Clostridium difficile infection (CDI) in HIV-positive patients

The main aim of this study was to look at the association of Clostridium difficile infection (CDI) and HIV. A secondary goal was to look at the trend of CDI-related deaths in Texas from 1999-2011. To evaluate the coinfection of CDI and HIV, we looked at 2 datasets provided by CHS-TDSHS, for 13 years of study period from 1999-2011: 1) Texas death certificate data and 2) Texas hospital discharge data. An ancillary source of data was national level death data from CDC. We did a secondary data analysis and reported the age-adjusted death rates (mortality) and hospital discharge frequencies (morbidity) for CDI, HIV and for CDI+HIV coinfection.^ Since the turn of the century, CDI has reemerged as an important public health challenge due to the emergence of hypervirulent epidemic strains. From 1999-2011, there has been a significant upward trend in CDI-related death rates; in the state of Texas alone, CDI mortality rate has increased 8.7 fold in this time period at the rate of 0.2 deaths per year per 100,000 individuals. On the contrary, mortality due to HIV has decreased by 46% and has been trending down. The demographic groups in Texas with the highest CDI mortality rates were elderly aged 65+, males, whites and hospital inpatients. The epidemiology of C. difficile has changed in such a way that it is not only staying confined to these traditional high-risk groups, but is also being increasingly reported in low-risk populations such as healthy people in the community (community acquired C. difficile), and most recently immunocompromised patients. Among the latter, HIV can worsen the adverse health outcomes of CDI and vice versa. In patients with CDI and HIV coinfection, higher mortality and morbidity was found in young & middle-aged adults, blacks and males, the same demographic population that is at higher risk for HIV. As with typical CDI, the coinfection was concentrated in the hospital inpatients. Of all the CDI-related deaths in USA from 1999-2010, in the 25-44 year age group, 13% had HIV infection. Of all CDI-related inpatient hospital discharges in Texas from 1999-2011, in patients 44 years and younger, 17% had concomitant HIV infection. Therefore, HIV is a possible novel emerging risk factor for CDI.^

Intensive care unit utilization among patients with cancer at the end of life

Over the last 2 decades, survival rates in critically ill cancer patients have improved. Despite the increase in survival, the intensive care unit (ICU) continues to be a location where end-of-life care takes place. More than 20% of deaths in the United States occur after admission to an ICU, and as baby boomers reach the seventh and eighth decades of their lives, the volume of patients in the ICU is predicted to rise. The aim of this study was to evaluate intensive care unit utilization among patients with cancer who were at the end of life. End of life was defined using decedent and high-risk cohort study designs. The decedent study evaluated characteristics and ICU utilization during the terminal hospital stay among patients who died at The University of Texas MD Anderson Cancer Center during 2003-2007. The high-risk cohort study evaluated characteristics and ICU utilization during the index hospital stay among patients admitted to MD Anderson during 2003-2007 with a high risk of in-hospital mortality. Factors associated with higher ICU utilization in the decedent study included non-local residence, hematologic and non-metastatic solid tumor malignancies, malignancy diagnosed within 2 months, and elective admission to surgical or pediatric services. Having a palliative care consultation on admission was associated with dying in the hospital without ICU services. In the cohort of patients with high risk of in-hospital mortality, patients who went to the ICU were more likely to be younger, male, with newly diagnosed non-metastatic solid tumor or hematologic malignancy, and admitted from the emergency center to one of the surgical services. A palliative care consultation on admission was associated with a decreased likelihood of having an ICU stay. There were no differences in ethnicity, marital status, comorbidities, or insurance status between patients who did and did not utilize ICU services. Inpatient mortality probability models developed for the general population are inadequate in predicting in-hospital mortality for patients with cancer. The following characteristics that differed between the decedent study and high-risk cohort study can be considered in future research to predict risk of in-hospital mortality for patients with cancer: ethnicity, type and stage of malignancy, time since diagnosis, and having advance directives. Identifying those at risk can precipitate discussions in advance to ensure care remains appropriate and in accordance with the wishes of the patient and family.^

Indeterminate QunatiFERON-TB Gold In-Tube assay results in association with procedural specimen collection in children

BACKGROUND. The development of interferon-gamma release assays (IGRA) has introduced powerful tools in diagnosing latent tuberculosis infection (LTBI) and may play a critical role in the future of tuberculosis diagnosis. However, there have been reports of high indeterminate results in young patient populations (0-18 years). This study investigated results of the QunatiFERON-TB Gold In-Tube (QFT-GIT) IGRA in a population of children (0-18 years) at Texas Children's Hospital in association with specimen collection procedures using surrogate variables. ^ METHODS. A retrospective case-control study design was used for this investigation. Cases were defined as having QFT-GIT indeterminate results. Controls were defined as having either positive or negative results (determinates). Patients' admission status, staff performing specimen collection, and specific nurse performing specimen collection were used as surrogates to measure specimen collection procedures. ^ To minimize potential confounding, abstraction of patients' electronic medical records was performed. Abstracted data included patients' medications and evaluation at the time of QFT-GIT specimen collection in addition to their medical history. QFT-GIT related data was also abstracted. Cases and controls were characterized using chi-squared tests or Fisher's exact tests across categorical variables. Continuous variables were analyzed using one-way ANOVA and t-tests for continuous variables. A multivariate model was constructed by backward stepwise removal of statistically significant variables from univariate analysis. ^ RESULTS. Patient data was abstracted from 182 individuals aged 0-18 years from July 2010 to August 2011 at Texas Children's Hospital. 56 cases (indeterminates) and 126 controls (determinates) were enrolled. Cancer was found to be an effect modifier with subsequent stratification resulting in a cancer patient population too small to analyze (n=13). Subsequent analyses excluded these patients. ^ The exclusion of cancer patients resulted in a population of 169 patients with 49 indeterminates (28.99%) and 120 determinates (71.01%), with mean ages of 9.73 (95% CI: 8.03, 11.43) years and 11.66 (95% CI: 10.75, 12.56) years (p = 0.033), respectively. Median age of patients who were indeterminates and determinates were 12.37 and 12.87 years, respectively. Lack of data for our specific nurse surrogate (QFTNurse) resulted in its exclusion from analysis. The final model included only our remaining surrogate variables (QFTStaff and QFTInpatientOutpatient). The staff collecting surrogate (QFTStaff) was found to be modestly associated with indeterminates when nurses collected the specimen (OR = 1.54, 95% CI: 0.51, 4.64, p = 0.439) in the final model. Inpatients were found to have a strong and statistically significant association with indeterminates (OR = 11.65, 95% CI: 3.89, 34.9, p < 0.001) in the final model. ^ CONCLUSION. Inpatient status was used as a surrogate for indication of nurse drawn blood specimens. Nurses have had little to no training regarding shaking of tubes versus phlebotomists regarding QFT-GIT testing procedures. This was also measured by two other surrogates; specifically a medical note stating whether a nurse or phlebotomist collected the specimen (QFTStaff) and the name and title of the specific nurse if collection was performed by a nurse (QFTNurse). Results indicated that inpatient status was a strong and statistically significant factor for indeterminates, however, nurse collected specimens and indeterminate results had no statistically significant association in non-cancer patients. The lack of data denoting the specific nurse performing specimen collection excluded the QFTNurse surrogate in our analysis. ^ Findings suggests training of staff personnel in specimen procedures may have little effect on the number of indeterminates while inpatient status and thus possibly illness severity may be the most important factor for indeterminate results in this population. The lack of congruence between our surrogate measures may imply that our inpatient surrogate gauged illness severity rather than collection procedures as intended. ^ Despite the lack of clear findings, our analysis indicated that more than half of indeterminates were found in specimens drawn by nurses and as such staff training may be explored. Future studies may explore methods in measuring modifiable variables during pre-analytical QFT-GIT procedures that can be discerned and controlled. Identification of such measures may provide insight into ways to lowering indeterminate QFT-GIT rates in children.^

Estimates of hospital and physician costs of epilepsy in the United States for 1995 comparing the provider -based survey method and a patient -based medical charts and billing method

This investigation compares two different methodologies for calculating the national cost of epilepsy: provider-based survey method (PBSM) and the patient-based medical charts and billing method (PBMC&BM). The PBSM uses the National Hospital Discharge Survey (NHDS), the National Hospital Ambulatory Medical Care Survey (NHAMCS) and the National Ambulatory Medical Care Survey (NAMCS) as the sources of utilization. The PBMC&BM uses patient data, charts and billings, to determine utilization rates for specific components of hospital, physician and drug prescriptions. ^ The 1995 hospital and physician cost of epilepsy is estimated to be $722 million using the PBSM and $1,058 million using the PBMC&BM. The difference of $336 million results from $136 million difference in utilization and $200 million difference in unit cost. ^ Utilization. The utilization difference of $136 million is composed of an inpatient variation of $129 million, $100 million hospital and $29 million physician, and an ambulatory variation of $7 million. The $100 million hospital variance is attributed to inclusion of febrile seizures in the PBSM, $−79 million, and the exclusion of admissions attributed to epilepsy, $179 million. The former suggests that the diagnostic codes used in the NHDS may not properly match the current definition of epilepsy as used in the PBMC&BM. The latter suggests NHDS errors in the attribution of an admission to the principal diagnosis. ^ The $29 million variance in inpatient physician utilization is the result of different per-day-of-care physician visit rates, 1.3 for the PBMC&BM versus 1.0 for the PBSM. The absence of visit frequency measures in the NHDS affects the internal validity of the PBSM estimate and requires the investigator to make conservative assumptions. ^ The remaining ambulatory resource utilization variance is $7 million. Of this amount, $22 million is the result of an underestimate of ancillaries in the NHAMCS and NAMCS extrapolations using the patient visit weight. ^ Unit cost. The resource cost variation is $200 million, inpatient is $22 million and ambulatory is $178 million. The inpatient variation of $22 million is composed of $19 million in hospital per day rates, due to a higher cost per day in the PBMC&BM, and $3 million in physician visit rates, due to a higher cost per visit in the PBMC&BM. ^ The ambulatory cost variance is $178 million, composed of higher per-physician-visit costs of $97 million and higher per-ancillary costs of $81 million. Both are attributed to the PBMC&BM's precise identification of resource utilization that permits accurate valuation. ^ Conclusion. Both methods have specific limitations. The PBSM strengths are its sample designs that lead to nationally representative estimates and permit statistical point and confidence interval estimation for the nation for certain variables under investigation. However, the findings of this investigation suggest the internal validity of the estimates derived is questionable and important additional information required to precisely estimate the cost of an illness is absent. ^ The PBMC&BM is a superior method in identifying resources utilized in the physician encounter with the patient permitting more accurate valuation. However, the PBMC&BM does not have the statistical reliability of the PBSM; it relies on synthesized national prevalence estimates to extrapolate a national cost estimate. While precision is important, the ability to generalize to the nation may be limited due to the small number of patients that are followed. ^