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C K Tse

Publications and source records attributed to C K Tse.

At least 19 recordsLinked to original sources
PubMed1996

Male and female employment in the textile industry in relation to miscarriage and preterm delivery.

To address potential reproductive hazards in textile manufacturing, we conducted a community-based case-control study in central North Carolina. Miscarriage cases were identified from medical records (280 interviewed cases): preterm delivery cases and term, normal birth weight controls (454 and 605, respectively) were identified from area hospitals. Exposures were based on job title, an interview concerning textile-related exposures, expert imputation of exposure based on job titles and interviews, and self-reported exposures by women. Relative to women and men working in nonhazardous occupations, workers in the textile industry were not at increased risk of miscarriage or preterm delivery, with the possible exception of preterm delivery among women and men employed in sectors other than knitting and yarn mills and men employed in yarn mills. Inferred exposures to specific agents were also not associated with adverse pregnancy outcome. Subject to uncertainty in exposure assessment and nonresponse, these data indicate an absence of adverse effects of the textile workplace environment on these pregnancy outcomes.

Case-Control Studies↗
PubMed1996

Anxiety and depressive symptom identification using the Duke Health Profile.

Duke Health Profile (DUKE) subscales were compared for their ability to identify anxiety and depressive symptoms as measured by the State Anxiety Inventory (SAI) and the Center for Epidemiologic Studies Depression Scale (CES-D) in 413 primary care patients. The seven-item Duke Anxiety-Depression Scale (DUKE-AD) was the best symptom identifier, with sensitivities and specificities greater than 70% for high scores on both the SAI and CES-D. Also, baseline DUKE-AD scores predicted five clinical outcomes during an 18-month follow-up period, with receiver operating characteristic (ROC) curve areas ranging from 57.1 to 58.7%. Patients shown by DUKE-AD scores to be at high risk (>30, scale 0-100) for symptoms of anxiety and/or depression were more often women, less well-educated, not working, and with lower socioeconomic status. The severity of illness was higher than that of low-risk patients. Although the providers did not know which patients were at high risk, they made a clinical diagnosis of anxiety or depression more often in high-risk patients.

Adolescent↗
PubMed1996

Cigarette smoking and semen quality.

OBJECTIVE: To determine whether cotinine levels provide stronger evidence for an association between smoking and semen quality than the number of cigarettes smoked per day or years smoked controlling for potential confounders and effect modifiers. DESIGN: Cross-sectional study. SETTING: Male volunteers at the Reproductive Endocrinology-Fertility Laboratory. PARTICIPANTS: Eighty-eight men (ages 18 to 35 years) provided a semen, urine, and blood specimen and completed a self-administered questionnaire concerning smoking and demographic information as well as caffeine and alcohol consumption. Urine, blood, and semen cotinine levels were analyzed via RIA. MAIN OUTCOME MEASURE: Standard clinical semen analysis. RESULTS: Number of cigarettes smoked per day, years smoked, and log-transformed cotinine levels were associated negatively with semen quality (density, total count, and motility). The association was evident among men age > or = 22 years. For example, the correlation coefficient for the overall association between logged urine cotinine and logged sperm density was -0.23; those stratified by age were 0. 13 (age < 22 years) and - 0. 39 (age > or = 22 years). Potential confounders included in regression models did not diminish the associations. CONCLUSIONS: Smoking is associated with lowered semen quality.

Adolescent↗
PubMed1995

Perceived family stress as a predictor of health-related outcomes.

OBJECTIVE: To measure the predictive effect of patient-perceived family stress for health-related outcomes. DESIGN: Prospective study of patients whose social stress and support were measured by self-report at baseline with the Duke Social Support and Stress Scale and used as predictors of outcomes during an 18-month follow-up period. SETTING: Rural primary care community health clinic. PATIENTS: Convenience sample of ambulatory adults. INTERVENTION: None. MAIN OUTCOME MEASURES: Follow-up (one or more follow-up visits), frequent follow-up (more than six visits), referral and/or hospitalization (one or more), high follow-up severity of illness (upper-tertile mean Duke Severity of Illness Checklist scores), and high follow-up total charges (> or = $268). RESULTS: There were 413 patients with a mean age of 40.4 years. Of these, 58.6% were women; 47.2%, African American; 52.8%, white; 56.7%, married; 77.2%, wage earners or housekeepers; and 52.3% had more than one health problem. At baseline, patients with high self-reported family stress (upper-tertile Duke Social Support and Stress Scale scores) had lower quality of life, functional health, and social support scores and higher dysfunctional health and social stress scores than other patients. High baseline family stress scores (scale of 0 to 100) predicted follow-up (odds ratio [OR] = 1.014), frequent follow-up (OR = 1.021), referral and/or hospitalization (OR = 1.018), high severity of illness at follow-up (OR = 1.016), and high follow-up charges (OR = 1.018) after controlling for the effects of social support, age, gender, and race. Family stress scores were stronger predictors of these outcomes than the other social stress and support variables. CONCLUSION: The finding of patient-perceived family stress as a risk factor for unfavorable health-related outcomes suggests the need for early detection and treatment of family stress by family physicians.

Adult↗
PubMed1995

Assessing Impact of Weight on Quality of Life.

This paper is a preliminary report on the development of a new instrument, the Impact of Weight on Quality of Life (IWQOL) questionnaire, that assesses the effects of weight on various areas of life. We conducted two studies utilizing subjects in treatment for obesity at Duke University Diet and Fitness Center. The first study describes item development, assesses reliability, and compares pre- and post-treatment scores on the IWQOL. In the second study we examined the effects of body mass index (BMI), gender, and age on subjects' perceptions of impact of weight on quality of life. Results indicate adequate psychometric properties with test-retest reliabilities averaging .75 for single items, and .89 for scales. Scale internal consistency averaged .87. Post-treatment scores differed significantly from pre-treatment scores on all scales, indicating that treatment produced positive changes in impact of weight on quality of life. The results of the second study indicate that the impact of weight generally worsened as the patients' size increased. However for women there was no association between BMI and impact of weight on Self-Esteem and Sexual Life. Even at the lowest BMI tertile studied, women reported that weight had a substantial impact in these areas. There were also significant gender differences, with women showing greater impact of weight on Self-Esteem and Sexual Life compared with men. The impact of age was a bit surprising, with some areas showing positive changes and others showing no change.

Adult↗
PubMed1995

Health status and severity of illness as predictors of outcomes in primary care.

Two measures of health status and severity of illness were tested as indicators of patient case-mix to predict health-related outcomes in a rural primary care community health clinic, using a convenience sample of 413 ambulatory adults (mean age = 40.4 years: 58.6% women, and 47.2% black). At baseline; patients completed the Duke Health Profile, and providers completed the Duke Severity of Illness Checklist. During the 18-month follow-up study, patients experienced the following outcomes: at least one follow-up visit (74.3%), more than six visits (20.6%), at least one referral or hospital admission (17.3%), upper tertile severity scores (24.9%), and upper tertile office charges (24.9%). Baseline physical health, perceived health, and severity scores were statistically significantly predictive of all five outcomes. Predictive accuracy (i.e., area under the receiver operating characteristic curves) for outcome probabilities estimated from a case-mix model of physical health, severity, age, gender, and race was 72.3% for follow-up, 69.7% for frequent follow-up, 70.5% for referral and/or hospital stay, 65.7% for high follow-up severity of illness, and 67.6% for high follow-up charges. These data support health status and severity of illness as case-mix indicators and outcome predictors of follow-up utilization, severity of illness, and cost in the primary care setting.

Adult↗
PubMed1995

Computer-prompted diagnostic codes.

BACKGROUND: The purpose of this study was to develop and evaluate a computer system that would translate patient diagnoses noted by a physician into appropriate International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes and maintain a patient-specific up-to-date problem list. METHODS: The intervention consisted of a computerized list (dictionary) of diagnoses, including practice-specific synonyms and abbreviations, linked to their corresponding ICD-9-CM codes. To record the diagnoses for the office visit before the intervention, physicians used International Classification of Health Problems in Primary Care (ICHPPC-2) codes. After the intervention, physicians used their own words or checked previously identified diagnoses on the computer-generated problem list. The computer then identified the correct ICD-9-CM code. Accuracy of coding was compared before and after the new computerized system was implemented. RESULTS: Visits in which all diagnoses matched increased from 58% to 76% (P < .001) with use of the computer system. Visits in which no computer diagnoses matched the chart decreased from 22% to 8% (P < .001). Errors of omission declined from 38% to 18% (P < .001). Errors of commission decreased from 19% to 11% (P = .006). Overall accuracy increased from 62% to 82% (P < .001). CONCLUSIONS: Outpatient medical diagnosis coding can be simplified and accuracy improved by using a computerized dictionary of practice-specific diagnoses and synonyms linked to appropriate ICD-9-CM codes. Such a system provides a computer-generated problem list that accurately reflects the chart and assists with prompted coding on subsequent visits.

Abstracting and Indexing↗
PubMed1993

The Duke Severity of Illness Checklist (DUSOI) for measurement of severity and comorbidity.

The Duke Severity of Illness Checklist (DUSOI) was evaluated on 414 primary care adult patients using data collected both by medical providers at the time of the patient visit and later by a chart auditor. Severity scores for individual diagnoses were determined by summing the ratings for four non-disease-specific parameters: symptom level, complications, prognosis without treatment, and expected response to treatment. Mean diagnosis severity scores (scale 0-100) among the 21 most prevalent diagnoses varied from a low of 13.9 for menopausal syndrome to a high of 43.0 for sprains and strains. An overall severity score was calculated by combining diagnosis severity scores and giving highest weights to the most severe diagnoses. Provider-generated overall severity scores (mean = 43.3) and auditor-generated overall severity scores (mean = 38.9) were significantly correlated (coefficient of agreement = 0.59, p < 0.0001). Diagnoses varied in their individual contribution to the overall severity score, from 8.9% for lipid disorder to 90.0% for sprains and strains. Separate comorbidity severity scores were calculated to measure the severity of all of each patient's health problems except the diagnosis under study. For example, patients with menopausal syndrome had co-existing health problems which generated a high mean comorbidity severity score of 43.2, while patients with sprains and strains had a low mean comorbidity score of 4.7. The DUSOI Checklist can be used in the clinical setting by both providers and auditors to produce quantitative severity scores (by diagnosis, overall, and for comorbidity) which are based entirely upon clinical judgment. This method should be useful in controlling for severity of illness in clinical studies and indicating the outcome of medical care in terms of reduction in severity of illness following medical interventions.

Adolescent↗
PubMed1993

Disease-specific versus generic measurement of health-related quality of life in insulin-dependent diabetic patients.

The health-related quality of life of 170 adult insulin-dependent diabetic patients was measured cross-sectionally to compare a disease-specific instrument, Diabetes Quality of Life (DQOL) questionnaire, and two generic instruments, the Duke Health Profile (DUKE) and the General Health Perceptions Questionnaire (GHP). The generic measures provided as much or more information about health-related quality of life as the disease-specific instrument. This was demonstrated both by comparison of the DQOL with the DUKE and GHP and by comparison of the disease-specific with the generic components of a modified version of the DQOL. Patients with the diabetic complication of nephropathy had increased worry over their health and lower general health perceptions. Neither the duration of diabetes nor the intensity of insulin therapy, however, was found to have a statistically significant effect on any of the health-related quality of life scores. Nondiabetic factors, such as the comorbidity, nondiabetic medications, marital status, social relationships, and family arguments were found to be predictors of health-related quality of life more often than the diabetic factors duration of diabetes, complications, and intensity of insulin therapy. These analyses suggest the clinical value of using generic questionnaires to measure health-related quality of life and psychosocial factors to identify nondiabetic problems that might respond to intervention, thereby potentially enhancing the effect of diabetes-specific therapy.

Adolescent↗
PubMed1993

Increasing compliance with mammography recommendations: health assessment forms.

BACKGROUND: Inexpensive reminder systems are needed to ensure that primary care physicians consistently provide health maintenance services to their patients. The purpose of this study was to determine the effectiveness of a simple, inexpensive health assessment form in place of the standard chart note to increase physician compliance with mammography recommendations. METHODS: A health assessment form with a reminder for screening mammography was implemented in a family practice in 1987 and was to be used as the official chart record for health maintenance visits. The charts of all women 50 years of age and older with two or more office visits during the years 1985 through 1988 were audited to determine how many mammograms were completed. Results were compared with mammography completion rates at a similar practice that did not use a health assessment form. RESULTS: The study group showed a significant increase in mammography completion after implementation of the form, with compliance increasing from 7.3% to 32.0% (P < .001). The comparison group had an increase in mammogram completion from 12.0% to 17.8% (P < .001). The difference between the changes in rates of mammography in the two practices was statistically significant (P < .001). Among women in the study group who had a scheduled health maintenance visit during the study period the average rate of mammography completion increased from 21.2% to 65.2% (P < .001). CONCLUSIONS: The addition of a health assessment form with a mammography reminder at the health maintenance visit is an effective and inexpensive method to increase compliance with mammography.

Adolescent↗
PubMed1992

Quality of life and functional health of primary care patients.

Quality of life and functional health were measured cross-sectionally for 314 adult ambulatory primary care patients in a rural clinic and found to be much better for patients with low severity of illness who required no confinement to home because of health problems, than for patients with high severity of illness who required confinement. Severity of illness was the strongest predictor for patient-reported physical health function and for patient quality of life when assessed by the health provider. Confinement was the strongest predictor for patient quality of life when assessed by the patient. There was very little agreement between patient-assessed and provider-assessed quality of life. Family stress was the strongest predictor of function in terms of mental health, social health, general health, self-esteem, anxiety, and depression. These data suggest that clinicians should direct increased attention to patient-assessed quality of life, patient-reported functional health status, and psychosocial factors such as family stress in an effort to improve medical outcomes.

Activities of Daily Living↗
PubMed1991

Development of the 17-item Duke Health Profile.

The 17-item Duke Health Profile (DUKE) was developed as a refined version of the 63-item Duke-UNC Health Profile (DUHP) using a methodology based upon a balanced clinical and statistical rationale. The result is a brief, valid functional health measure with 10 scales that compares well with the MOS Short-form and the COOP Charts. In addition to the five constructs (ambulation, emotional symptoms, activities with friends or relatives, health perception, and pain) which are measured by all three of the instruments, the DUKE quantitates cognition, social self-esteem, confinement, and somatic symptoms other than pain.

Adult↗
PubMed1991

Validation of the Duke Social Support and Stress Scale.

The Duke Social Support and Stress Scale (DUSOCS) was validated in 249 adult family practice patients using the Family Strengths, the Family Inventory of Life Events, and the Duke Health Profile (DUKE) as comparison instruments. Validity was supported in that the DUSOCS family support measure had the clinically expected positive associations with DUKE health measures (regression coefficients of +7.4 to +18.7) and negative associations with DUKE anxiety and depression measures (-2.0 to -17.2). DUSOCS family stress had negative associations with the health measures (-11.6 to -34.5) and positive associations with anxiety and depression (+18.9 to +32.1). Family and non-family stress contributed more than severity of illness to elevated levels of anxiety and depression and lowered levels of mental health, social health, and self-esteem, while these same stresses contributed only half as much as severity of illness to lowered physical health.

Adolescent↗
PubMed1991

Tricyclic antidepressant prescribing for nonpsychiatric disorders. An analysis based on data from the 1985 National Ambulatory Medical Care Survey.

BACKGROUND: Primary care physicians often do not document a psychiatric diagnosis when prescribing psychotropic medications. Recent literature suggests the potential benefit of tricyclic antidepressants (TCAs) in a number of nonpsychiatric conditions (low back pain, peptic disease, fibrositis, headache, peripheral neuropathy, rheumatoid disease, and irritable colon). METHODS: Data from the 1985 National Ambulatory Medical Care Survey (NAMCS) were used to categorize the primary diagnoses given during office visits in which tricyclic antidepressants were prescribed. Comparisons were made across specialties. RESULTS: Primary care physicians prescribed tricyclic antidepressants in 1% of all visits (an estimated 2,892,000 visits per year). Whereas 50% of these visits at which TCAs were prescribed were for documented psychiatric illnesses or conditions, 15% were for nonpsychiatric TCA-responsive conditions. The majority of visits by patients with these disorders were to primary care physicians. The pattern of TCA prescribing for these disorders by primary care physicians parallels that of other medical specialties except that primary care physicians prescribed TCAs for nonpsychiatric TCA-responsive disorders less frequently than did other medical specialists. CONCLUSIONS: When nonpsychiatric TCA-responsive disorders are included, primary care physicians document with appropriate diagnoses 15% more of their TCA prescriptions than previous studies have indicated. An understanding of the 35% of TCA prescriptions that do not show proper documentation will require further study and information not available from the NAMCS:

Adolescent↗
PubMed1990

Depression, disability days, and days lost from work in a prospective epidemiologic survey.

We describe the relationship of depression and depressive symptoms to disability days and days lost from work in 2980 participants in the Epidemiologic Catchment Area Study in North Carolina after 1 year of follow-up. Compared with asymptomatic individuals, persons with major depression had a 4.78 times greater risk of disability (95% confidence interval, 1.64 to 13.88), and persons with minor depression with mood disturbance, but not major depression, had a 1.55 times greater risk (95% confidence interval, 1.00 to 2.40). Because of its prevalence, individuals with minor depression were associated with 51% more disability days in the community than persons with major depression. This group was also at increased risk of having a concomitant anxiety disorder or developing major depression within 1 year. We conclude that the threshold for identifying clinically significant depression may need to be reevaluated to include persons with fewer symptoms but measurable morbidity. Only by changing our nosology can the societal impact of depression be adequately addressed.

Absenteeism↗
PubMed1990

The health status and life satisfaction of first-year medical students.

The self-reported health status and life satisfaction of 286 first-year Duke University medical students in four consecutive classes were measured at the beginning and end of the school year and compared statistically with relevant sociodemographic and behavioral factors. Health status, quantitated in terms of Duke Health Profile scores, was generally lower for women than for men. Although there was a definite trend of worsening along all parameters of health and satisfaction during the year for both women and men, the most marked change was the increase in depressive symptoms. The students who were very satisfied with life had fewer symptoms of depression and anxiety; higher self-esteem, better physical, mental, and social health; stronger social ties; more physical activity; more sleep; and fewer stressful life events. Strong social ties was the factor most positively related to better health and life satisfaction.

Depressive Disorder↗
PubMed1990

The Duke Health Profile. A 17-item measure of health and dysfunction.

The Duke Health Profile (DUKE) is a 17-item generic self-report instrument containing six health measures (physical, mental, social, general, perceived health, and self-esteem), and four dysfunction measures (anxiety, depression, pain, and disability). Items were derived from the 63-item Duke-UNC Health Profile, based upon face validity and item-remainder correlations. The study population included 683 primary care adult patients. Reliability was supported by Cronbach's alphas (0.55 to 0.78) and test-retest correlations (0.30 to 0.78). Convergent and discriminant validity were demonstrated by score correlations between the DUKE and the Sickness Impact Profile, the Tennessee Self-Concept Scale, and the Zung Self-Rating Depression Scale. Clinical validity was supported by differences between the health scores of patients with clinically different health problems. Patients with painful physical problems had a DUKE physical health mean score of 58.1, while patients with only health maintenance problems had a mean score of 83.9 (scale: 0.0 = poorest health and 100.0 = best health). Patients with mental health problems had a DUKE mental health mean score of 49.2, in contrast to 75.7 for patients with painful physical problems and 79.2 for those with health maintenance. The DUKE is presented as a brief technique for measuring health as an outcome of medical intervention and health promotion.

Adolescent↗