Prognostic factors in meningococcal disease. Development of a bedside predictive model and scoring system. Barcelona Meningococcal Disease Surveillance Group

Barquet, Nicolau; Domingo, Peré; Ja, Caylà; Gonzalez, Jean Paul; Rodrigo, Carlos; Fernández-Viladrich, P; Fa, Moraga-Llop; Marco, Francesca De; Vázquez, José Juan; Ja, Sáez-Nieto; Casal, J.; Canela, Jaume; M, Foz

doi:10.1001/jama.278.6.491

Cited by 46 publications

(32 citation statements)

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“…The fi nal regression equation in the multivariate logistic models was used to determine the predicted probabilities of death. The weight of each variable was assumed as the ratio between the modules of the coeffi cient of the analyzed variable and of the smallest coeffi cient among the variables of the logistic regression model, which was rounded to the closest integer (32) . Finally, the score of each patient with a respective probability of death was calculated by adding the weight of each variable in the fi nal model.…”

Section: Model Derivationmentioning

confidence: 99%

Predicting death from kala-azar: construction, development, and validation of a score set and accompanying software

Costa

Rocha

Chaves³

et al. 2016

Rev. Soc. Bras. Med. Trop.

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Section: Model Derivationmentioning

confidence: 99%

Predicting death from kala-azar: construction, development, and validation of a score set and accompanying software

Costa

Rocha

Chaves³

et al. 2016

Rev. Soc. Bras. Med. Trop.

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“…Presently, many laboratories, particularly those in smaller and more rural settings, rely on reference laboratories to perform CSF testing for infectious agents. This leads to delays, which can have significant clinical consequences if therapy is delayed or incorrectly administered (9)(10)(11). It may also have an impact on appropriate infection prevention measures, in some cases including postexposure prophylaxis of close contacts.…”

mentioning

confidence: 99%

Multicenter Evaluation of BioFire FilmArray Meningitis/Encephalitis Panel for Detection of Bacteria, Viruses, and Yeast in Cerebrospinal Fluid Specimens

et al. 2016

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Rapid diagnosis and treatment of infectious meningitis and encephalitis are critical to minimize morbidity and mortality. Comprehensive testing of cerebrospinal fluid (CSF) often includes Gram stain, culture, antigen detection, and molecular methods, paired with chemical and cellular analyses. These methods may lack sensitivity or specificity, can take several days, and require significant volume for complete analysis. The FilmArray Meningitis/Encephalitis (ME) Panel is a multiplexed in vitro diagnostic test for the simultaneous, rapid (ϳ1-h) detection of 14 pathogens directly from CSF specimens: Escherichia coli K1, Haemophilus influenzae, Listeria monocytogenes, Neisseria meningitidis, Streptococcus pneumoniae, Streptococcus agalactiae, cytomegalovirus, enterovirus, herpes simplex virus 1 and 2, human herpesvirus 6, human parechovirus, varicella-zoster virus, and Cryptococcus neoformans/Cryptococcus gattii. We describe a multicenter evaluation of 1,560 prospectively collected CSF specimens with performance compared to culture (bacterial analytes) and PCR (all other analytes). The FilmArray ME Panel demonstrated a sensitivity or positive percentage of agreement of 100% for 9 of 14 analytes. Enterovirus and human herpesvirus type 6 had agreements of 95.7% and 85.7%, and L. monocytogenes and N. meningitidis were not observed in the study. For S. agalactiae, there was a single false-positive and false-negative result each, for a sensitivity and specificity of 0 and 99.9%, respectively. The specificity or negative percentage of agreement was 99.2% or greater for all other analytes. The FilmArray ME Panel is a sensitive and specific test to aid in diagnosis of ME. With use of this comprehensive and rapid test, improved patient outcomes and antimicrobial stewardship are anticipated.

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“…Impaired mental status, seizures and focal neurologic signs after the first dose of antibiotics were considered neurological complications. The development of septic shock, acute respiratory failure, renal failure, and/or consumption coagulopathy was considered as extra-neurological complications if related to ABM and apparent on admission or shortly afterwards [17][18][19][20][21][22].…”

Section: Definitionsmentioning

confidence: 99%

“…The corresponding incidence was 4.03/ 100,000 and 7.40/100,000 inhabitants/year for group I and II, respectively (RR = 1.84; 95% CI: 1.56-2.17, P < 0.0001). The median yearly number of cases was 21 (95% CI: [19][20][21][22][23][24][25]. Demographics of the population studied are summarized in Table 1.…”

Section: Population Studiedmentioning

confidence: 99%

See 1 more Smart Citation

Diagnosis and Treatment of Tuberculous Meningitis

Kim¹

2014

J Neurocrit Care

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Prognostic factors in meningococcal disease. Development of a bedside predictive model and scoring system. Barcelona Meningococcal Disease Surveillance Group

Cited by 46 publications

References 0 publications

Predicting death from kala-azar: construction, development, and validation of a score set and accompanying software

Predicting death from kala-azar: construction, development, and validation of a score set and accompanying software

Multicenter Evaluation of BioFire FilmArray Meningitis/Encephalitis Panel for Detection of Bacteria, Viruses, and Yeast in Cerebrospinal Fluid Specimens

Diagnosis and Treatment of Tuberculous Meningitis

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