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Predictors of mortality
after colectomy for fulminant Clostridium difficile colitis.
Arch Surg. 2008 Feb; 143(2): 150-4; discussion 155.
OBJECTIVES: To
present, to our knowledge, the largest experience with colectomy for
fulminant Clostridium difficile colitis and to propose factors
significant in predicting mortality. DESIGN: Retrospective medical
record review. SETTING: University teaching hospital. PATIENTS:
Seventy-three patients undergoing colectomy between 1994 and 2005 for
C difficile-associated pseudomembranous colitis. MAIN OUTCOME
MEASURES: Preoperative predictors of in-hospital mortality. RESULTS:
Seventy-three of 5718 cases (1.3%) of C difficile colitis required
colectomy. Mean age was 68 years. In-hospital mortality was 34% (n =
25). Eighty-six percent (n = 63) of patients received a subtotal
colectomy. Patients presented with diarrhea (84%; n = 61), abdominal
pain (75%; n = 55), and ileus (16%; n = 12). Mean duration of symptoms
was 7 days followed by 4 days of medical treatment prior to colectomy.
On univariate analysis, an admitting diagnosis other than C difficile
(P = .049), vasopressor requirement (P = .001), intubation (P = .001),
and mental status changes (P < .001) were significant predictors of
mortality. Arterial lactate level (4.9 vs 2.4 mmol/L; P = .007) was
significantly higher and length of medical management (6.4 vs 3.0
days; P = .006) was significantly longer in the mortality group.
Platelet counts (169 x 10(3)/microL vs 261 x 10(3)/microL [to convert
to x 10(9)/L, multiply by 1]; P = .04) were significantly lower in the
mortality group. On multivariate analysis, vasopressor requirement (P
= .04; odds ratio, 5.0), mental status changes (P = .002; odds ratio,
12.6), and
treatment length (P = .002; odds ratio, 1.4) remained significant
predictors of mortality. CONCLUSIONS: Colectomy for C difficile
colitis carries a substantial mortality regardless of patient age and
white blood cell count. Preoperative vasopressor requirement, mental
status changes, and length of medical treatment significantly predict
mortality. |