PubMed Health⌕ Search

Biomedical subjects

W Knaus

Publications and source records attributed to W Knaus.

At least 19 recordsLinked to original sources
PubMed2001

[Severity assessment by APACHE III system in Spain].

BACKGROUND: To assess the performance of the prediction equation of the APACHE(Acute Physiology Age and Chronic Health Evaluation) III prognostic scoring system when applied in Spain. PATIENTS AND METHOD: Prospective multicenter cohort study that included 10786 adult patients from 86 Spanish intensive care units (ICU). Data collection during first 24 hours of admission: acute physiology score, age and comorbilties,for calculating APACHE III score; treatment location prior to ICU admission and main diagnosis admission category for applying the mortality prediction equation of APACHE III system. Main outcome was observed hospital mortality. RESULTS: Age was 57.74 (0.16); 68% males. Non-operative patients represented 76% of sample. APACHE III score was 53.75(0.26); observed and predicted hospital mortality were 21.2% and 19.8% respectively, with a standardized mortality ration of 1.07. The Chi2 Hosmer-Lemershow statistic was (H) 135.6, (C) 133.91: p < 0.001. The area under the Receiver Operating Curve (ROC) was 0.808, and correct classification at mortality risk of 50% was 82%. Uniformity of fit was better for non-operative diagnoses and for patients admitted from the emergency area. Calibration was excellent for risk lower than 60% but slightly underestimated observed risks above this level. CONCLUSIONS: The American APACHE III equation fit well when applied to Spanish critical patients but with limitations. Discrepancies could be attributed to differences in case-mix and variations in practice style.

APACHE↗
PubMed2000

Prediction of survival for older hospitalized patients: the HELP survival model. Hospitalized Elderly Longitudinal Project.

OBJECTIVE: To develop and validate a model estimating the survival time of hospitalized persons aged 80 years and older. DESIGN: A prospective cohort study with mortality follow-up using the National Death Index. SETTING: Four teaching hospitals in the US. PARTICIPANTS: Hospitalized patients enrolled between January 1993 and November 1994 in the Hospitalized Elderly Longitudinal Project (HELP). Patients were excluded if their length of hospital stay was 48 hours or less or if admitted electively for planned surgery. MEASUREMENTS: A log-normal model of survival time up to 711 days was developed with the following variables: patient demographics, disease category, nursing home residence, severity of physiologic imbalance, chart documentation of weight loss, current quality of life, exercise capacity, and functional status. We assessed whether model accuracy could be improved by including symptoms of depression or history of recent fall, serum albumin, physician's subjective estimate of prognosis, and physician and patient preferences for general approach to care. RESULTS: A total of 1266 patients were enrolled over a 10-month period, (median age 84.9, 61% female, 68% with one or more dependency), and 505 (40%) died during an average follow-up of more than 2 years. Important prognostic factors included the Acute Physiology Score of APACHE III collected on the third hospital day, modified Glasgow coma score, major diagnosis (ICU categories together, congestive heart failure, cancer, orthopedic, and all other), age, activities of daily living, exercise capacity, chart documentation of weight loss, and global quality of life. The Somers' Dxy for a model including these factors was 0.48 (equivalent to a receiver-operator curve (ROC) area of 0.74, suggesting good discrimination). Bootstrap estimation indicated good model validation (corrected Dxy of 0.46, ROC of 0.73). A nomogram based on this log-normal model is presented to facilitate calculation of median survival time and 10th and 90th percentile of survival time. A count of geriatric syndromes or comorbidities did not add explanatory power to the model, nor did the hospital of patient recruitment, depression, or the patient preferences for general approach to care. The physician's perception of the patient's preferences and the physician's subjective estimate of the patient's prognosis improved the estimate of survival time significantly. CONCLUSIONS: Accurate estimation of length of life for older hospitalized persons may be calculated using a limited amount of clinical information available from the medical chart plus a brief interview with the patient or surrogate. The accuracy of this model can be improved by including measures of the physician's perception of the patient's preferences for care and the physician's subjective estimate of prognosis.

Activities of Daily Living↗
PubMed2000

Family satisfaction with end-of-life care in seriously ill hospitalized adults.

OBJECTIVE: To examine factors associated with family satisfaction with end-of-life care in the Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments (SUPPORT). DESIGN: A prospective cohort study with patients randomized to either usual care or an intervention that included clinical nurse specialists to assist in symptom control and facilitation of communication and decision-making. SETTING: Five teaching hospitals in the United States. PARTICIPANTS: Family members and other surrogate respondents for 767 seriously ill hospitalized adults who died. MEASUREMENTS: Eight questionnaire items regarding satisfaction with the patient's medical care expressed as two scores, one measuring satisfaction with patient comfort and the other measuring satisfaction with communication and decision-making. RESULTS: Sixteen percent of respondents reported dissatisfaction with patient comfort and 30% reported dissatisfaction with communication and decision-making. Factors found to be significantly associated with satisfaction with communication and decision-making were hospital site, whether death occurred during the index hospitalization (adjusted odds ratio (AOR) 2.2, 95% CI, 1.3-3.9), and for patients who died following discharge, whether the patient received the SUPPORT intervention (AOR 2.0, 1.2-3.2). For satisfaction with comfort, male surrogates reported less satisfaction (0.6, 0.4-1.0), surrogates who reported patients' preferences were followed moderately to not at all had less satisfaction (0.2, 0.1-0.4), and surrogates who reported the patient's illness had greater effect on family finances had less satisfaction (0.4, 0.2-0.8). CONCLUSIONS: Satisfaction scores suggest the need for improvement in end-of-life care, especially in communication and decision making. Further research is needed to understand how factors affect satisfaction with end-of-life care. An intervention like that used in SUPPORT may help family members.

Aged↗
PubMed2000

Withholding versus withdrawing life-sustaining treatment: patient factors and documentation associated with dialysis decisions.

OBJECTIVE: We evaluated prospectively the use of acute hemodialysis among hospitalized patients to identify demographic and clinical predictors of and chart documentation concerning dialysis withheld and withdrawn. DESIGN: Prospective cohort study. SETTING: Five teaching hospitals. PATIENTS: Five hundred sixty-five seriously ill hospitalized patients who had not previously undergone dialysis who developed renal failure. MAIN OUTCOME MEASURES: Patient demographics, clinical characteristics, preferences, and prognostic estimates associated with having dialysis withheld rather than initiated and withdrawn rather than continued. Differences in chart documentation concerning decision-making for dialysis withheld, withdrawn, and continued. RESULTS: Older patient age, cancer diagnosis, and male gender were associated with dialysis withheld rather than withdrawn. Age and gender differences persisted after adjustment for patients' aggressiveness of care preference. Worse 2-month prognosis was associated with both withholding and withdrawing dialysis. Chart documentation of decision-making was lacking more often for patients with dialysis withheld than for dialysis withdrawn. CONCLUSIONS: Measuring the equity of life-sustaining treatment use will require evaluation of care withheld, not just care withdrawn. Older patients and men, after accounting for prognosis and function, are more likely to have dialysis withheld than withdrawn after a trial. Further exploration is needed into this disparity and the inadequate chart documentation for patients with dialysis withheld.

APACHE↗
PubMed1998

The Apache III prognostic system: customized mortality predictions for Spanish ICU patients.

OBJECTIVE: To customize the Acute Physiology and Chronic Health Evaluation (APACHE) III mortality equation for Spanish admissions to the intensive care unit (ICU) and evaluate its discrimination and calibration. DESIGN: Prospective multicenter inception cohort study. SETTING: 86 ICUs located in all regions of Spain. PATIENTS: 10,929 adult patients selected by a systematic sampling method. All types of critical care patients were included, including coronary bypass patients, but excluding those with burn injury, those admitted for pacemaker implants, patients under 16 years of age, and patients with length of ICU stay < 6 h. MEASUREMENTS AND RESULTS: Data collection in the first 24 h after patient admission included: APACHE III score, treatment location prior to ICU admission, and main ICU admission diagnosis. Using these variables, a model for predicting hospital mortality was constructed, adapted to Spain, and its discriminating ability was assessed by the area below the ROC curve, which was 0.83. The model was validated using the jacknife method and the area below the receiver operating characteristic (ROC) curve for the cross-validated predictions was 0.82. The percentage of patients correctly classified at 0.50 risk of death was 82.3%. Model calibration was evaluated by analysis of the agreement between the observed and cross-validated predicted mortality using the Hosmer-Lemeshow test, which gave a value of (H) 12.27, with no statistical significance, i.e., good calibration. CONCLUSIONS: We have customized the APACHE III mortality prediction system for the Spanish population. This adapted model has demonstrated the requisite validation, calibration, and discrimination for its use among Spanish critical care patients.

APACHE↗
PubMed1996

Effects of dietary fatty acid pattern on melting point and composition of adipose tissues and intramuscular fat of broiler carcasses.

Soybean oil (SO), rapeseed oil (RO), or two commercial fat products (FP1, FP2) were incorporated at 3.5% levels into four different corn-soybean meal mash broiler diets. Each of the four diets was fed to five replicates (pens) of broiler chickens for 42 d. After slaughtering the birds, samples of the abdominal fat, subcutaneous fat, and fat extracted from the thigh and the breast portion were collected from 16 birds per treatment. The fat samples were analyzed for their fatty acid composition using gas chromatography and the melting point of the abdominal fat was recorded. The results showed that the abdominal and subcutaneous fat had very similar fatty acid patterns and differed significantly from the composition of the fat extracted from breast and thigh. The different dietary treatments caused significant changes in the fatty acid patterns for all analyzed tissues, although the differences were more pronounced for the adipose tissues. Overall, the adipose tissues contained more polyunsaturated and less saturated fatty acids than the fat from the breast and thigh portions. The melting point of the abdominal fat was significantly altered by the use of different dietary fats: RO gave a lower melting point than SO and FP1; the highest values were recorded for FP2. The data presented here indicate that the selection of certain dietary fat sources has a major impact on the composition and the melting point of broiler adipose tissues. The effect on the fatty acid composition of meat portions, however, is limited.

Adipose Tissue↗
PubMedDate not supplied

The covariance decomposition of the probability score and its use in evaluating prognostic estimates. SUPPORT Investigators.

The probability score (PS) or Brier score has been used in a large number of studies in which physician judgment performance was assessed. However, the covariance decomposition of the PS has not previously been used to evaluate medical judgment. The authors introduce the technique and demonstrate it by analyzing prognostic estimates of three groups: physicians, their patients, and the patients' decision-making surrogates. The major components of the covariance decomposition--bias, slope, and scatter--are displayed in covariance graphs for each of the three groups. The decomposition reveals that whereas the physicians have the best overall estimation performance, their bias and their scatter are not always superior to those of the other two groups. This is primarily due to two factors. First, the physicians' prognostic estimates are pessimistic. Second, the patients place the large majority of their estimates in the most optimistic category, thereby achieving low scatter. The authors suggest that the calculational simplicity of this decomposition, its informativeness, and the intuitive nature of its components make it a useful tool with which to analyze medical judgment.

Bias↗