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Biomedical subjects

D Berlowitz

Publications and source records attributed to D Berlowitz.

6 recordsLinked to original sources
PubMed2001

Cardiac and respiratory activity at arousal from sleep under controlled ventilation conditions.

Arousal from sleep is associated with elevated cardiac and respiratory activity. It is unclear whether this occurs because of homeostatic mechanisms or a reflex activation response associated with arousal. Cardiorespiratory activity was measured during spontaneous arousals from sleep in subjects breathing passively on a ventilator. Under such conditions, homeostatic mechanisms are eliminated. Ventilation, end-tidal PCO2, mask pressure, diaphragmatic electromyograph, heart rate, and blood pressure were measured in four normal subjects under two conditions: assisted ventilation and a normal ventilation control condition. In the control condition, there was a normal, sleep-related fall in ventilation and rise in end-tidal PCO2. Subsequently, at an arousal, there was an increase in respiratory and cardiac activity. In the ventilator condition, a vigorous cardiorespiratory response to a spontaneous arousal from sleep remained. These results indicate that sleep-related respiratory stimuli are not necessary for the occurrence of elevated cardiorespiratory activity at an arousal from sleep and are consistent with the hypothesis that such activity is at least in part due to a reflex activation response.

Adult↗
PubMed2000

Does diagnostic information contribute to predicting functional decline in long-term care?

BACKGROUND: Compared with the acute-care setting, use of risk-adjusted outcomes in long-term care is relatively new. With the recent development of administrative databases in long-term care, such uses are likely to increase. OBJECTIVES: The objective of this study was to determine the contribution of ICD-9-CM diagnosis codes from administrative data in predicting functional decline in long-term care. RESEARCH DESIGN: We used a retrospective sample of 15,693 long-term care residents in VA facilities in 1996. METHODS: We defined functional decline as an increase of > or =2 in the activities of daily living (ADL) summary score from baseline to semiannual assessment. A base regression model was compared to a full model enhanced with ICD-9-CM codes. We calculated validated measures of model performance in an independent cohort. RESULTS: The full model fit the data significantly better than the base model as indicated by the likelihood ratio test (chi2 = 179, df = 11, P <0.001). The full model predicted decline more accurately than the base model (R2 = 0.06 and 0.05, respectively) and discriminated better (c statistics were 0.70 and 0.68). Observed and predicted risks of decline were similar within deciles between the 2 models, suggesting good calibration. Validated R2 statistics were 0.05 and 0.04 for the full and base models; validated c statistics were 0.68 and 0.66. CONCLUSIONS: Adding specific diagnostic variables to administrative data modestly improves the prediction of functional decline in long-term care residents. Diagnostic information from administrative databases may present a cost-effective alternative to chart abstraction in providing the data necessary for accurate risk adjustment.

Activities of Daily Living↗
PubMedDate not supplied

Primary carcinoid tumor of the pancreas.

Serotonin-secreting (carcinoid) tumors of the pancreas are very rare. There are only 13 cases reported since 1963. Liver metastases have not previously been described. We present two patients with primary carcinoid tumor of the pancreas, which metastasized to the liver. These patients differ in their clinical and radiological appearance. Carcinoid tumor should be considered in the differential diagnosis of a pancreatic mass in a patient with carcinoid syndrome, but lack of this syndrome does not exclude the diagnosis.

Aged↗
PubMedDate not supplied

Risk adjustment for measuring health outcomes: an application in VA long-term care.

An empirically derived risk adjustment model is useful in distinguishing among facilities in their quality of care. We used Veterans Affairs (VA) administrative databases to develop and validate a risk adjustment model to predict decline in functional status, an important outcome measure in long-term care, among patients residing in VA long-term care facilities. This model was used to compare facilities on adjusted and unadjusted rates of decline. Predictors of decline included age, time between assessments, baseline functional status, terminal illness, pressure ulcers, pulmonary disease, cancer, arthritis, congestive heart failure, substance-related disorders, and various neurologic disorders. The model performed well in the development and validation databases (c statistics, 0.70 and 0.68, respectively). Risk-adjusted rates and rankings of facilities differed from unadjusted ratings. We conclude that judgments of facility performance depend on whether risk-adjusted or unadjusted decline rates are used. Valid risk adjustment models are therefore necessary when comparing facilities on outcomes.

Aged↗