More Accurate Risk Classification

More accurate risk assessment of Lower Respiratory Tract Infections

Optimize patient admission and site of treatment

Combining MR-proADM with current clinical risk assessment scores offers an easy to use algorithm for more precise risk management and greater confidence in site of care assignment. Defined cut-off values, in combination with existing CURB-65 scores, help better align patients into three defined risk categories, which can optimize decisions upon hospital admission and throughout the emergency department10, 20, as well as support the early discharge of low risk patients. Thus, unnecessary clinical complications and healthcare resource consumption are minimised10.

Algorithm for applying MR-proADM cut-off valuesAlgorithm for applying MR-proADM cut-off values to the clinical risk assessment of LRTI patients (adapted from Albrich et al. 20119, 10)

 

MR-proADM: More accurate patient risk classification

CURB-65 scores are grouped into low (0-1 points), intermediate (2 points) and high risk (3-5 points) categories and combined with MR-proADM cut-offs.

Data from 1359 patients with presumed LRTI (the observational OPTIMA I trial) was collected over six Swiss hospitals and analyzed in order to assess the association between levels of MR-proADM, the risk of adverse events and, ultimately, mortality9. A composite score was created by combining CURB-65 classes with MR-proADM cut-offs to give a CURB65-A score, in order to more accurately risk-stratify patients. Accordingly, the study made the following observations when risk assessment scores were combined with MR-proADM:

 

Enhanced safety of all out-patients

Enhanced safety of all out-patients

Of the 10.4 % (n=142) of patients that were originally classified as out-patients using CURB-65 alone, 38 % (n=54) should have actually been hospitalized (11.2 % as high risk, 26.7 % as intermediate risk), thus highlighting an increased risk to patient safety in the absence of the MR-proADM algorithm.

Decreased hospital admissions

Decreased hospital admissions

Of the 89.6 % (n=1217) of in-patients classified by CURB-65 alone, 17.9 % (n=218) could have been reclassified as out-patients if the CURB-65 score had been combined with MR-proADM. The financial implications of this for healthcare providers cannot be overstated. In the US, 2009 financial data for in-patient CAP treatment was shown to cost over 30 times more than that of out-patient treatment ($36,139 vs $1091)21.

 

MR-proADM: Safely increase out-patient numbers and decrease medical overruling

Increased out-patient numbers

Increased out-patient numbers

Using only CURB-65, 89.6 % of patients (n=1217) were treated as in-patients, and 10.4 % (n=142) treated as out-patients. After the combination of CURB-65 scores with MR-proADM, the number of out-patients increased to 22.5 % (n=306).

Increased out-patient numbers in an interventional trial

Increased out-patient numbers in an interventional trial

OPTIMA II was the first interventional study to evaluate the feasibility of adding MR-proADM to the CURB-65 score with regards to risk stratification22. A total of 313 patients with LRTI were enrolled over 3 centers, and the number of individuals considered for out-patient care was shown to more than double up to 19 % in the MR-proADM algorithm group, compared to 8.7 % in the OPTIMA I control group.

Decreased patient overruling

Decreased patient overruling

Mainly based on medical criteria (90.2 %), overruling occurred in 50.9 % of patients in the OPTIMA II control group after hospital admission, however, in the MR-proADM group the algorithm was overruled in only 27.4 % of patients on initial presentation (p < 0.001), thus giving physicians a greater degree of confidence in their overall disposition decision.

 

Benefits of out-patient treatment include:

Benefits of out-patient treatment include: Reduction in the risk of associated healthcare infections and nosocomial complications; Greater availability of in demand resources, such as ED and ICU beds and physician time; Reduced financial costs compared to in-patient treatment; Increased patient satisfaction and comfort

 

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