Background. This study evaluated whether large venous-arterial CO(2) gap (PCO(2) gap) preoperatively is associated to poor outcome. Method. Prospective study which included adult high-risk surgical patients. The patients were pooled into two groups: wide [P(v-a)CO(2)] versus narrow [P(v-a)CO(2)]. In order to determine the best value to discriminate hospital mortality, it was applied a ROC (receiver operating characteristic) curve for the [P(v-a)CO(2)] values collected preoperatively, and the most accurate value was chosen as cut-off to define the groups. Results. The study included 66 patients. The [P(v-a)CO(2)] value preoperatively that best discriminated hospital mortality was 5.0 mmHg, area = 0.73. Preoperative patients with [P(v-a)CO(2)] more than 5.0 mmHg presented a higher hospital mortality (36.4% versus 4.5% P = 0.004), higher prevalence of circulatory shock (56.8% versus 22.7% P = 0.01) and acute renal failure postoperatively (27.3% versus 4.5% P = 0.02), and longer hospital length of stays 20.0 (14.0-30.0) versus 13.5 (9.0-25.0) days P = 0.01. Conclusions. The PCO(2) gap values more than 5.0 mmHg preoperatively were associated with worse postoperatively outcome.
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http://dx.doi.org/10.1155/2011/759792 | DOI Listing |
J Telemed Telecare
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Division of Hospital Internal Medicine, Mayo Clinic, Rochester, MN, USA.
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Afr J Prim Health Care Fam Med
December 2024
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View Article and Find Full Text PDFTherap Adv Gastroenterol
January 2025
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Background: Alkaline phosphatase (ALP) is a potential cancer biomarker. However, its prognostic value in patients with colorectal liver metastasis remains unclear.
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Eur Heart J Digit Health
January 2025
Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, USA.
Aims: Accurate prediction of clinical outcomes following percutaneous coronary intervention (PCI) is essential for mitigating risk and peri-procedural planning. Traditional risk models have demonstrated a modest predictive value. Machine learning (ML) models offer an alternative risk stratification that may provide improved predictive accuracy.
View Article and Find Full Text PDFBackground And Aims: Hematopoietic stem cell transplantation (HSCT) is a key therapeutic approach for pediatric patients with hematologic and non-hematologic disorders. However, post-transplant pulmonary complications remain a significant cause of morbidity and mortality. Pulmonary Function Tests (PFTs) are essential for the early detection of pulmonary dysfunction, yet their application in pediatric HSCT recipients has yielded inconsistent results.
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