Essay On Neonatal Sepsis

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Logistic regression is used to analyze a variety of variables that may involve a particular outcome. It also uses a maximum likelihood estimate to analyze the relationship between independent and dependent variables. Logistic regression is used in health care to help with diagnoses, predictions, and predicting. Polit, D. (2010).
Xiao, Griffin, Lake, & Moorman, (2010). used the methods nearest-neighbor and logistic regression analysis to make the early diagnosis of neonatal sepsis using continuous physiological monitoring of heart rate characteristics, and intermittent measurements of laboratory values. They used two different methods to analyze the variable of clinical and heart rate characteristics in the early diagnosis of neonatal sepsis. …show more content…

Neonatal sepsis seems to be a clinical problem when using the nearest-neighbor analysis to come up with predictive models. These infants are continuously monitored with frequent lab testing. since there is no single test that is highly predictive, there is always uncertainty about the diagnosis by physicians until the presence of signs of severe illness. Combining nearest-neighbor and logistic regression is great because there are both linear and nonlinear associations. Logistic regression may have superior performance in handling the linear processes and nearest-neighbor may be more effective in treating the nonlinear components. The challenge is ideal when handling continuous and intermittent data with unequal magnitude and variation, and unknown correlations. It was found that, Both the nearest-neighbor and regression models using heart rate characteristics and available laboratory test results were significantly associated with imminent sepsis, and each kind of model added independent information to the other. The best predictive strategy is to use both models. Xiao, Griffin, Lake, & Moorman, (2010). propose that the nearest-neighbor analysis in addition to regression in the early diagnosis of subacute, potentially catastrophic illnesses such as neonatal sepsis, and they recommend it as an approach to the general problem of predicting a clinical event from a multivariable data

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