Development of a clinical prediction model for an ordinal outcome: the World Health Organization Multicentre Study of Clinical Signs and Etiological agents of Pneumonia, Sepsis and Meningitis in Young Infants. WHO/ARI Young Infant Multicentre Study Group.

@article{Harrell1998DevelopmentOA,
  title={Development of a clinical prediction model for an ordinal outcome: the World Health Organization Multicentre Study of Clinical Signs and Etiological agents of Pneumonia, Sepsis and Meningitis in Young Infants. WHO/ARI Young Infant Multicentre Study Group.},
  author={Frank E. Harrell and Peter A. Margolis and Sandy Gove and Karen E. Mason and Edward Kim Mulholland and Deborah Lehmann and Lulu M. Muhe and Salvacion R. Gatchalian and Heinz F. Eichenwald},
  journal={Statistics in medicine},
  year={1998},
  volume={17 8},
  pages={
          909-44
        }
}
This paper describes the methodologies used to develop a prediction model to assist health workers in developing countries in facing one of the most difficult health problems in all parts of the world: the presentation of an acutely ill young infant. Statistical approaches for developing the clinical prediction model faced at least two major difficulties. First, the number of predictor variables, especially clinical signs and symptoms, is very large, necessitating the use of data reduction… 
View on PubMed
lcc.uma.es
125 Citations
Background Citations
9
Methods Citations
15

125 Citations

Citation Type

Citation Type

Predictors of neonatal sepsis in developing countries
TLDR
Physical signs can be used to identify young infants at risk of severe disease, however with limited specificity, resulting in large numbers of unnecessary referrals, but there appear to be limits on the accuracy of prediction that is achievable.
Early diagnosis model for meningitis supports public health decision making.
Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED)
TLDR
The risk of mortality among ED patients could be accurately predicted by using common clinical signs and biochemical tests, and a close agreement between predicted and observed mortality risk was found.
Predicting severe pneumonia in the emergency department: a global study of the Pediatric Emergency Research Networks (PERN)—study protocol
TLDR
This study overcomes limitations of prior pneumonia severity scores by allowing for broad generalisability of findings, which can be actively implemented after model development and validation.
A Clinical Prediction Algorithm to Stratify Pediatric Musculoskeletal Infection by Severity.
TLDR
Clinical and laboratory data obtained in the emergency department may be used to accurately differentiate pediatric MSKI severity at presentation irrespective of tissue involvement and anatomic diagnosis.
Prognosis following severe head injury: Development and validation of a model for prediction of death, disability, and functional recovery.
TLDR
A practical model for predicting the probability of death, survival with major disability, and functional recovery in patients who are comatose 24 hours after severe head injury is developed and validated.
Abnormal Heart Rate Characteristics Preceding Neonatal Sepsis and Sepsis-Like Illness
TLDR
Continuous HRC monitoring is a generally valid and potentially useful noninvasive tool in the early diagnosis of neonatal sepsis and sepsi-like illness.
Risk stratification in acute heart failure: rationale and design of the STRATIFY and DECIDE studies.
Pneumonia Risk Stratification Scores for Children in Low-Resource Settings: A Systematic Literature Review
TLDR
While pediatric pneumonia-specific risk scores have been developed and validated, it is yet unclear if implementation is feasible, what impact, if any, implemented scores may have on child outcomes, or how broadly scores may be generalized.
Derivation and internal validation of the screening to enhance prehospital identification of sepsis (SEPSIS) score in adults on arrival at the emergency department
TLDR
The SEPSIS score is significantly associated with high risk of severe illness or death from sepsis on arrival at the Emergency Department, and may assist ambulance clinicians to identify those patients with sePSis in need of antibiotic therapy.
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 60 REFERENCES
A scoring system to quantify illness in babies under 6 months of age
TLDR
Ordinal logistic regression analysis was used on a sample of 1007 babies under 6 months of age seen at home and in hospital to identify the symptoms and signs of serious illness and has been made into a score card called Baby Check, designed for use by parents and health professionals to quantify the severity of a baby's illness.
Prognostic scores for detecting a high risk group: estimating the sensitivity when applied to new data.
TLDR
It is concluded that Copas' method, which is easy to implement in practice, may be helpful in realistically anticipating the extent of such exaggeration, and that it can be usefully employed before pursuing a scoring system on newly collected data.
Assessment of predictive models for binary outcomes: an empirical approach using operative death from cardiac surgery.
TLDR
Eight methodological strategies for creating predictive models are compared in a large, complex data base consisting of preoperative risk and operative outcome data on 12,712 patients undergoing coronary artery bypass grafting and entered into the Department of Veterans Affairs Cardiac Surgery Risk Assessment Program between April 1987 and March 1990.
Regression modelling strategies for improved prognostic prediction.
TLDR
A general index of predictive discrimination is used to measure the ability of a model developed on training samples of varying sizes to predict survival in an independent test sample of patients suspected of having coronary artery disease.
Probabilistic prediction in patient management and clinical trials.
It is argued that the provision of accurate and useful probabilistic assessments of future events should be a fundamental task for biostatisticians collaborating in clinical or experimental medicine,…
Development of health risk appraisal functions in the presence of multiple indicators: the Framingham Study nursing home institutionalization model.
TLDR
A methodology for the development of health risk appraisal functions when the number of potential risk factors is large is discussed and sex specific functions for nursing home institutionalization are illustrated.
Regression models for prognostic prediction: advantages, problems, and suggested solutions.
TLDR
Regression models can make more accurate predictions than other methods such as stratification and recursive partitioning, when model assumptions are thoroughly examined; steps are taken when assumptions are violated; and the method of model formulation does not result in overfitting the data.
Ordinal regression models for epidemiologic data.
TLDR
The application of the proposed models to data from a study of chest x-rays of workers exposed to mineral fibers confirmed that they are easy to use and interpret, but gave results quite similar to those obtained using simple logistic regression after dichotomizing outcome in the conventional way.
Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors.
TLDR
An easily interpretable index of predictive discrimination as well as methods for assessing calibration of predicted survival probabilities are discussed, applicable to all regression models, but are particularly needed for binary, ordinal, and time-to-event outcomes.
Multivariate tests for multiple endpoints in clinical trials.
TLDR
A risk score test whose rejection boundary corresponds to a contour of constant risk is proposed, which would place an emphasis on the effect of non-standard alternatives, and on identifying settings where some tests may lack clinical relevance.
...
1
2
3
4
5
...