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At least 235 records · Page 13Linked to original sources
PubMed1995

Predicting future functional status for seriously ill hospitalized adults. The SUPPORT prognostic model.

OBJECTIVE: To develop a model estimating the probability of an adult patient having severe functional limitations 2 months after being hospitalized with one of nine serious illnesses. DESIGN: Prospective cohort study. SETTING: Five teaching hospitals in the United States. PARTICIPANTS: 1746 patients (model development) who survived 2 months and completed an interview, selected from 4301 patients in the Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments (SUPPORT); independent validation sample of 2478 patients. MEASUREMENTS AND MAIN OUTCOMES: Patient function 2 months after admission categorized as absence or presence of severe functional limitations (defined as Sickness Impact Profile scores > or = 30 or as activities of daily living scores > or = 4 [levels that require near-constant personal assistance]). A logistic regression model was constructed to predict severe functional limitation. RESULTS: One third (n = 590) of patients who were interviewed at 2 months had severe functional limitations. Changes in functional status were common: Of those with no baseline dependencies (not dependent on personal assistance), 21% were severely limited at 2 months; of those with 4 or more baseline limitations, 30% had improved. The patient's ability to do activities of daily living was the most important predictor of functional status. Physiologic abnormalities, diagnosis, days in hospital, age, quality of life, and previous exercise capacity also contributed substantially. Model performance, assessed using receiver-operating characteristic curves, was 0.79 for the development sample and 0.75 for the validation sample. The model was well calibrated for the entire risk range. CONCLUSIONS: Functional outcome varied substantially after hospitalization for a serious illness. A small amount of readily available clinical information can estimate the probability of severe functional limitations.

Activities of Daily Living↗
PubMed2003

A prognostic model for temporal courses that combines temporal abstraction and case-based reasoning.

Since clinical management of patients and clinical research are essentially time-oriented endeavours, reasoning about time has recently become a hot topic in medical informatics. Here we present a method for prognosis of temporal courses, which combines temporal abstractions with Case-based Reasoning. We have applied our method in two programs. The first one deals with multiparametric time course prognosis of the kidney function. The intention of the second program is to compute early warnings against approaching infectious diseases like influenza.

Disease Progression↗
PubMed1981

A prognostic model for clinical stage I melanoma of the lower extremity. Location on foot as independent risk factor for recurrent disease.

Thirteen variables were studied to determine their usefulness in predicting recurrent disease in 158 patients with stage I melanoma of the lower extremity. A Cox proportional hazards analysis demonstrated that three variables were independent risk factors for recurrent disease in these patients: (1) thickness, in millimeters, of the primary tumor (P = 0.000009), (2) primary tumor location on the foot (P = 0.0003), and (3) the number of mitoses/mm2 (P = 0.0244). Life-table analyses of patient subgroups defined by different combinations of these three variables demonstrated that thick (greater than or equal to 3.0 mm) melanomas of the foot were associated with recurrent disease much more frequently than tumors of similar thickness located on the thigh or calf. These data provide guidelines that can be used to evaluate results of surgical and/or adjuvant therapy studies for patients with melanoma of the lower extremity.

Foot Diseases↗
PubMed1995

A prognostic model of recurrence and death in stage I non-small cell lung cancer utilizing presentation, histopathology, and oncoprotein expression.

In order to construct a multivariate model for predicting early recurrence and cancer death for patients with stage I non-small cell lung cancer, 271 consecutive patients (mean age, 63 +/- 8 years) who were diagnosed, treated, and followed at one institution were studied. All patients were clinical stage I with head and chest/abdominal computed tomograms and radionuclide bone scans without evidence of metastatic disease. Pathological material after resection was reviewed to verify histological staging. Follow-up documented the time and location of any recurrence, was a median 56 months in duration, and was complete in all cases. Data recorded included age, sex, smoking history, presenting symptoms, pathological description, and oncoprotein staining for erbB-2 (HER-2/neu), p53, and KI-67 proliferation protein. Immunohistochemistry of oncogene expression was performed on two separate archived paraffin tumor blocks for each patient, with normal lung as control. All analyses were blinded and included Kaplan-Meier survival estimates with Cox proportional hazards regression modeling. Data, including immunohistochemistry, were complete for all 271 patients. Actual 5-year survival was 63% and actuarial 10-year survival was 58%. Significant univariate predictors (P < 0.05) of early recurrence and cancer-death were: male sex; the presence of symptoms; chest pain; type of cough; hemoptysis; tumor size > 3 cm diameter (T2); poor differentiation; vascular invasion; erbB-2 expression; p53 expression; and a higher KI-67 proliferation index (> 5%). An additive oncogene expression curve demonstrated a 5-year survival of 72% for 136 patients without p53 or erbB-2, 58% for 108 patients who expressed either oncogene, and 38% for 27 who expressed both (P < 0.001).(ABSTRACT TRUNCATED AT 250 WORDS)

Aged↗