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J Am Geriatr Soc ; 60(9): 1609-15, 2012 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-22906222

RESUMO

OBJECTIVES: To determine whether readily collected perioperative information might identify older surgical patients at higher risk of complications. DESIGN: Retrospective cohort study. SETTING: Medical chart review at a single academic institution. PARTICIPANTS: One hundred two individuals aged 65 and older who underwent abdominal surgery between January 2007 and December 2009. MEASUREMENTS: Primary predictor variables were first postoperative Braden Scale score (within 24 hours of surgery) and a Deficit Accumulation Index (DAI) constructed based on 39 available preoperative variables. The primary outcome was presence or absence of complication within 30 days of surgery. RESULTS: Of 102 patients, 64 experienced at least one complication, with wound infection being the most common. In models adjusted for age, race, sex, and open versus laparoscopic surgery, lower Braden Scale scores were predictive of 30-day postoperative complication (odds ratio (OR) = 1.30, 95% confidence interval (CI) = 1.06-1.60), longer length of stay (ß = 1.44 (0.25) days; P ≤ .001), and discharge to an institution rather than home (OR = 1.23, 95% CI = 1.02-1.48). The cut-off value for the Braden score with the highest predictive value for complication was ≤ 18 (OR = 3.63, 95% CI = 1.43-9.19; c statistic 0.744). The DAI and several traditional surgical risk factors were not significantly associated with 30-day postoperative complications. CONCLUSION: This is the first study to identify the perioperative Braden Scale score, a widely used risk-stratifier for pressure ulcers, as an independent predictor of other adverse outcomes in geriatric surgical patients. Further studies are needed to confirm this finding and to investigate other uses for this tool, which correlates well to phenotypic models of frailty.


Assuntos
Complicações Pós-Operatórias/epidemiologia , Índice de Gravidade de Doença , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Tempo de Internação/estatística & dados numéricos , Modelos Logísticos , Masculino , North Carolina/epidemiologia , Valor Preditivo dos Testes , Curva ROC , Estudos Retrospectivos , Medição de Risco , Fatores de Risco
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