Tools & Strategies News

Risk Scores Predict Patients Likely to Develop Multiple Infections

Risk scores could help providers detect trauma patients who are highly susceptible to developing multiple infections while in the hospital.

Risk scores predict patients likely to develop multiple infections

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By Jessica Kent

- Certain risk scores already used to evaluate the severity of a trauma patient’s condition can also help providers determine which patients are highly likely to develop multiple infections, according to a study published in PLOS One.

Hospital-acquired infections among trauma patients can lead to significantly increased hospital stays, as well as high healthcare costs. Trauma patients are at high risk of developing multiple infections while in the hospital, but it’s challenging to identify individuals who are especially susceptible.

Researchers from Massachusetts General Hospital (MGH) set out to find whether organ dysfunction and trauma severity, assessed by commonly used disease-severity scoring systems, could predict patients susceptible to multiple infections during their hospital stay.

The team analyzed data from 1,665 trauma patients and examined five disease-severity scores – the Denver score, the Marshall score, the Acute Physiology and Chronic Health Evaluation II (APACHE II) score, the Injury Severity Score (ISS), and the New Injury Severity Score (NISS) – as predictors of susceptibility to multiple independent infectious episodes (MIIEs).

These scores differ in the way they assess a patient’s condition by measuring physiologic responses or injury patterns, researchers noted.

The results showed that the Denver and Marshall scores can accurately predict susceptibility to multiple independent infections after trauma, even when the scores are determined much earlier than any clinical sign of infection. Both the Denver and Marshall scores are typically used to assess the severity of organ failure in the setting of traumatic injury.

This study demonstrates that the Denver and Marshall tools could be instrumental in predicting the predisposition of trauma patients to multiple infections, even before individuals develop any clinical signs of infection.

“Our findings could potentially facilitate clinical decision-making by identifying patients who are at higher risk of suffering multiple infections during their hospital stay,” said senior author Laurence G. Rahme, PhD, Director of the MGH Molecular Surgical Laboratory, Professor of Surgery and Microbiology at Harvard Medical School, and senior scientific staff at Shriners Hospital for Children.

The healthcare industry currently lacks a predictive tool that can evaluate trauma patients’ risk of developing multiple infections, researchers stated.

“Previous studies investigating the potential of trauma assessment scoring systems to identify patients at increased risk of post-traumatic hospital-acquired infections mainly focused on scores such as APACHE II, ISS and NISS,” the group said.

“Past research found that APACHE II and ISS did not successfully predict the incidence of infections in trauma patients. Additionally, research has shown that ISS failed to distinguish between trauma patients with and without infections. These results are in accordance with our findings. Those studies were somewhat limited by their relatively low sample size, as well as by their monocentric nature.”

The current study indicates that patients’ physiologic response to injury is a better predictor of infection. This discovery could lead to more proactive care, researchers stated.      

“Our finding that physiology-based disease-severity scores (i.e., Denver and Marshall), rather than anatomy-based trauma-severity scores (i.e., ISS and NISS) can successfully predict the increased post-traumatic predisposition to MIIEs, conceivably suggests that the post-traumatic susceptibility to MIIEs correlates better with the individual physiologic response to injury, rather than the anatomical severity of the trauma,” the team said.

The findings could also lead to more personalized care plans, which could be cost-saving because it would limit interventions to only those patients most likely to develop infections. Personalized care plans would also help clinicians prevent hospital-acquired infections that can lead to prolonged hospital stays.

“Early prognosis, before infections occur, could strategically guide the timing and duration of antibiotic administration to these patients," said Rahme, who is also an MGH Research Scholar 2020-2025.

"It would also allow physicians to implement prophylactic measures, enhance patient nutrition, and formulate potent personalized treatment plans for this group of patients, thus protecting those at higher risk of repeated infections during their recovery period.”