Purpose: The aim of this study was to assess mortality in healthy elderly patients after non-elective medical ICU admission and to identify predictive factors of mortality in these patients.
Methods: Patients >or=65 years living at home and with full-autonomy (Barthel index, BI > 60), without cognitive impairment, and non-electively admitted to a medical ICU were prospectively recruited. A full comprehensive geriatric assessment was made with validated scales.
Results: A total of 230 patients were included, 110 (48%) between 65 and 74 years and 120 (52%) >or=75 years. No significant differences were observed between the two groups in premorbid functional and cognitive status, main diagnosis at ICU admission, APACHE II and SOFA scores, use of mechanical ventilation or haemodialysis or length of ICU stay. Over a mean follow-up of 522 days (range 20-1,170 days) the cumulative mortality of the whole group was 55%, being significantly higher in older subjects (62 vs. 47%; P = 0.024). On multivariate analysis, only parameters related to quality of life (QOL) and functional status were independent predictors of cumulated mortality (P < 0.01, both). Thus, in patients with EQ-5D(vas) (<70) or baseline Lawton index (LI) (<5) the hazard ratio for cumulated mortality was 2.45 (95% CI: 1.15-5.25; P = 0.03) and 4.10 (95% CI: 1.53-10.99; P = 0.006), respectively, compared to those with better scores.
Conclusions: Healthy elderly non-elective medical patients admitted to the ICU have a high mortality rate related to premorbid QOL. The LI and/or EQ-5D(vas) may be useful tools to identify patients with the best chance of survival.
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http://dx.doi.org/10.1007/s00134-008-1345-8 | DOI Listing |
Int Urol Nephrol
January 2025
Institute of Urology, Gansu Province Clinical Research Center for Urinary System Disease, The Second Hospital and Clinical Medical School, Lanzhou University, No. 82 Cuiyingmen, Chengguan District, Lanzhou, Gansu, China.
Purpose: To evaluate the impact of maximal transurethral resection of bladder tumor (TURBT) on perioperative outcomes following radical cystectomy (RC).
Methods: This study included 310 patients who underwent RC for the diagnosis of bladder urothelial carcinoma. Of these, 146 patients had a history of maximal TURBT (TURBT group) and 164 did not (non-TURBT group).
Pediatr Crit Care Med
January 2025
Division of Medical Critical Care, Department of Pediatrics, Boston Children's Hospital, Boston, MA.
Objectives: To assess factors associated with serum phosphorus (P) and hypophosphatemia in children with type 1 diabetes mellitus (T1DM) treated for diabetic ketoacidosis (DKA).
Design: Retrospective cohort.
Setting: Community-based PICU in a university-affiliated hospital.
Pediatr Crit Care Med
January 2025
Center for Iron Disorders, Department of Medicine, UCLA, Los Angeles, CA.
Objectives: The primary objective was to determine iron deficiency (ID) anemia (IDA) monitoring practices in children during PICU stay. A secondary objective was to determine the current follow-up practices for IDA after PICU discharge.
Design: Retrospective observational study of 2 years (2021-2022).
Pediatr Crit Care Med
January 2025
Department of Pediatrics, Division of Critical Care Medicine, Children's National Hospital and The George Washington University School of Medicine and Health Sciences, Washington, DC.
Objectives: To examine the relationship between adequacy of caloric nutritional support during the first week after severe traumatic brain injury (TBI) and outcome.
Design: Single-center retrospective cohort, 2010-2022.
Setting: Tertiary care children's hospital with a level 1 trauma center.
Infect Control Hosp Epidemiol
January 2025
One Health Trust, Washington, D.C., USA.
Background: Clinical trials for assessing the effects of infection prevention and control (IPC) interventions are expensive and have shown mixed results. Mathematical models can be relatively inexpensive tools for evaluating the potential of interventions. However, capturing nuances between institutions and in patient populations have adversely affected the power of computational models of nosocomial transmission.
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