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Detailed paper information
| Paper title | Early Quantitative Pupillometry Index (QPi) as a Predictor of Long-Term Outcome in Severe Traumatic Brain Injury Patients: A Prospective Observational Study |
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| Paper code | A02 |
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| Form of presentation | Oral abstract presentation |
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| Abstract text |
Background Automated infrared pupillometry provides reliable, objective, and quantitative data on pupillary function, including numerical indices that grade PLR, such as the Quantitative Pupillometry Index (QPi). This study aims to examine the link between abnormal QPi and neurological outcomes (GOSE), as well as QPi's ability to predict outcomes in severe TBI (sTBI) patients. Message This single-center, prospective, observational study included 100 adult patients with sTBI (GCS ≤ 8) admitted to the Neurocritical Care Unit within 48 hours of injury. Automated pupillometry was performed at 0, 12, 24, 48, and 72 hours, with QPi recorded (0-5). A QPi < 3 was considered abnormal. Patients were followed up via telephone at 6 months to evaluate neurological outcomes using the extended Glasgow Outcome Scale (GOSE). Impact on patient care A total of 980 QPi readings were collected, with 445 (45%) being abnormal. Sixty-five (67%) patients experienced a poor neurological outcome (GOSE ≤ 4), and 36 (37%) of them died. The median QPi was significantly associated with poor neurological outcome (adjusted OR, 1.80; 95% CI, 1.04-6.66; p = 0.04) and mortality (adjusted OR, 4.15; 95% CI, 1.50-11.49; p = 0.006). QPi readings on Days 2 and 3 independently predicted poor neurological outcome [OR 2.88 (1.04 -7.94), p = 0.04 and OR 3.21 (1.14 - 9.03), p = 0.027, respectively]. We conclude that median QPi was significantly associated with poor neurological outcomes and mortality. Median QPi over three days of admission, as well as QPi on days 2 and 3, were independent predictors of poor neurological outcomes and mortality. Median QPi, along with Day-2 and Day-3 QPi, can serve as prognostic markers in sTBI and should be included as factors in prognostic models for sTBI. |