0.61 infection extent and 0.57 local of infection, for ATB 2 it was 0.66, 0.50 and 0.57, respectively. Conclusion None of existing classifications had a good discriminating power to identify IAIs caused by pathogens sensitive to current antibiotic treatment recommendations. A new classification, including patients’ individual characteristics like those included in the current model, might have a higher potential to distinguish IAIs by resistant pathogens allowing a better choice of empiric antibiotic therapy.

scholarly journals Bootstrap goodness-of-fit test for the beta-binomial model

2001 ◽  
Vol 28 (5) ◽  
pp. 561-571 ◽  
Author(s):  
Steven T. Garren ◽  
Richard L. Smith ◽  
Walter W. Piegorsch
Keyword(s):  
Goodness Of Fit ◽  
Binomial Model ◽  
Goodness Of Fit Test

scholarly journals Intra-abdominal infections: the role of different classifications on the selection of the best antibiotic treatment.

2019 ◽  
Author(s):  
João Silva Nunes ◽  
Teresa Maria Costa Cardoso
Keyword(s):  
Hospital Mortality ◽  
Antibiotic Therapy ◽  
Antibiotic Treatment ◽  
Goodness Of Fit ◽  
Individual Characteristics ◽  
Empiric Antibiotic Therapy ◽  
Operating Characteristics ◽  
Goodness Of Fit Test ◽  
Abdominal Infections ◽  
Selection Of

Abstract Background: Intra-abdominal infections (IAIs) represent a serious cause of morbimortality. A full classification, including all facets of IAIs, does not exist. Two classifications are used to subdivide IAIs: uncomplicated or complicated, considering infection extent; and community-acquired, healthcare-associated or hospital-acquired, regarding the place of acquisition. Inadequate antibiotic therapy is associated with treatment failure and increased mortality. This study was designed to determine accuracy of different classifications of IAIs to identify infections by pathogens sensitive to current treatment guidelines helping the selection of the best antibiotic therapy. Methods: A retrospective cohort study including all adult patients discharged from hospital with a diagnosis of IAI between 1st of January and 31st of October 2016. All variables potentially associated with pre-defined outcomes: infection by a pathogen sensitive to non-pseudomonal cephalosporin or ciprofloxacin plus metronidazole (ATB 1, primary outcome), sensitive to piperacillin-tazobactam (ATB 2) and hospital mortality (secondary outcomes) were studied through logistic regression. Accuracy of the models was assessed by area under receiver operating characteristics (AUROC) curve and calibration was tested using the Hosmer-Lemeshow goodness-of-fit test. Results: Of 1804 patients screened 154 met inclusion criteria. Sensitivity to ATB 1 was independently associated with male gender (adjusted OR=2.612) and previous invasive procedures in the last year (adjusted OR=0.424) (AUROC curve=0,65). Sensitivity to ATB 2 was independently associated with liver disease (adjusted OR=3.580) and post-operative infections (adjusted OR=2.944) (AUROC curve=0.604). Hospital mortality was independently associated with age≥70 (adjusted OR=4.677), solid tumour (adjusted OR=3.127) and sensitivity to non-pseudomonal cephalosporin or ciprofloxacin plus metronidazole (adjusted OR=0.368). The accuracy of pre-existing classifications to identify infection by a pathogen sensitive to ATB 1 was 0.59 considering place of acquisition, 0.61 infection extent and 0.57 local of infection, for ATB 2 it was 0.66, 0.50 and 0.57, respectively. Conclusion: None of existing classifications had a good discriminating power to identify IAIs caused by pathogens sensitive to current antibiotic treatment recommendations. A new classification, including patients’ individual characteristics like those included in the current model, might have a higher potential to distinguish IAIs by resistant pathogens allowing a better choice of empiric antibiotic therapy. Keywords: intra-abdominal infections; classification; antibiotic therapy; hospital mortality.

scholarly journals Intra-abdominal infections: the role of different classifications on the selection of the best antibiotic treatment.

2019 ◽  
Author(s):  
João Silva Nunes ◽  
Teresa Maria Costa Cardoso
Keyword(s):  
Hospital Mortality ◽  
Antibiotic Therapy ◽  
Antibiotic Treatment ◽  
Goodness Of Fit ◽  
Individual Characteristics ◽  
Empiric Antibiotic Therapy ◽  
Operating Characteristics ◽  
Goodness Of Fit Test ◽  
Abdominal Infections ◽  
Selection Of

Abstract Background: Intra-abdominal infections (IAIs) represent a serious cause of morbimortality. A full classification, including all facets of IAIs, does not exist. Two classifications are used to subdivide IAIs: uncomplicated or complicated, considering infection extent; and community-acquired, healthcare-associated or hospital-acquired, regarding the place of acquisition. Inadequate antibiotic therapy is associated with treatment failure and increased mortality. This study was designed to determine accuracy of different classifications of IAIs to identify infections by pathogens sensitive to current treatment guidelines helping the selection of the best antibiotic therapy. Methods: A retrospective cohort study including all adult patients discharged from hospital with a diagnosis of IAI between 1st of January and 31st of October 2016. All variables potentially associated with pre-defined outcomes: infection by a pathogen sensitive to non-pseudomonal cephalosporin or ciprofloxacin plus metronidazole (ATB 1, primary outcome), sensitive to piperacillin-tazobactam (ATB 2) and hospital mortality (secondary outcomes) were studied through logistic regression. Accuracy of the models was assessed by area under receiver operating characteristics (AUROC) curve and calibration was tested using the Hosmer-Lemeshow goodness-of-fit test. Results: Of 1804 patients screened 154 met inclusion criteria. Sensitivity to ATB 1 was independently associated with male gender (adjusted OR=2.612) and previous invasive procedures in the last year (adjusted OR=0.424) (AUROC curve=0,65). Sensitivity to ATB 2 was independently associated with liver disease (adjusted OR=3.580) and post-operative infections (adjusted OR=2.944) (AUROC curve=0.604). Hospital mortality was independently associated with age≥70 (adjusted OR=4.677), solid tumour (adjusted OR=3.127) and sensitivity to non-pseudomonal cephalosporin or ciprofloxacin plus metronidazole (adjusted OR=0.368). The accuracy of pre-existing classifications to identify infection by a pathogen sensitive to ATB 1 was 0.59 considering place of acquisition, 0.61 infection extent and 0.57 local of infection, for ATB 2 it was 0.66, 0.50 and 0.57, respectively. Conclusion: None of existing classifications had a good discriminating power to identify IAIs caused by pathogens sensitive to current antibiotic treatment recommendations. A new classification, including patients’ individual characteristics like those included in the current model, might have a higher potential to distinguish IAIs by resistant pathogens allowing a better choice of empiric antibiotic therapy. Keywords: intra-abdominal infections; classification; antibiotic therapy; hospital mortality.

scholarly journals Intra-abdominal infections: the role of different classifications on the selection of the best antibiotic treatment

2019 ◽  
Author(s):  
João Silva Nunes ◽  
Teresa Maria Costa Cardoso
Keyword(s):  
Hospital Mortality ◽  
Antibiotic Therapy ◽  
Antibiotic Treatment ◽  
Goodness Of Fit ◽  
Individual Characteristics ◽  
Empiric Antibiotic Therapy ◽  
Operating Characteristics ◽  
Goodness Of Fit Test ◽  
Abdominal Infections ◽  
Selection Of

Abstract Background Intra-abdominal infections (IAIs) represent a most frequent gastrointestinal emergency and serious cause of morbimortality. A full classification including all facets of IAIs does not exist. Two classifications are used to subdivide IAIs: uncomplicated or complicated, considering infection extent; and community-acquired, healthcare-associated or hospital-acquired, regarding place of acquisition. Adequacy of initial empirical antibiotic therapy prescribed is an essential need. Inadequate antibiotic therapy is associated with treatment failure and increased mortality. This study was designed to determine accuracy of different classifications of IAIs to identify infections by pathogens sensitive to current treatment guidelines helping in selection of best antibiotic therapy. Methods Retrospective cohort study including all adult patients discharged from hospital with diagnosis of IAI between 1st of January and 31st of October, 2016. All variables potentially associated with pre-defined outcomes: infection by a pathogen sensitive to non-pseudomonal cephalosporin or ciprofloxacin plus metronidazol (ATB 1, primary outcome), sensitive to piperacillin-tazobactam (ATB 2) and hospital mortality (secondary outcomes) were studied through logistic regression. Accuracy of the models was assessed by area under receiver operating characteristics (AUROC) curve and calibration was tested using Hosmer-Lemeshow goodness-of-fit test. Results Of 1804 patients screened 154 met inclusion criteria. Sensitivity to ATB 1 was independently associated with male gender (adjusted OR=2.612) and previous invasive procedures in last year (adjusted OR=0.424) (AUROC curve=0,65). Sensitivity to ATB 2 was independently associated with liver disease (adjusted OR=3.580) and post-operative infections (adjusted OR=2.944) (AUROC curve=0.604). Hospital mortality was independently associated with age≥70 (adjusted OR=4.677), solid tumor (adjusted OR=3.127) and sensitivity to non-pseudomonal cephalosporin or ciprofloxacin plus metronidazole (adjusted OR=0.368). Accuracy of pre-existing classifications to identify infection by a pathogen sensitive to ATB 1 was 0.59 considering place of acquisition, 0.61 infection extent and 0.57 local of infection, for ATB 2 it was 0.66, 0.50 and 0.57, respectively. Conclusion None of existent classifications had a good discriminative power to identify IAIs caused by pathogens sensitive to current antibiotic treatment recommendations. A new classification including patients individual characteristics like those included in current model might have a higher potential to distinguish IAIs by resistant pathogens allowing a better choice of empiric antibiotic therapy.

On a Likelihood-Based Goodness-of-Fit Test of the Beta-Binomial Model

Biometrics ◽  
2000 ◽  
Vol 56 (3) ◽  
pp. 947-949 ◽  
Author(s):  
Steven T. Garren ◽  
Richard L. Smith ◽  
Walter W. Piegorsch
Keyword(s):  
Goodness Of Fit ◽  
Binomial Model ◽  
Goodness Of Fit Test

The Application of χ2 Goodness-of-Fit Detection Method

2014 ◽  
Vol 687-691 ◽  
pp. 739-742
Author(s):  
Xiao Cheng Gao
Keyword(s):  
Maximum Likelihood ◽  
Normal Distribution ◽  
Test Scores ◽  
Goodness Of Fit ◽  
Detection Method ◽  
Maximum Likelihood Estimates ◽  
Goodness Of Fit Test ◽  
Test Of Hypothesis

This paper is to use the method of test of goodness of fit test of hypothesis. By computing the maximum likelihood estimates of income, the results, to test scores of students to obey normal distribution, and confirm by MATLAB.

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