Browsing by Author "Campbell, Noll"

Now showing 1 - 8 of 8
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    Aging and Post-Intensive Care Syndrome (PICS): A Critical Need for Geriatric Psychiatry
    (Elsevier, 2017) Wang, Sophia; Allen, Duane; Kheir, You Na; Campbell, Noll; Khan, Babar; Department of Psychiatry, IU School of Medicine
    Due to the aging of the intensive care unit (ICU) population and an improvement in survival rates after ICU hospitalization, an increasing number of older adults are suffering from long-term impairments due to critical illness, known as post-intensive care syndrome (PICS). This paper focuses on PICS-related cognitive, psychological, and physical impairments, and the impact of ICU hospitalization on families and caregivers. The authors also describe innovative models of care for PICS, and what roles geriatric psychiatrists could play in the future of this rapidly growing population.
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    Anticholinergic Exposure During Rehabilitation: Cognitive and Physical Function Outcomes in Patients with Delirium Superimposed on Dementia
    (Elsevier, 2015-12) Kolanowski, Ann; Mogle, Jacqueline; Fick, Donna M.; Campbell, Noll; Hill, Nikki; Mulhall, Paula; Behrens, Liza; Colancecco, Elise; Boustani, Malaz; Clare, Linda; Department of Medicine, IU School of Medicine
    OBJECTIVES: We examined the association between anticholinergic medication exposure and subsequent cognitive and physical function in patients with delirium superimposed on dementia during rehabilitation. We also examined length of stay and discharge disposition by anticholinergic medication exposure. DESIGN: In this secondary analysis we used control group data from an ongoing randomized clinical trial. SETTING/PARTICIPANTS: Participants with delirium and dementia were enrolled at admission to post-acute care. These 99 participants had a mean age of 86.11 (±6.83) years; 67.6% were women; 98% were Caucasian; and 33% were positive for at least one APOE e4 allele. MEASURES: We obtained daily measures of cognitive and physical function using: Digit Span; memory, orientation and attention items from the Montreal Cognitive Assessment; CLOX; the Confusion Assessment Method; and the Barthel Index. Anticholinergic medication exposure was measured weekly using the Anticholinergic Cognitive Burden Scale. RESULTS: Using multilevel models for time we found that greater use of clinically relevant anticholinergic medications in the previous week reduced cognitive and physical function, as measured by Digit Span Backwards and the Barthel index, in the current week. There was no effect of anticholinergic medication use on delirium severity, and APOE status did not moderate any outcomes. Greater use of clinically relevant anticholinergic medications was related to longer length of stay but not discharge disposition. CONCLUSIONS: For vulnerable older adults, anticholinergic exposure represents a potentially modifiable risk factor for poor attention, working memory, physical function, and greater length of stay during rehabilitation.
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    Development and Temporal Validation of an Electronic Medical Record-Based Insomnia Prediction Model Using Data from a Statewide Health Information Exchange
    (MDPI, 2023-05-05) Holler, Emma; Chekani, Farid; Ai, Jizhou; Meng, Weilin; Khandker, Rezaul Karim; Ben Miled, Zina; Owora, Arthur; Dexter, Paul; Campbell, Noll; Solid, Craig; Boustani, Malaz; Electrical and Computer Engineering, School of Engineering and Technology
    This study aimed to develop and temporally validate an electronic medical record (EMR)-based insomnia prediction model. In this nested case-control study, we analyzed EMR data from 2011–2018 obtained from a statewide health information exchange. The study sample included 19,843 insomnia cases and 19,843 controls matched by age, sex, and race. Models using different ML techniques were trained to predict insomnia using demographics, diagnosis, and medication order data from two surveillance periods: −1 to −365 days and −180 to −365 days before the first documentation of insomnia. Separate models were also trained with patient data from three time periods (2011–2013, 2011–2015, and 2011–2017). After selecting the best model, predictive performance was evaluated on holdout patients as well as patients from subsequent years to assess the temporal validity of the models. An extreme gradient boosting (XGBoost) model outperformed all other classifiers. XGboost models trained on 2011–2017 data from −1 to −365 and −180 to −365 days before index had AUCs of 0.80 (SD 0.005) and 0.70 (SD 0.006), respectively, on the holdout set. On patients with data from subsequent years, a drop of at most 4% in AUC is observed for all models, even when there is a five-year difference between the collection period of the training and the temporal validation data. The proposed EMR-based prediction models can be used to identify insomnia up to six months before clinical detection. These models may provide an inexpensive, scalable, and longitudinally viable method to screen for individuals at high risk of insomnia.
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    Interaction between cognitive impairment and discharge destination and its effect on rehospitalization
    (Wiley, 2013-11) Nazir, Arif; LaMantia, Michael; Chodosh, Joshua; Khan, Babar; Campbell, Noll; Hui, Siu; Boustani, Malaz; Medicine, School of Medicine
    OBJECTIVES: To evaluate the effect of cognitive impairment on rehospitalization in older adults. DESIGN: One-year longitudinal study. SETTING: Medical service of an urban, 340-bed public hospital in Indianapolis between July 2006 and March 2008. PARTICIPANTS: Individuals aged 65 and older admitted to the medical service (N = 976). MEASUREMENTS: Rehospitalization was defined as any hospital admission after the index admission. Participant demographics, discharge destination, Charlson Comorbidity Index, Acute Physiology Score, and prior hospitalizations were measured as the confounders. Participants were considered to have cognitive impairment if they had two or more errors on the Short Portable Mental Status Questionnaire. RESULTS: After adjusting for confounders, a significant interaction between cognitive impairment and discharge location was found to predict rehospitalization rate (P = .008) and time to 1-year rehospitalization (P = .03). Participants with cognitive impairment discharged to a facility had a longer time to rehospitalization (median 142 days) than participants with no cognitive impairment (median 98 days) (hazard ratio (HR) = 0.77, 95% confidence interval (CI) = 0.58-1.02, P = .07), whereas participants with cognitive impairment discharged to home had a slightly shorter time to rehospitalization (median 182 days) than those without cognitive impairment (median 224 days) (HR = 1.15, 95% CI = 0.92-1.43, P = .23). These two nonsignificant HRs in opposite directions were significantly different from each other (P = .03). CONCLUSION: Discharge destination modifies the association between cognitive impairment and rehospitalization. Of participants discharged to a facility, those without cognitive impairment had higher rehospitalization rates, whereas the rates were similar between cognitively impaired and intact participants discharged to the community.
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    Neuropathological Correlates of Cumulative Benzodiazepine and Anticholinergic Drug Use
    (IOS Press, 2020-04) Richardson, Kathryn; Wharton, Stephen B.; Grossi, Carlota M.; Matthews, Fiona E.; Fox, Chris; Maidment, Ian; Loke, Yoon K.; Steel, Nicholas; Arthur, Antony; Myint, Phyo Kyaw; Boustani, Malaz; Campbell, Noll; Robinson, Louise; Brayne, Carol; Savva, George M.; Medicine, School of Medicine
    Background:Benzodiazepines and anticholinergic drugs have been implicated in causing cognitive decline and potentially increasing dementia risk. However, evidence for an association with neuropathology is limited. Objective:To estimate the correlation between neuropathology at death and prior use of benzodiazepines and anticholinergic drugs. Methods:We categorized 298 brain donors from the population-based Medical Research Council Cognitive Function and Ageing Study, according to their history of benzodiazepine (including Z-drugs) or anticholinergic medication (drugs scoring 3 on the Anticholinergic Cognitive Burden scale) use. We used logistic regression to compare dichotomized neuropathological features for those with and without history of benzodiazepine and anticholinergic drug use before dementia, adjusted for confounders. Results:Forty-nine (16%) and 51 (17%) participants reported benzodiazepine and anticholinergic drug use. Alzheimer’s disease neuropathologic change was similar whether or not exposed to either drug, for example 46% and 57% had intermediate/high levels among those with and without anticholinergic drug use. Although not significant after multiple testing adjustments, we estimated an odds ratio (OR) of 0.40 (95% confidence interval [95% CI] 0.18–0.87) for anticholinergic use and cortical atrophy. For benzodiazepine use, we estimated ORs of 4.63 (1.11–19.24) and 3.30 (1.02–10.68) for neuronal loss in the nucleus basalis and substantial nigra. There was evidence of neuronal loss in the nucleus basalis with anticholinergic drug use, but the association reduced when adjusted for confounders. Conclusions:We found no evidence that benzodiazepine or anticholinergic drug use is associated with typical pathological features of Alzheimer’s disease; however, we cannot rule out effects owing to small numbers.
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    Relationship between Angiotensin Converting Enzyme Inhibitors and Angiotensin Receptor Blockers Prescribing and Delirium in the ICU-A Secondary Analysis
    (Wiley, 2023) Mulkey, Malissa A.; Khan, Sikandar; Perkins, Anthony; Gao, Sujuan; Wang, Sophia; Campbell, Noll; Khan, Babar; Medicine, School of Medicine
    Background: Studies suggest Angiotensin-Converting Enzyme inhibitors (ACEI) and Angiotensin Receptor Blockers (ARB) may slow the decline of memory function in individuals with mild to moderate Alzheimer's disease by regulating migroglial activation and oxidative stress within the brain's reticular activating system. Therefore, we evaluated the relationship between delirium prevalence and being prescribed ACEI and ARB in participants admitted to the intensive care units (ICU). Methods: A secondary analysis of data from two parallel pragmatic randomized controlled trials was performed. ACEI and ARB exposure was defined as being prescribed an ACEI or an ARB within six months prior to the ICU admission. The primary endpoint was the first positive delirium assessment based on Confusion Assessment Method for the ICU (CAM-ICU) for up to thirty days. Results: A total of 4791 patients admitted to the medical, surgical, and progressive ICU and screened for eligibility for the parent studies between February 2009 and January 2015 from two level 1 trauma and one safety net hospital in a large urban academic health system were included. Delirium rates in the ICU were not significantly different among participants with no exposure to ACEI/ARB (12.6%), or exposure to ACEI (14.4%), ARB (11.8%), or ACEI and ARB in combination (15.4%) in six months prior to the ICU admission. Exposure to ACEI (OR = 0.97[0.77, 1.22]), ARB (OR = 0.70 [0.47, 1.05]), or both (OR = 0.97 [0.33, 2.89]) in six months prior to ICU admission was not significantly associated with odds of delirium during the ICU admission after adjusting for age, gender, race, co-morbidities, and insurance status. Conclusions: While the impact of ACEI and ARB exposure prior to the ICU admission was not associated with the prevalence of delirium in this study, further research is needed to fully understand the impact of antihypertensive medications on delirium.
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    User Personas to Guide Technology Intervention Design to Support Caregiver-Assisted Medication Management
    (Oxford, 2022-11) Linden, Anna; Loganathar, Priya; Holden, Richard; Boustani, Malaz; Campbell, Noll; Ganci, Aaron; Werner, Nicole; Herron School of Art
    Informal caregivers often help manage medications for people with ADRD. Caregiver-assisted medication management has the potential to optimize outcomes for caregivers and people with ADRD, but is often associated with suboptimal outcomes. We used the user-centered design persona method to represent the needs of ADRD caregivers who manage medications for people with ADRD to guide future design decisions for technology interventions. Data were collected through virtual contextual inquiry in which caregivers (Nf24) sent daily multimedia text messages depicting medication management activities for seven days each, followed by an interview that used the messages as prompts to understand medication management needs. We applied the persona development method to the data to identify distinct caregiver personas, i.e., evidence-derived groups of prospective users of a future intervention. We used team-based affinity diagramming to organize information about participants based on intragroup (dis)similarities, to create meaningful clusters representing intervention-relevant attributes. We then used group consensus discussion to create personas based on attribute clusters. The six identified attributes differentiating personas were: 1. medication acquisition, 2. medication organization, 3. medication administration, 4. monitoring symptoms, 5. care network, 6. technology preferences. Three personas were identified based on differences on those attributes: Regimented Ruth (independent, proactive, tech savvy, controls all medications), Intuitive Ian (collaborative, uses own judgment, some technology, provides some medication autonomy), Passive Pamela (reactive, easy going, technology novice, provides full medication autonomy). These personas can be used to guide technology intervention design by evaluating how well intervention designs support each of them.
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    Using Agile Methodology and Nudge Strategies to Improve Enrollment in Clinical Trials
    (Oxford University Press, 2022-12-20) Bylund, Peggy; Mehta, Jade; Mathavan, Nandini; Trowbridge, Kimberly; Taylor, Britain; El Sharu, Husam; Campbell, Noll; Medicine, School of Medicine
    The enrollment of human subjects is crucial for the success of clinical trials. In the ongoing “Reducing the Risk of Dementia through Deprescribing” trial, the initial approach for enrolling subjects did not meet expected goals in the first 6 months, creating the need for innovative nudge strategies. We used an Agile methodology as the framework to understand the problem, then find and implement a solution. Our study aimed to examine the effectiveness of utilizing a texting nudge to enhance post-agreement recruitment of subjects with cognitive impairments. Prior to enrollment, eligible potential participants were contacted using a texting nudge. Potential participants received a second contact call to remind subjects of the enrollment appointment, introduce the person and the phone number that would call them, and the option of confirming or rescheduling. During the 1-week text-message experiment, 8 out of 9 subjects who agreed to participate in the study and received the text message enrolled, yielding an 89% post-agreement enrollment rate compared to a baseline rate of 44% prior to introducing this nudge. After implementing into the standard operating procedures, the 6-month average rate of enrollment among those that agreed rose to 80%, nearly doubling the rate from the first 6 months of the study and quadrupling the number enrolled each month. Inadequate recruitment has necessitated the use of innovative recruitment methods. Using the Agile problem-solving mindset, the texting nudge was developed to leverage the behavioral influences of the messenger, social commitments, priming and affect to increase subject enrollment.