Diabetes increases financial burden of individuals with traumatic spinal cord injury (TSCI)

Abstract

Study design: Secondary analysis of existing data. Objective: To estimate the association of diabetes with family income in a pooled 15-year cohort of individuals with TSCI. Setting: A large specialty hospital in the southeastern United States. Methods: A total number of 1408 individuals identified with TSCI were surveyed regarding family income as well as clinical and demographic factors. Due to income being reported in censored intervals rather than individual dollar values, interval regression was used to estimate models of the association of family income with diabetes.Results: Approximately 12% of individuals with TSCI reported being diagnosed with diabetes. The most frequent family income interval in our sample was o$10 000, lower than the poverty threshold. The family income interval with the highest rate of diabetes was $15 000-$20 000. In an unadjusted model, diabetes was associated with a significant reduction of $8749 and in a fully adjusted model, diabetes was significantly associated with a reduction of $8560 in family income. Being a minority was also significantly associated with a reduction whereas educational attainment was associated with increased family income. TSCI severity was not significantly related to family income. Conclusion: Diabetes imposes an additional financial burden on individuals with TSCI an already vulnerable population with high health care costs. The burden is more pronounced in minorities with TSCI. Providers should be aware of the higher prevalence of diabetes among patients with TSCI and pursue a policy of testing early and vigilant management. Further studies are needed regarding special interventions for managing diabetes in the TSCI population.

Relationship Between Viremia and Specific Organ Damage in Ebola Patients: A Cohort Study

“…: ALT, AST, LDH and CPK) were assessed by using MME interval regression models. MME interval regression is a generalization of other censored regression estimators, [17] such as Tobit, [18] and can be used when the dependent variable is measured as point data, interval-censored data, left-censored data, or right-censored data. [17] Estimates for intercept (baseline) and independent variables coefficients were optimized by using the naturallog transformed dependent variables.…”

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“…39 Other comorbidities seen to be higher in patients with a low income included diabetes mellitus (higher rates in the $15,000-$20,000 income range, p < 0.05) and tooth and gum problems (OR 1.66, 95% CI 1.18-2.33). 11,44 As regards long-term outcomes, a study based on a questionnaire reported that the prevalence of obesity was not significantly different for various income groups (p = 0.39). 21 Paradoxically, one recent cohort study reported a higher mortality rate among patients in the $40,000-$60,000 income range than that among patients with less than $40,000.…”

Neuroprotective effects of estrogen in CNS injuries: insights from animal models

“… 28 A quirk of fate is that ~12% of the patients with SCI are being diagnosed with diabetes that imposes an additional economic burden on the patients with SCI, who are already vulnerable with high health care costs. 29 The economic burden is highly noticeable in minority populations suffering from the devastating consequences of SCI.…”