The publication data currently available has been vetted by Vanderbilt faculty, staff, administrators and trainees. The data itself is retrieved directly from NCBI's PubMed and is automatically updated on a weekly basis to ensure accuracy and completeness.
If you have any questions or comments, please contact us.
OBJECTIVE - To develop and validate a simple prognostic scoring system to identify patients in nontraumatic coma at high risk for poor outcomes using data available early in the hospital course.
DESIGN - Prospective cohort study.
SETTING - Five geographically diverse academic medical centers.
PATIENTS - A total of 596 patients in nontraumatic coma enrolled in the Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments (SUPPORT), including 247 in the model derivation set and 349 in the model validation set.
MAIN OUTCOME MEASURES - Death and severe disability by 2 months.
MAIN RESULTS - For the 596 patients studied (median age, 67 years; 52% female), the primary cause of coma was cardiac arrest in 31% and cerebral infarction or intracerebral hemorrhage in 36%. At 2 months 69% had died, 20% had survived with known severe disability, 8% were known to have survived without severe disability, and 3% survived with unknown functional status. Five clinical variables available on day 3 after enrollment were associated independently with 2-month mortality: abnormal brain stem response (adjusted odds ratio [OR] = 3.2; 95% confidence interval [CI], 1.3 to 8.1), absent verbal response (OR = 4.6; 95% CI, 1.8 to 11.7), absent withdrawal response to pain (OR = 4.3; 95% CI, 1.7 to 10.8), creatinine level greater than or equal to 132.6 mumol/L (1.5 mg/dL) (OR = 4.5; 95% CI, 1.8 to 11.0), and age of 70 years or older (OR = 5.1; 95% CI, 2.2 to 12.2). Mortality at 2 months for patients with four or five of these risk factors was 97% (58/60; 95% CI, 88% to 100%) in the validation set. Brain stem and motor responses best predicted death or severe disability by 2 months. For patients with either an abnormal brain stem response or absent motor response to pain, the rate of death or severe disability at 2 months was 96% (185/193; 95% CI, 92% to 98%) in the validation set.
CONCLUSIONS - Five readily available clinical variables identify a large subgroup of patients in nontraumatic coma at high risk for poor outcomes. This risk stratification approach offers physicians, patients, and patients' families information that may prove useful in patient care decisions and resource allocation.
We analyzed data from the records of 422 patients with acute bacterial or viral meningitis. A cerebrospinal fluid (CSF) glucose level less than 1.9 mmol/L, a CSF-blood glucose ratio less than 0.23, a CSF protein level greater than 2.2 g/L, more than 2000 x 10(6)/L CSF leukocytes, or more than 1180 x 10(6)/L CSF polymorphonuclear leukocytes were individual predictors of bacterial infection with 99% certainty or better. Although any one of these tests could rule in bacterial meningitis with high probability, none could rule it out. To better predict whether a patient has bacterial vs viral infection, we developed a logistic multiple regression model using CSF-blood glucose ratio, total polymorphonuclear leukocyte count in CSF, age, and month of onset. This proved highly reliable when validated in an independent test sample, with an area under receiver operating characteristic curve of 0.97. The model should allow physicians to differentiate between acute viral and acute bacterial meningitis with greater accuracy.
To determine if the risk of hip fracture difference between persons receiving benzodiazepines with long (greater than or equal to 24 hours) or short (less than 24 hours) elimination half-lives, we conducted a nested case-control study among residents of the Canadian province of Saskatchewan who were 65 years of age and older. We identified 4501 cases occurring between 1977 and 1985 from computerized hospital records and 24,041 population controls. Current benzodiazepine use, defined as having filled a prescription in the past 30 days, was ascertained from computerized pharmacy records. The relative risk of hip fracture was 1.7 (95% confidence interval, 1.5 to 2.0) for current users of long half-life benzodiazepines, in contrast to that of 1.1 (95% confidence interval, 0.9 to 1.3) for current users of short half-life drugs. This finding was not altered by sex, age, calendar year, nursing home residence, or history of hospitalization. Medical record review for a sample of 189 cases suggested that this finding was not due to confounding by dementia, ambulatory status, functional status, or body mass.
Exposure to certain environmental agents may induce a scleroderma-like syndrome in a small proportion of individuals. Differences in susceptibility could involve metabolic activation of a protoxin, with affected patients having a greater converting ability. This possibility was investigated in 84 patients with scleroderma and 108 control subjects with in vivo probes of specific pathways of metabolism. Scleroderma was associated with reduced hydroxylating activity for dapsone and S-mephenytoin, whereas the ability to hydroxylate debrisoquin and N-acetyl dapsone was similar in both groups. Logistic regression confirmed these associations based on the shift in frequency distribution. Individuals who were poor metabolizers for mephenytoin and only modest N-hydroxylators of dapsone had a tenfold increased risk of scleroderma (p = 0.008). Thus this combined metabolic impairment may be causally involved in the development of scleroderma or, alternatively, the disease may produce inhibition of selected metabolizing enzymes in a subset of patients.
The utility of ordinal logistic regression in the prediction of colorectal neoplasia was demonstrated in a group of 461 consecutive patients undergoing colonoscopy in a community practice. One hundred twenty-nine patients had adenomatous polyps and 34 had colorectal adenocarcinoma. An ordinal logistic regression model developed in a random subset (292 patients) identified five predictors of colorectal neoplasia. Colorectal neoplasia risk could be predicted using the patient's age, sex, hematocrit, fecal occult blood test result and indication for colonoscopy. The risk of colorectal neoplasia in the remaining subset of patients (169) could be reliably estimated from the model. Ordinal logistic regression analysis in this select group of patients can accurately estimate the likelihood of colorectal neoplasia. Because the generalizability of our findings are unknown, the model should not be applied to other patients. However, application of this technique to an unselected group of patients not already referred for colonoscopy could provide unbiased estimates of colorectal neoplasia risk in individual patients.