Browsing by Subject "COMA"

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  • EPO-TBI Investigators Anzics Clin; Skrifvars, Markus B. (2019)
    Background Acute kidney injury (AKI) in traumatic brain injury (TBI) is poorly understood and it is unknown if it can be attenuated using erythropoietin (EPO). Methods Pre-planned analysis of patients included in the EPO-TBI ( NCT00987454) trial who were randomized to weekly EPO (40 000 units) or placebo (0.9% sodium chloride) subcutaneously up to three doses or until intensive care unit (ICU) discharge. Creatinine levels and urinary output (up to 7 days) were categorized according to the Kidney Disease Improving Global Outcome (KDIGO) classification. Severity of TBI was categorized with the International Mission for Prognosis and Analysis of Clinical Trials in TBI. Results Of 3348 screened patients, 606 were randomized and 603 were analyzed. Of these, 82 (14%) patients developed AKI according to KDIGO (60 [10%] with KDIGO 1, 11 [2%] patients with KDIGO 2, and 11 [2%] patients with KDIGO 3). Male gender (hazard ratio [HR] 4.0 95% confidence interval [CI] 1.4-11.2, P = 0.008) and severity of TBI (HR 1.3 95% CI 1.1-1.4, P <0.001 for each 10% increase in risk of poor 6 month outcome) predicted time to AKI. KDIGO stage 1 (HR 8.8 95% CI 4.5-17, P <0.001), KDIGO stage 2 (HR 13.2 95% CI 3.9-45.2, P <0.001) and KDIGO stage 3 (HR 11.7 95% CI 3.5-39.7, P <0.005) predicted time to mortality. EPO did not influence time to AKI (HR 1.08 95% CI 0.7-1.67, P = 0.73) or creatinine levels during ICU stay (P = 0.09). Conclusions Acute kidney injury is more common in male patients and those with severe compared to moderate TBI and appears associated with worse outcome. EPO does not prevent AKI after TBI.
  • Raj, Rahul; Luostarinen, Teemu; Pursiainen, Eetu; Posti, Jussi P.; Takala, Riikka S. K.; Bendel, Stepani; Konttila, Teijo; Korja, Miikka (2019)
    Our aim was to create simple and largely scalable machine learning-based algorithms that could predict mortality in a real-time fashion during intensive care after traumatic brain injury. We performed an observational multicenter study including adult TBI patients that were monitored for intracranial pressure (ICP) for at least 24 h in three ICUs. We used machine learning-based logistic regression modeling to create two algorithms (based on ICP, mean arterial pressure [MAP], cerebral perfusion pressure [CPP] and Glasgow Coma Scale [GCS]) to predict 30-day mortality. We used a stratified crossvalidation technique for internal validation. Of 472 included patients, 92 patients (19%) died within 30 days. Following cross-validation, the ICP-MAP-CPP algorithm's area under the receiver operating characteristic curve (AUC) increased from 0.67 (95% confidence interval [CI] 0.60-0.74) on day 1 to 0.81 (95% CI 0.75-0.87) on day 5. The ICP-MAP-CPP-GCS algorithm's AUC increased from 0.72 (95% CI 0.64-0.78) on day 1 to 0.84 (95% CI 0.78-0.90) on day 5. Algorithm misclassification was seen among patients undergoing decompressive craniectomy. In conclusion, we present a new concept of dynamic prognostication for patients with TBI treated in the ICU. Our simple algorithms, based on only three and four main variables, discriminated between survivors and non-survivors with accuracies up to 81% and 84%. These open-sourced simple algorithms can likely be further developed, also in low and middleincome countries.
  • Raj, Rahul; Mikkonen, Era D.; Kivisaari, Riku; Skrifvars, Markus B.; Korja, Miikka; Siironen, Jari (2016)
    BACKGROUND: Surgery for elderly patients with acute subdural hematomas (ASDH) is controversial, because postoperative mortality rates are reported to be high and long-term outcomes unknown. Thus, we aimed to describe midterm and long-term mortality rates of elderly patients operated for an ASDH. METHODS: We reviewed all consecutive >= 75-year-old patients operated on for an ASDH between 2009 and 2012. We recorded data on preadmission functional status (independent or dependent) and use of antithrombotic medication. Patients were followed up a median of 4.2 years (range, 2.5-6.4 years). RESULTS: Forty-four patients were included. The majority of the patients (70%) were independent and taking antithrombotic medication (77%). Independent patients had a 1-year mortality of 42%, compared to 69% for dependent patients; 56% of patients taking antithrombotics and 30% of those without antithrombotics died within the first postoperative year. All patients with an admission Glasgow coma scale score of 3-8 died within the first postoperative year, if they used antithrombotics or were dependent before the injury. Of all 1-year survivors, 77% were alive at the end of follow-up. CONCLUSION: In this first surgical case series of 75-year-old or older patients with ASDH, the overall mortality rate appears to be relatively low, especially for preoperatively conscious and independent patients without antithrombotic medication. Patients alive at 1-year after surgery had a life expectancy comparable to their age-matched peers. The prognosis seems to be detrimental for preoperatively unconscious patients who were functionally dependent or used antithrombotic medication before the injury.