Sentence examples for diagnosis count from inspiring English sources

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BISEP: Burden of illness score for elderly persons; CGA: Comprehensive geriatric assessment; CIRS: Cumulative illness rating scale; ChI: Charlson index; DC: Diagnosis count; GIC: Geriatric index of comorbidity; ICED: Index of coexistent disease; IDS: Individual disease severity; PI: Prognostic index.

The Diagnosis Count (DC) is a simple and universally available comorbidity index consisting of a numeric sum of all secondary diagnoses and has been demonstrated to be predictive of overall mortality and hospital resource utilization [ 16, 17].

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28 Diagnosis counts and rates of chlamydia and gonorrhoea in GUM clinics and, for chlamydia, through the NCSP (excluding GP), were calculated.

Overall and annual age-standardised and gender-standardised diagnosis counts and rates (per 100 000 population) with 95% CIs were then estimated for all GPs in England, using English population estimates.

Patients typically present with severe thrombocytopenia at diagnosis (platelet count <20,000/mm), and physicians, associating the low platelet count with a high risk of hemorrhage, often administer drug therapy.

Secondary outcomes included, 'late' diagnosis (CD4 count < 350/mm3 at diagnosis), 'very late' diagnosis (CD4 count < 200/mm3 at diagnosis) and time to diagnosis (months from first presentation to diagnosis).

Cognitive impairment was not associated with number of years since HIV diagnosis, CD4 count (current or nadir), neuropathy, depression, medication adherence, or alcohol use (Table 5).

Neuroses (anxiety and somatoform disorders) was the most common diagnosis by count and was recorded for 573 recipients.

At the time of diagnosis, blood count, creatinine, ALP, aspartate aminotransferase, lactate dehydrogenase (LDH), albumin, and CRP were evaluated.

The study variables included sociodemographic and behavior characteristics; characteristics related to diagnosis (CD4+ count at AIDS diagnosis) and treatment regimen; and time from AIDS diagnosis to AIDS-related death.

We built bivariate and multivariate Poisson regression models to assess the association between baseline age, sex, education, employment, TB diagnosis, CD4 count, and enrollment year on the rate of first UCI during the first year on ART.

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