Systematic review of comorbidity indices for administrative data

Analgesia and Sedation Use During Noninvasive Ventilation for Acute Respiratory Failure

OBJECTIVES

To describe U.S. practice regarding administration of sedation and analgesia to patients on noninvasive ventilation (NIV) for acute respiratory failure (ARF) and to determine the association of this practice with odds of intubation or death.

DESIGN

A retrospective multicenter cohort study.

SETTING

A total of 1017 hospitals contributed data between January 2010 and September 2020 to the Premier Healthcare Database, a nationally representative healthcare database in the United States.

PATIENTS

Adult (≥ 18 yr) patients admitted to U.S. hospitals requiring NIV for ARF.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We identified 433,357 patients on NIV of whom (26.7% [95% CI] 26.3%-27.0%) received sedation or analgesia. A total of 50,589 patients (11.7%) received opioids only, 40,646 (9.4%) received benzodiazepines only, 20,146 (4.6%) received opioids and benzodiazepines, 1.573 (0.4%) received dexmedetomidine only, and 2,639 (0.6%) received dexmedetomidine in addition to opioid and/or benzodiazepine. Of 433,357 patients receiving NIV, 50,413 (11.6%; 95% CI, 11.5-11.7%) patients underwent invasive mechanical ventilation on hospital days 2-5 or died on hospital days 2-30. Intubation was used in 32,301 patients (7.4%; 95% CI, 7.3-7.6%). Further, death occurred in 24,140 (5.6%; 95% CI, 5.5-5.7%). In multivariable analysis adjusting for relevant covariates, receipt of any medication studied was associated with increased odds of intubation or death. In inverse probability weighting, receipt of any study medication was also associated with increased odds of intubation or death (average treatment effect odds ratio 1.38; 95% CI, 1.35-1.40).

CONCLUSIONS

The use of sedation and analgesia during NIV is common. Medication exposure was associated with increased odds of intubation or death. Further investigation is needed to confirm this finding and determine whether any subpopulations are especially harmed by this practice.

Postoperative revision, complication and economic outcomes of patients with reverse or anatomic total shoulder arthroplasty at one year: a retrospective, United States hospital billing database analysis

BACKGROUND

Data on the 1-year postoperative revision, complication, and economic outcomes in a hospital setting after total shoulder arthroplasty (TSA) are sparse.

METHODS

A retrospective cohort study using the Premier Healthcare Database, a hospital-billing data source, evaluated 1-year postoperative revision, complication, and economic outcomes of reverse (RTSA) and anatomic (ATSA) TSA for patients who underwent the procedure from 2015 until 2021. All-cause revisits, including revision-related events (categorized as either irrigation and débridement or revision procedures and device removals) and shoulder/nonshoulder complications were collected. The incidences and costs of these revisits were evaluated. Generalized linear models were used to evaluate the associations between patient characteristics and revision and complication occurrences and costs.

RESULTS

Among 51,478 RTSA and 34,623 ATSA patients (mean [standard deviation] ages RTSA 71.5 [8.1] years, ATSA 66.8 [9.0] years), 1-year adjusted incidences of all-cause revisits, irrigation/débridement, revision procedures/device removals, and shoulder/nonshoulder complications were RTSA: 45.0% (95% confidence interval (CI): 44.6%-45.5%), 0.1% (95% CI: 0.1%-0.2%), 2.1% (95% CI: 2.0%-2.2%), and 17.8% (95% CI: 17.5%-18.1%) and ATSA: 42.3% (95% CI: 41.8%-42.9%), 0.2% (95% CI: 0.1%-0.2%), 1.9% (95% CI: 1.8%-2.1%), and 14.4% (95% CI: 14.0%-14.8%), respectively; shoulder-related complications were RTSA: 12.4% (95% CI: 12.1%-12.7%) and ATSA: 9.9% (95% CI: 9.6%-10.3%). Significant factors associated with a high risk of revisions and complications included, but were not limited to, chronic comorbidities and noncommercial insurance. Per patient, the mean (standard deviations) total 1-year hospital cost was $25,225 ($15,911) and $21,520 ($13,531) for RTSA and ATSA, respectively. Revision procedures and device removals were most costly, averaging $22,920 ($18,652) and $26,911 ($18,619) per procedure for RTSA and ATSA, respectively. Patients with revision-related events with infections had higher total hospital costs than patients without this event (RTSA: $60,887 (95% CI: $56,951-$64,823) and ATSA: $59,478 (95% CI: $52,312-$66,644)), equating to a mean difference of $36,148 with RTSA and $38,426 with ATSA. Significant factors associated with higher costs of revision-related events and complications included age, race, chronic comorbidities, and noncommercial insurance.

CONCLUSIONS

Nearly 45% RTSA and 42% ATSA patients returned to the hospital, most often for shoulder/nonshoulder complications (overall 17.8% RTSA and 14.4% ATSA, and shoulder-related 12.4% RTSA and 9.9% ATSA). Revisions and device removals were most expensive ($22,920 RTSA and $26,911 ATSA). Infection complications requiring revision had the highest 1-year hospital costs (∼$60,000). This study highlights the need for technologies and surgical techniques that may help reduce TSA health care utilization and economic burden.

Retrospective analysis of hospitalization costs using two payment systems: the diagnosis related groups (DRG) and the Queralt system, a newly developed case-mix tool for hospitalized patients

BACKGROUND

Hospital services are typically reimbursed using case-mix tools that group patients according to diagnoses and procedures. We recently developed a case-mix tool (i.e., the Queralt system) aimed at supporting clinicians in patient management. In this study, we compared the performance of a broadly used tool (i.e., the APR-DRG) with the Queralt system.

METHODS

Retrospective analysis of all admissions occurred in any of the eight hospitals of the Catalan Institute of Health (i.e., approximately, 30% of all hospitalizations in Catalonia) during 2019. Costs were retrieved from a full cost accounting. Electronic health records were used to calculate the APR-DRG group and the Queralt index, and its different sub-indices for diagnoses (main diagnosis, comorbidities on admission, andcomplications occurred during hospital stay) and procedures (main and secondary procedures). The primary objective was the predictive capacity of the tools; we also investigated efficiency and within-group homogeneity.

RESULTS

The analysis included 166,837 hospitalization episodes, with a mean cost of € 4,935 (median 2,616; interquartile range 1,011-5,543). The components of the Queralt system had higher efficiency (i.e., the percentage of costs and hospitalizations covered by increasing percentages of groups from each case-mix tool) and lower heterogeneity. The logistic model for predicting costs at pre-stablished thresholds (i.e., 80th, 90th, and 95th percentiles) showed better performance for the Queralt system, particularly when combining diagnoses and procedures (DP): the area under the receiver operating characteristics curve for the 80th, 90th, 95th cost percentiles were 0.904, 0.882, and 0.863 for the APR-DRG, and 0.958, 0.945, and 0.928 for the Queralt DP; the corresponding values of area under the precision-recall curve were 0.522, 0.604, and 0.699 for the APR-DRG, and 0.748, 0.7966, and 0.834 for the Queralt DP. Likewise, the linear model for predicting the actual cost fitted better in the case of the Queralt system.

CONCLUSIONS

The Queralt system, originally developed to predict hospital outcomes, has good performance and efficiency for predicting hospitalization costs.

Colorectal Cancer Screening Among Individuals With a Substance Use Disorder: A Retrospective Cohort Study

Introduction

There is limited evidence on colorectal cancer screening among individuals with a substance use disorder. This study aims to investigate the association between personal history of a substance use disorder and colorectal cancer colonoscopy screening completion rates.

Methods

This retrospective cohort study analyzed 176,300 patients, of whom 171,973 had no substance use disorder and 4,327 had a substance use disorder diagnosis from electronic health record data (January 1, 2008-December 31, 2022) in a Midwestern healthcare system. Baseline was January 1, 2013, and a 10-year follow-up period ran through December 31, 2022. The outcome was receipt of colonoscopy in the 10-year follow-up period. Patients were aged 50-65 years at baseline, meaning that they were eligible for a colonoscopy through the entirety of the 10-year follow-up period. Covariates included demographics (age, race, and neighborhood SES), health services utilization, psychiatric and physical comorbidities, and prior colonoscopy or fecal occult blood testing. Entropy balancing was used to control for confounding in weighted log-binomial models calculating RR and 95% CIs.

Results

Patients were on average aged 57.1 (±4.5) years, 58.2% were female, 81.0% were White, and 16.9% were of Black race. The most prevalent comorbidities were obesity (29.6%) and hypertension (29.4%), followed by smoking/nicotine dependence (21.0%). The most prevalent psychiatric comorbidity was depression (6.4%), followed by anxiety disorder (4.5%). During the 10-year follow-up period, 40.3% of eligible patients completed a colorectal cancer colonoscopy screening test, and individuals with a substance use disorder diagnosis were significantly less likely to receive a colorectal cancer colonoscopy screening test both prior to and after controlling for confounding (RR=0.73; 95% CI=0.70, 0.77 and RR=0.81; 95% CI=0.74, 0.89, respectively). Results were not modified by sex, race, psychiatric comorbidity, or neighborhood SES.

Conclusions

Personal history of substance use disorder was independently associated with lower screening completion rates. Healthcare professionals should recognize unique barriers among individuals with substance use disorder and then address them individually as a multidisciplinary team in the outpatient setting to reduce this health disparity.

Depression and Time to Knee Arthroplasty Among Adults Who Have Knee Osteoarthritis

BACKGROUND

Depression is common in osteoarthritis (OA) and is associated with poor outcomes following total knee arthroplasty (TKA). Depression can increase pain sensitivity and may be related to an increased likelihood of TKA.

METHODS

Nationally distributed electronic health record data from 2010 to 2018 were used to identify eligible patients (n = 9,466) who had knee OA and were 45 to 80 years of age. Cox proportional hazard models were computed to estimate the association between depression and incident TKA for all patients and by age group (45 to 54, 55 to 64, and 65 to 80 years of age). Confounding was controlled using entropy balancing. Sensitivity analyses determined if the association between depression and TKA differed when depression occurred in the 12 months occurring 90, 60, 30, and 0 days lag time before TKA.

RESULTS

The mean age of the sample was 63 (range, 45 to 80), 64.0% were women, 83.3% were White race, and approximately 50% resided in the Midwest. There was no association between depression and incident TKA (hazard ratio = 0.97; confidence interval = 0.81 to 1.16]). Results did not differ in age-stratified analyses. Sensitivity analyses revealed a higher percentage of TKA among depressed versus nondepressed patients (24.2 versus 21.6%; P = .028) when the patient's depression diagnosis was established in the 12 months with no lag time before TKA.

CONCLUSIONS

Patients who have knee OA and comorbid depression, compared to those who have only knee OA, do not have an increased likelihood of TKA. The multifactorial, complex decision to obtain TKA does not appear to be influenced by depression, but depression is a common comorbidity.

Predicting short- to medium-term care home admission risk in older adults: a systematic review of externally validated models

INTRODUCTION

Predicting risk of care home admission could identify older adults for early intervention to support independent living but require external validation in a different dataset before clinical use. We systematically reviewed external validations of care home admission risk prediction models in older adults.

METHODS

We searched Medline, Embase and Cochrane Library until 14 August 2023 for external validations of prediction models for care home admission risk in adults aged ≥65 years with up to 3 years of follow-up. We extracted and narratively synthesised data on study design, model characteristics, and model discrimination and calibration (accuracy of predictions). We assessed risk of bias and applicability using Prediction model Risk Of Bias Assessment Tool.

RESULTS

Five studies reporting validations of nine unique models were included. Model applicability was fair but risk of bias was mostly high due to not reporting model calibration. Morbidities were used as predictors in four models, most commonly neurological or psychiatric diseases. Physical function was also included in four models. For 1-year prediction, three of the six models had acceptable discrimination (area under the receiver operating characteristic curve (AUC)/c statistic 0.70-0.79) and the remaining three had poor discrimination (AUC < 0.70). No model accounted for competing mortality risk. The only study examining model calibration (but ignoring competing mortality) concluded that it was excellent.

CONCLUSIONS

The reporting of models was incomplete. Model discrimination was at best acceptable, and calibration was rarely examined (and ignored competing mortality risk when examined). There is a need to derive better models that account for competing mortality risk and report calibration as well as discrimination.

Association Between Coronary Artery Disease Testing in Patients with New-Onset Heart Failure and Heart Failure Readmission and Mortality

BACKGROUND

In patients with new-onset heart failure (HF), coronary artery disease (CAD) testing remains underutilized. Whether widespread CAD testing in patients with new-onset HF leads to improved outcomes remains to be determined.

OBJECTIVE

We sought to examine whether CAD testing, and its timing, among patients hospitalized with new-onset HF with reduced ejection fraction (HFrEF), is associated with improved outcomes.

DESIGN

Retrospective cohort study.

PARTICIPANTS

Adult (≥ 18 years) non-pregnant patients with new-onset HFrEF hospitalized within one of 15 Kaiser Permanente Southern California medical centers between 2016 and 2021. Key exclusion criteria included history of heart transplant, hospice, and a do-not-resuscitate order.

MAIN MEASURES

Primary outcome was a composite of HF readmission or all-cause mortality through end of follow-up on 12/31/2022.

KEY RESULTS

Among 2729 patients hospitalized with new-onset HFrEF, 1487 (54.5%) received CAD testing. The median age was 66 (56-76) years old, 1722 (63.1%) were male, and 1074 (39.4%) were White. After a median of 1.8 (0.6-3.4) years, the testing group had a reduced risk of HF readmission or all-cause mortality (aHR [95%CI], 0.71 [0.63-0.79]). These results were consistent across subgroups by history of atrial fibrillation, diabetes, renal disease, myocardial infarction, and elevated troponin during hospitalization. In a secondary analysis where CAD testing was further divided to early (received testing before discharge) and late testing (up to 90 days after discharge), there was no difference in late vs early testing (0.97 [0.81-1.16]).

CONCLUSIONS

In a contemporary and diverse cohort of patients hospitalized with new-onset HFrEF, CAD testing within 90 days of hospitalization was associated with a lower risk of HF readmission or all-cause mortality. Testing within 90 days after discharge was not associated with worse outcomes.

Baseline Characteristics From a New Longitudinal Cohort of Patients With Noncancer Pain and Chronic Opioid Use in the United States

Retrospective cohort studies have consistently observed that long-term prescription opioid use is a risk factor for new major depressive episodes. However, prospective studies are needed to confirm these findings and establish evidence for causation. The Prescription Opioids and Depression Pathways cohort study is designed for this purpose. The present report describes the baseline sample and associations between participant characteristics and odds of daily versus nondaily opioid use. Second, we report associations between participant characteristics and odds of depression, dysthymia, anhedonia, and vital exhaustion. Patients with noncancer pain were eligible if they started a new period of prescription opioid use lasting 30 to 90 days. Participants were 54.8 (standard deviation ± 11.3) years of age, 57.3% female and 73% White race. Less than college education was more common among daily versus nondaily opioid users (32.4% vs 27.3%; P = .0008), as was back pain (64.2% vs 51.3%; P < .0001), any nonopioid substance use disorder (12.8% vs 4.8%; P < .0001), and current smoking (30.7% vs 18.4% P < .0001). High pain interference (50.9% vs 28.4%; P < .0001) was significantly associated with depression, as was having more pain sites (6.9 ± 3.6 vs 5.7 ± 3.6; P < .0001), and benzodiazepine comedication (38.2% vs 23.4%; P < .0001). High pain interference was significantly more common among those with anhedonia (46.8% vs 27.4%; P < .0001), and more pain sites (7.0 ± 3.7 vs 5.6 ± 3.6; P < .0001) were associated with anhedonia. Having more pain sites (7.9 ± 3.6 vs 5.5 ± 3.50; P < .0001) was associated with vital exhaustion, as was back pain (71.9% vs 56.8%; P = .0001) and benzodiazepine comedication (42.8% vs 22.8%; P < .0001). Patients using prescription opioids for noncancer pain have complex pain, psychiatric, and substance use disorder comorbidities. Longitudinal data will reveal whether long-term opioid therapy leads to depression or other mood disturbances such as anhedonia and vital exhaustion. PERSPECTIVE: This study reports baseline characteristics of a new prospective, noncancer pain cohort study. Risk factors for adverse opioid outcomes were most common in those with depression and vital exhaustion and less common in dysthymia and anhedonia. Baseline data highlight the complexity of patients receiving long-term opioid therapy for noncancer pain.

Effectiveness and safety of early treatment with spironolactone for new-onset acute heart failure

BACKGROUND

The effectiveness and safety of mineralocorticoid receptor antagonists (MRA) in acute heart failure (HF) is uncertain. We sought to describe the prescription of spironolactone during acute HF and whether early treatment is effective and safe in a real-world setting.

METHODS

We performed a retrospective cohort study of adult (≥18 years) nonpregnant patients hospitalized with new-onset HF with reduced ejection fraction (HFrEF, defined by ejection fraction ≤40%) within 15 Kaiser Permanente Southern California medical centers between 2016 and 2021. Early treatment was defined by spironolactone prescription at discharge. The primary effectiveness outcome was a composite of HF readmission or all-cause mortality at 180 days. Safety outcomes were hypotension and hyperkalemia at 90 days.

RESULTS

Among 2318 HFrEF patients, 368 (15.9%) were treated with spironolactone at discharge. After 1:2 propensity score matching, 354 early treatment and 708 delayed/no treatment patients were included in the analysis. The median age was 63 (IQR: 52-74) years; 61.6% were male, and 38.6% were White. By 90 days, ~20% had crossed over in the two groups. Early treatment was not associated with the composite outcome at 180 days (HR [95% CI]: 0.81 [0.56-1.17]), but a trend towards benefit by 365 days that did not reach statistical significance (0.78 [0.58-1.06]). Early treatment was also associated with hyperkalemia (subdistribution HR [95% CI]: 2.33 [1.30-4.18]) but not hypotension (0.93 [0.51-1.72]).

CONCLUSIONS

Early treatment with spironolactone at discharge for new-onset HFrEF in a real-world setting did not reduce the risk of HF readmission or mortality in the first year after discharge. The risk of hyperkalemia was increased.

Comparing Charlson Comorbidity Index Scores between Anesthesiologists, Patients, and Administrative Data: A Prospective Observational Study

(1) Background: Patients' comorbidities play an immanent role in perioperative risk assessment. It is unknown how Charlson Comorbidity Indices (CCIs) from different sources compare. (2) Methods: In this prospective observational study, we compared the CCIs of patients derived from patients' self-reports and from physicians' assessments with hospital administrative data. (3) Results: The data of 1007 patients was analyzed. Agreement between the CCI from patients' self-report compared to administrative data was fair (kappa 0.24 [95%CI 0.2-0.28]). Agreement between physicians' assessment and the administrative data was also fair (kappa 0.28 [95%CI 0.25-0.31]). Physicians' assessment and patients' self-report had the best agreement (kappa 0.33 [95%CI 0.30-0.37]). The CCI calculated from the administrative data showed the best predictability for in-hospital mortality (AUROC 0.86 [95%CI 0.68-0.91]), followed by equally good prediction from physicians' assessment (AUROC 0.80 [95%CI 0.65-0.94]) and patients' self-report (AUROC 0.80 [95%CI 0.75-0.97]). (4) Conclusions: CCIs derived from patients' self-report, physicians' assessments, and administrative data perform equally well in predicting postoperative in-hospital mortality.

Real-World Experience of Immune-Checkpoint Inhibitors in Older Patients with Advanced Cutaneous Squamous Cell Carcinoma

BACKGROUND

Older patients are often underrepresented in clinical trials owing to exclusionary comorbidities, which are more common with age. Chemotherapy is poorly tolerated in older comorbid advanced cutaneous squamous cell carcinoma (CSCC) patients; however, little is known on the efficacy and tolerability of immune-checkpoint inhibitors (ICIs) in this population. To our knowledge, this is the largest dedicated report on a cohort of older patients with advanced CSCC treated with immunotherapy to date.

OBJECTIVE

The aim was to report outcomes of ICI use in a real-world older cohort with advanced CSCC.

PATIENTS AND METHODS

A single-centre retrospective audit of all patients treated via an access scheme providing ICIs to patients with advanced CSCC was conducted. Participants were ≥ 70 years of age and had advanced CSCC not amenable to curative surgery or radiotherapy. Best overall response rate (ORR), 12-month overall survival (OS) and progression-free survival (PFS), and toxicity rates were assessed.

RESULTS

A total of 53 patients were analysed. The median age was 81.8 years (range 70.1-96.8); 81% were male; 34% were immunocompromised; and 34% had an Eastern Cooperative Oncology Group (ECOG) performance status score of ≥ 2. The ORR was 57%, and 12-month OS and PFS were 63% (95% confidence interval [CI] 44-78) and 41% (95% CI 25-57), respectively. Thirty-two per cent developed an immune-related adverse event (irAE), but only two patients experienced a grade 3 irAE, with no treatment-related deaths. Higher ECOG score was associated with worse OS and PFS. No significant association was identified for increasing age, sex, Charlson Comorbidity Index score, or immunocompromised status.

CONCLUSIONS

ICIs have demonstrated efficacy and have an acceptable safety profile among older patients with advanced CSCC, with comparable efficacy to what has been demonstrated in current clinical trials.

Performance of models for predicting 1-year to 3-year mortality in older adults: a systematic review of externally validated models

Mortality prediction models support identifying older adults with short life expectancy for whom clinical care might need modifications. We systematically reviewed external validations of mortality prediction models in older adults (ie, aged 65 years and older) with up to 3 years of follow-up. In March, 2023, we conducted a literature search resulting in 36 studies reporting 74 validations of 64 unique models. Model applicability was fair but validation risk of bias was mostly high, with 50 (68%) of 74 validations not reporting calibration. Morbidities (most commonly cardiovascular diseases) were used as predictors by 45 (70%) of 64 of models. For 1-year prediction, 31 (67%) of 46 models had acceptable discrimination, but only one had excellent performance. Models with more than 20 predictors were more likely to have acceptable discrimination (risk ratio [RR] vs <10 predictors 1·68, 95% CI 1·06-2·66), as were models including sex (RR 1·75, 95% CI 1·12-2·73) or predicting risk during comprehensive geriatric assessment (RR 1·86, 95% CI 1·12-3·07). Development and validation of better-performing mortality prediction models in older people are needed.

Unplanned Emergency Department Visits Following Revision Total Joint Arthroplasty: Incidences, Risk Factors, and Mortalities

BACKGROUND

The incidence of unplanned emergency department (ED) visits following revision total joint arthroplasty is an indicator of the quality of postoperative care. The aim of this study was to investigate the incidences, timings, and characteristics of ED visits within 90 days after revision total joint arthroplasty.

METHODS

A retrospective review of 457 consecutive cases, including 254 revision total hip arthroplasty (rTHA) and 203 revision total knee arthroplasty (rTKA) cases, was conducted. Data regarding patient demographics, timings of the ED encounter, chief complaints, readmissions, and diagnoses indicating reoperation were analyzed.

RESULTS

The results showed that 41 patients who had rTHA (16.1%) and 14 patients who had rTKA (6.9%) returned to the ED within 90 days postoperatively. The incidence of ED visits was significantly higher in the rTHA group than in the rTKA group (P = .003). The most common surgery-related complications were dislocation among rTHA patients and wound conditions among rTKA patients. Apart from elevated calculated comorbidity scores, peptic ulcer in rTHA patients and cerebral vascular events and chronic obstructive pulmonary disease in rTKA patients might increase chances of unplanned ED visits. Patients who had ED visits showed significantly higher mortality rates than the others in both rTHA and rTKA cohorts (P = .050 and P = .008, respectively).

CONCLUSIONS

The ED visits within 90 days are more common after rTHA than after rTKA. Patients in both ED visit groups after rTHA and rTKA demonstrated worse survival. Efforts should be made to improve quality of care to prevent ED visits.

Alcohol Withdrawal Severity Measures for Identifying Patients Requiring High-Intensity Care

OBJECTIVES

Alcohol withdrawal syndrome (AWS) may progress to require high-intensity care. Approaches to identify hospitalized patients with AWS who received higher level of care have not been previously examined. This study aimed to examine the utility of Clinical Institute Withdrawal Assessment Alcohol Revised (CIWA-Ar) for alcohol scale scores and medication doses for alcohol withdrawal management in identifying patients who received high-intensity care.

DESIGN

A multicenter observational cohort study of hospitalized adults with alcohol withdrawal.

SETTING

University of Chicago Medical Center and University of Wisconsin Hospital.

PATIENTS

Inpatient encounters between November 2008 and February 2022 with a CIWA-Ar score greater than 0 and benzodiazepine or barbiturate administered within the first 24 hours. The primary composite outcome was patients who progressed to high-intensity care (intermediate care or ICU).

INTERVENTIONS

None.

MAIN RESULTS

Among the 8742 patients included in the study, 37.5% (n = 3280) progressed to high-intensity care. The odds ratio for the composite outcome increased above 1.0 when the CIWA-Ar score was 24. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) at this threshold were 0.12 (95% CI, 0.11-0.13), 0.95 (95% CI, 0.94-0.95), 0.58 (95% CI, 0.54-0.61), and 0.64 (95% CI, 0.63-0.65), respectively. The OR increased above 1.0 at a 24-hour lorazepam milligram equivalent dose cutoff of 15 mg. The sensitivity, specificity, PPV, and NPV at this threshold were 0.16 (95% CI, 0.14-0.17), 0.96 (95% CI, 0.95-0.96), 0.68 (95% CI, 0.65-0.72), and 0.65 (95% CI, 0.64-0.66), respectively.

CONCLUSIONS

Neither CIWA-Ar scores nor medication dose cutoff points were effective measures for identifying patients with alcohol withdrawal who received high-intensity care. Research studies for examining outcomes in patients who deteriorate with AWS will require better methods for cohort identification.

Impact of multimorbidity on the first ts/bDMARD effectiveness and retention rate after two years of follow-up in patients with rheumatoid arthritis from the BIOBADASER registry

BACKGROUND

Patients with Rheumatoid Arthritis (RA) have a higher prevalence of comorbidities compared to the general population. However, the implications of multimorbidity on therapeutic response and treatment retention remain unexplored.

OBJECTIVES

(a) To evaluate the impact of multimorbidity on the effectiveness of the first targeted synthetic or biologic disease-modifying antirheumatic drug (ts/bDMARD), in patients with RA after 2-year follow-up; (b) to investigate the influence of multimorbidity on treatment retention rate.

METHODS

Patients with RA from the BIOBADASER registry exposed to a first ts/bDMARDs were included. Patients were categorized based on multimorbidity status at baseline, defined as a Charlson Comorbidity index (CCI) score ≥ 3. A linear regression model, adjusted for sex and age, was employed to compare the absolute DAS28 score over time after ts/bDMARD initiation between the two groups. The Log-Rank test and Kaplan-Meier curve were used to compare the retention rates of the first ts/bDMARD between the groups.

RESULTS

A total of 1128 patients initiating ts/bDMARD were included, with 107 (9.3%) exhibiting multimorbidity. The linear regression model showed significantly higher DAS28 (beta coefficient 0.33, 95%CI:0.07-0.58) over a two-year period in patients with multimorbidity, even after adjusting for age and sex. Finally, no differences in the ts/bDMARD retention rate were found between groups (median 6.94-6.96 years in CCI < 3 vs. 5.68-5.62 in CCI ≥ 3; p = 0.610).

CONCLUSIONS

Multimorbidity in patients with RA was associated with greater DAS28 scores within the first two years after ts/bDMARD initiation, in comparison with patients without multimorbidity. A slightly shorter retention rate was found in patients with multimorbidity, although the difference was non-significant.

The validity of electronic health data for measuring smoking status: a systematic review and meta-analysis

BACKGROUND

Smoking is a risk factor for many chronic diseases. Multiple smoking status ascertainment algorithms have been developed for population-based electronic health databases such as administrative databases and electronic medical records (EMRs). Evidence syntheses of algorithm validation studies have often focused on chronic diseases rather than risk factors. We conducted a systematic review and meta-analysis of smoking status ascertainment algorithms to describe the characteristics and validity of these algorithms.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. We searched articles published from 1990 to 2022 in EMBASE, MEDLINE, Scopus, and Web of Science with key terms such as validity, administrative data, electronic health records, smoking, and tobacco use. The extracted information, including article characteristics, algorithm characteristics, and validity measures, was descriptively analyzed. Sources of heterogeneity in validity measures were estimated using a meta-regression model. Risk of bias (ROB) in the reviewed articles was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

RESULTS

The initial search yielded 2086 articles; 57 were selected for review and 116 algorithms were identified. Almost three-quarters (71.6%) of algorithms were based on EMR data. The algorithms were primarily constructed using diagnosis codes for smoking-related conditions, although prescription medication codes for smoking treatments were also adopted. About half of the algorithms were developed using machine-learning models. The pooled estimates of positive predictive value, sensitivity, and specificity were 0.843, 0.672, and 0.918 respectively. Algorithm sensitivity and specificity were highly variable and ranged from 3 to 100% and 36 to 100%, respectively. Model-based algorithms had significantly greater sensitivity (p = 0.006) than rule-based algorithms. Algorithms for EMR data had higher sensitivity than algorithms for administrative data (p = 0.001). The ROB was low in most of the articles (76.3%) that underwent the assessment.

CONCLUSIONS

Multiple algorithms using different data sources and methods have been proposed to ascertain smoking status in electronic health data. Many algorithms had low sensitivity and positive predictive value, but the data source influenced their validity. Algorithms based on machine-learning models for multiple linked data sources have improved validity.

Combining the Hospital Frailty Risk Score With the Charlson and Elixhauser Multimorbidity Indices to Identify Older Patients at Risk of Poor Outcomes in Acute Care

OBJECTIVE

The Hospital Frailty Risk Score (HFRS) can be applied to medico-administrative datasets to determine the risks of 30-day mortality and long length of stay (LOS) in hospitalized older patients. The objective of this study was to compare the HFRS with Charlson and Elixhauser comorbidity indices, used separately or combined.

DESIGN

A retrospective analysis of the French medical information database. The HFRS, Charlson index, and Elixhauser index were calculated for each patient based on the index stay and hospitalizations over the preceding 2 years. Different constructions of the HFRS were considered based on overlapping diagnostic codes with either Charlson or Elixhauser indices. We used mixed logistic regression models to investigate the association between outcomes, different constructions of HFRS, and associations with comorbidity indices.

SETTING

743 hospitals in France.

PARTICIPANTS

All patients aged 75 years or older hospitalized as an emergency in 2017 (n=1,042,234).Main outcome measures: 30-day inpatient mortality and LOS >10 days.

RESULTS

The HFRS, Charlson, and Elixhauser indices were comparably associated with an increased risk of 30-day inpatient mortality and long LOS. The combined model with the highest c-statistic was obtained when associating the HFRS with standard adjustment and Charlson for 30-day inpatient mortality (adjusted c-statistics: HFRS=0.654; HFRS + Charlson = 0.676) and with Elixhauser for long LOS (adjusted c-statistics: HFRS= 0.672; HFRS + Elixhauser =0.698).

CONCLUSIONS

Combining comorbidity indices and HFRS may improve discrimination for predicting long LOS in hospitalized older people, but adds little to Charlson's 30-day inpatient mortality risk.

Impact of emergency department length of stay on in-hospital mortality: a retrospective cohort study

BACKGROUND AND IMPORTANCE

Emergency Department (ED) workload may lead to ED crowding and increased ED length of stay (LOS). ED crowding has been shown to be associated with adverse events and increasing mortality. We hypothesised that ED-LOS is associated with mortality.

OBJECTIVE

To study the relationship between ED-LOS and in-hospital mortality.

DESIGN

Observational retrospective cohort study.

SETTINGS AND PARTICIPANTS

From 1 January 2015 to 30 September 2018, all visits by patients aged 15 or older to one of the two ED at Toulouse University Hospital were screened. Patients admitted to the hospital after ED visits were included. Visits followed by ED discharge, in-ED death or transfer to ICU or another hospital were not included.

OUTCOME MEASURE AND ANALYSIS

The primary outcome was 30-day in-hospital mortality. ED-LOS was defined as time from ED registration to inpatient admission. ED-LOS was categorised according to quartiles [<303 min (Q1), between 303 and 433 minutes (Q2), between 434 and 612 minutes (Q3) and >612 min (Q4)]. A multivariable logistic regression tested the association between ED-LOS and in-hospital mortality.

MAIN RESULTS

A total of 49 913 patients were admitted to our hospital after ED visits and included in the study. ED-LOS was not independently associated with in-hospital mortality. Compared to ED-LOS < 303 min (Q1, reference), odd-ratios (OR) [95% CI] of in-hospital mortality for Q2, Q3, and Q4 were respectively 0.872 [0.747-1.017], 0.906 [0.777-1.056], and 1.137 [0.985-1.312]. Factors associated to in-hospital mortality were: aged over 75 years (OR [95% CI] = 4.3 [3.8-4.9]), Charlson Comorbidity Index score > 1 (OR [95% CI] = 1.3 [1.1-1.5], and 2.2 [1.9-2.5] for scores 2 and ≥ 3 respectively), high acuity at triage (OR [95% CI] = 3.9 [3.5-4.4]), ED visit at Hospital 1 (OR [95% CI] = 1.6 [1.4-1.7]), and illness diagnosis compared to trauma (OR [95% CI] = 2.1 [1.7-2.6]). Night-time arrival was associated with decreased in-hospital mortality (OR [95% CI] = 0.852 [0.767-0.947]).

CONCLUSION

In this retrospective cohort study, there was no independent association between ED-LOS before admission to general non-ICU wards and in-patient mortality.

Using the Functional Comorbidity Index with administrative workers' compensation data: Utility, validity, and caveats

BACKGROUND

Chronic health conditions impact worker outcomes but are challenging to measure using administrative workers' compensation (WC) data. The Functional Comorbidity Index (FCI) was developed to predict functional outcomes in community-based adult populations, but has not been validated for WC settings. We assessed a WC-based FCI (additive index of 18 conditions) for identifying chronic conditions and predicting work outcomes.

METHODS

WC data were linked to a prospective survey in Ohio (N = 512) and Washington (N = 2,839). Workers were interviewed 6 weeks and 6 months after work-related injury. Observed prevalence and concordance were calculated; survey data provided the reference standard for WC data. Predictive validity and utility for control of confounding were assessed using 6-month work-related outcomes.

RESULTS

The WC-based FCI had high specificity but low sensitivity and was weakly associated with work-related outcomes. The survey-based FCI suggested more comorbidity in the Ohio sample (Ohio mean = 1.38; Washington mean = 1.14), whereas the WC-based FCI suggested more comorbidity in the Washington sample (Ohio mean = 0.10; Washington mean = 0.33). In the confounding assessment, adding the survey-based FCI to the base model moved the state effect estimates slightly toward null (<1% change). However, substituting the WC-based FCI moved the estimate away from null (8.95% change).

CONCLUSIONS

The WC-based FCI may be useful for identifying specific subsets of workers with chronic conditions, but less useful for chronic condition prevalence. Using the WC-based FCI cross-state appeared to introduce substantial confounding. We strongly advise caution-including state-specific analyses with a reliable reference standard-before using a WC-based FCI in studies involving multiple states.

Incidence of acute kidney injury (AKI) and its impact on patient outcomes among adult hospitalized patients with carbapenem-resistant Gram-negative infections who received targeted treatment with a newer β-lactam or β-lactam/β-lactamase inhibitor-, polymyxin- or aminoglycoside-containing regimen

BACKGROUND

Limited comparative data exist on acute kidney injury (AKI) risk and AKI-associated outcomes in hospitalized patients with carbapenem-resistant Gram-negative infections (CR-GNIs) treated with a newer β-lactam/β-lactam-β-lactamase inhibitor (BL/BL-BLI)-, polymyxin (PB)- or aminoglycoside (AG)-containing regimen. This study quantified the risk of AKI and AKI-related outcomes among patients with CR-GNIs treated with a newer BL/BL-BLI-, PB- or AG-containing regimen.

METHODS

A multicentre, retrospective, observational study was performed (2016-20). The study included adult hospitalized patients with (i) baseline estimated glomerular filtration rates ≥30 mL/min/1.73 m2; (ii) CR-GN pneumonia, complicated urinary tract infection or bloodstream infection; and (iii) receipt of newer BL/BL-BLI, PG or AG within 7 days of index CR-GN culture for ≥3 days. Outcomes included AKI, in-hospital mortality and hospital costs.

RESULTS

The study included 750 patients and most (48%) received a newer BL/BL-BLI. The median (IQR) treatment duration was 8 (5-11), 5 (4-8) and 7 (4-8) days in the newer BL/BL-BLI group, AG group and PB group, respectively. The PB group had the highest adjusted AKI incidence (95% CI) (PB: 25.1% (15.6%-34.6%) versus AG: 8.9% (5.7%-12.2%) versus newer BL/BL-BLI: 11.9% (8.1%-15.7%); P = 0.001). Patients with AKI had significantly higher in-hospital mortality (AKI: 18.5% versus 'No AKI': 5.6%; P = 0.001) and mean hospital costs (AKI: $49 192 versus 'No AKI': $38,763; P = 0.043).

CONCLUSIONS

The AKI incidence was highest among PB patients and patients with AKI had worse outcomes. Healthcare systems should consider minimizing the use of antibiotics that augment AKI risk as a measure to improve outcomes in patients with CR-GNIs.

Systemic Inflammatory Response Syndrome and Prosthetic Joint Infection

BACKGROUND

The development of systemic inflammatory response syndrome (SIRS) criteria leads to increased mortality. Little is known about development of SIRS in patients who have prosthetic joint infection (PJI). We aimed to determine the incidence, risk factors, clinical outcomes, and causative organisms in patients who develop SIRS with PJI.

METHODS

We retrospectively identified 655 patients (321 men, 334 women; 382 total hip, 273 total knee) who have hip or knee PJI at 1 institution between July 1, 2015 and December 31, 2020. We formed 2 groups: patients who have SIRS alert (PJI + SIRS) and patients who do not have SIRS alert (PJI). We analyzed clinical outcomes, comorbidities, and operating room culture results.

RESULTS

Of 655 patients, 63 developed SIRS with PJI (9.6%). Intensive care unit (ICU) admission rates (27.0 versus. 6.9%, P < .001) and length of stay (7.7 versus. 5.6 days, P = .003) were greater in PJI + SIRS. At 2 years, reoperation (36.5 versus. 22.3%, P = .01) and mortality rates (17.5 versus. 8.8%, P = .03) were greater in PJI + SIRS. Risk factors included deficiency anemia (P = .001), blood loss anemia (P = .013), uncomplicated diabetes (P = .006), diabetes with complication (P = .001), electrolyte disorder (P < .00001), neurological disorder (P = .0001), paralysis (P = .026), renal failure (P = .005), and peptic ulcer disease (P = .004). Staphylococcus aureus more commonly speciated on tissue cultures in PJI + SIRS (P = .002).

CONCLUSION

The incidence of SIRS is 10% among patients who have PJI. Development of PJI + SIRS is associated with increased lengths of stay, ICU admissions, and 2-year reoperation and mortality rates. Identifying certain comorbidities can stratify patients' risk of developing PJI + SIRS.

Hospital frailty risk score is superior to legacy comorbidity indices for risk adjustment of in-hospital cirrhosis cases

Background & Aims

The hospital frailty risk score (HFRS) identifies older patients at risk of poor outcomes and may have value in cirrhosis. We compared the Charlson (CCI), Elixhauser (ECI), and cirrhosis (CirCom) comorbidity indices with the HFRS in predicting outcomes for cirrhosis hospitalisations.

Methods

Using the National Inpatient Sample (quarter 4 of 2015-2019), we analysed cirrhosis hospitalisations. For each index, we described the prevalence of comorbid conditions and inpatient mortality. We compared the ability of CCI, ECI, CirCom, and HFRS to predict inpatient mortality. Raw and adjusted models predicting inpatient mortality were compared using the area under the receiver operating characteristic curve and the Akaike information criterion.

Results

The cohort's (N = 626,553) median age was 61 years (IQR 52-68 years), 60% were male, cirrhosis was caused by alcohol in 43%, and 38% had ascites. The median comorbidity scores are as follows: ECI 4 (IQR 3-6), CCI 5 (IQR 4-8), and HFRS 5.6 (IQR 3.0-8.6). The most common CirCom score was 0 + 0 (44%). Across the range of values of each index, we observed different mortality ranges: CCI 1.9-13.1%, ECI 3.2-8.7%, CirCom 4.9-13.8%, and HFRS 1.0-15.2%. An adjusted model with HFRS had the highest area under the receiver operating characteristic curve in predicting mortality (HFRS 0.782 vs. ECI 0.689, CCI 0.695, and CirCom 0.692). We observed substantial variation in mortality with HFRS within each level of CCI, ECI, and CirCom. For example, for ECI 4, mortality increased from 0.6 to 16.4%, as HFRS increased from 0 to 15.

Conclusions

Comorbidity indices predict inpatient cirrhosis mortality, but HFRS performs better than CCI, ECI, and CirCom. HFRS is an ideal tool for measuring comorbidity burden and disease severity risk adjustment in cirrhosis-related administrative database studies.

Impact and Implications

We compared commonly used comorbidity indices to a more recently described risk score (hospital frailty risk score [HFRS]) in patients with cirrhosis using a national sample of hospital records. Comorbid conditions are common in hospitalised patients with cirrhosis. There is significant variability in mortality across the range of each index. HFRS outperforms the Charlson comorbidity index, Elixhauser comorbidity index, and CirCom (cirrhosis-specific comorbidity scoring system) in predicting inpatient mortality. HFRS is a valuable index for risk adjustment in inpatient administrative database studies.

MDS-Comorbidity Index using register data has prognostic impact in Swedish MDS patients

Comorbidities influence the mortality in patients with myelodysplastic syndromes, and a growing body of evidence suggest that comorbidity history should be used in addition to established prognostic indices. A comorbidity index specific for MDS, the MDS-CI, was introduced a decade ago. In this study we aim to construct an MDS-CI version based on diagnoses from register data only, to expand its use beyond the clinical setting to retrospective and register based studies. We further test this version on a Swedish population-based MDS cohort of 2947 patients, and compare its prognostic accuracy to that of Charlson Comorbidity Index. Our register based MDS-CI divided patients into three risk groups of similar proportions as have been published for the original MDS-CI. Compared to low risk patients, intermediate and high risk patients had 50 % and 70 % higher mortality, respectively. The prognostic value of MDS-CI was equal to that of Charlson comorbidity index. Adding MDS-CI to the established prognostic factors IPSS-R and age increased the prognostic accuracy. In summary, we demonstrate that MDS-CI can be adequately estimated from diagnoses recorded in registers only, and that it is a useful tool in any future study on myelodysplastic syndromes with a need to adjust for comorbidities.

Association of nutritional status and comorbidity with long-term survival among community-dwelling older males

BACKGROUND

Estimates of survival in the older can be of benefit in various facets, particularly in medical and individual decision-making. We aim to validate the value of a combination of nutrition status evaluation and comorbidity assessment in predicting long-term survival among community-dwelling older.

METHODS

The Charlson Comorbidity Index (CCI) was applied for comprehensive evaluation of comorbidities. Participants were classified into CCI score ≤ 2 and ≥ 3 subgroups. Nutritional status was assessed by using Mini Nutritional Assessment-Short Form (MNA-SF) and Geriatric Nutritional Risk Index (GNRI) evaluations. Mortality rates and survival curves over a 5-year period were compared among subgroups classified by CCI and/or MNA-SF/GNRI evaluations.

RESULTS

A total of 1033 elderly male participants were enrolled in this study, with an average age of 79.44 ± 8.61 years. 108 deceased participants (10.5%) were identified during a follow-up of 5 years. Cox proportional hazards regression analysis showed that age, CCI, MNA-SF and GNRI were independent predictors of 5-year all-cause death in this cohort. Compared to those with normal nutrition status and CCI ≤ 2, the subgroup at risk of malnutrition and CCI ≥ 3 had a significantly higher 5-year all-cause mortality rate (HR = 4.671; 95% CI:2.613-8.351 for MNA-SF and HR = 7.268; 95% CI:3.401-15.530 for GNRI; P < 0.001 for both). Receiver operating characteristic curve analysis demonstrated that a combination of either MNA-SF or GNRI with CCI had significantly better performance than CCI, MNA-SF or GNRI alone in predicting all-cause death.

CONCLUSION

The combination of nutritional assessment (MNA-SF or GNRI) with CCI can significantly improve the predictive accuracy of long-term mortality outcomes among community-dwelling older males.

Transplanting candidates with stacked risks negatively affects outcomes

BACKGROUND

Lung transplant (LT) centers are increasingly evaluating patients with multiple risk factors for adverse outcomes. The effects of these stacked risks remains unclear. Our aim was to determine the relationship between the number of comorbidities and post-transplant outcomes.

METHODS

We performed a retrospective cohort study using the National Inpatient Sample (NIS) and UNOS Starfile (USF). We applied a probabilistic matching algorithm using 7 variables (transplant: month, year, and type; recipient: age, sex, race, payer). We matched recipients in the USF to transplant patients in the NIS between 2016 and 2019. The Elixhauser methodology was used to identify comorbidities present on admission. We determined the associations between mortality, length of stay (LOS), total charges, and disposition with comorbidity numbers using penalized cubic splines, Kaplan-Meier, and linear and logistic regression methods.

RESULTS

From 28,484,087 NIS admissions, we identified 1,821 LT recipients. Matches were exact in 76.8% of the cohort. While the remaining cohort had a probability match of ≥0.94. Penalized splines of Elixhauser comorbidity number identified 3 knots defining 3 groups of stacked risk: low (<3), medium (3-6), and high risk (>6). Inpatient mortality increased from low to medium to high-risk categories: (1.6%, 3.9%, and 7.0%; p < 0.001), as did LOS (16, 21, 29 days, p < 0.001), total charges ($553,057, $666,791, $821,641.5; p = 0.004) and discharge to a skilled nursing facility (15%, 20%, 31%; p < 0.001).

CONCLUSIONS

Stacked risks adversely affect post-LT mortality, LOS, charges, and discharge disposition. Further study to understand the details of specific stacked risks is warranted.

Access to Health Care Improves COVID-19 Vaccination and Mitigates Health Disparities Among Medicare Beneficiaries

BACKGROUND

COVID-19 disproportionately impacts the elderly, particularly racial/ethnic minorities and those with low socioeconomic status (SES). These latter groups may also have higher vaccine hesitancy. We aim to evaluate if access to care improves COVID-19 vaccination rates and improves health disparities.

METHODS

We conducted a retrospective cohort study of Medicare patients receiving care in a high-touch capitated network across ten states. We collected type and date of COVID-19 vaccine and demographic and clinical data from the inpatient and outpatient electronic health records and socioeconomic status from the US census. Our primary outcome was completing vaccination using logistic regression.

RESULTS

Our cohort included 93,224 patients enrolled in the network during the study period. Sixty nine percent of all enrolled patients completed full vaccination. Those who completed vaccination did it with Pfizer (46%), Moderna (49%), and Jannsen (4.6%) vaccines. In adjusted models, we found that the following characteristics increased the odds of being vaccinated: being male, increasing age, BMI, and comorbidities, being Black or Hispanic, having had the flu vaccine in 2020, and increasing number of office primary care visits. Living in a neighborhood with higher social deprivation and having dual Medicaid/Medicare enrollment decreased the odds of completing full vaccination.

CONCLUSIONS

Increasing office visit in a high-touch primary care model is associated with higher vaccination rates among elderly populations who belong to racial/ethnic minorities or have low socioeconomic status. However, lower SES and Medicaid populations continue to have difficulty in completing vaccination.

KEY POINTS

• High COVID-19 vaccination rates of minorities enrolled in Medicare can be achieved. • Lower socioeconomic status is associated with completing vaccination. • Increasing office visits can lead to higher vaccination rates.

Treatment for Urinary Incontinence in Women Older Than 65 Years

IMPORTANCE

Urinary incontinence (UI) is common among women older than 65 years and negatively affects quality of life. However, the prevalence of UI treatment and determinants of treatment are largely unknown.

OBJECTIVES

The aim of this study was to identify rates of UI treatment and factors associated with treatment in older women with self-reported UI.

STUDY DESIGN

This is a retrospective cohort analysis of a data set linking UI symptoms from the Nurses' Health Study to Medicare claims. We evaluated use of pharmacotherapy, noninvasive, and procedural treatments for UI within 1 year before symptom survey. For pharmacotherapy, we used multivariable logistic regression to estimate odds ratios (ORs) of UI treatment.

RESULTS

Of the 67,587 Nurses' Health Study respondents, 15,088 had linkage to Medicare, subscribed to part D, and answered UI questions. Of these, 8,332 (55.2%) women reported UI, and 10.9% with UI had a Medicare claim for treatment; pharmacotherapy represented 94.6% of all treatments.On regression analysis, women with more severe and longer-term UI had higher odds of treatment (severe vs slight UI: OR, 3.1; 95% confidence interval [CI], 2.2-4.3) (longer vs new UI: OR, 1.9; 95% CI, 1.5-2.3). Women with mixed (OR, 2.5; 95% CI, 1.9-3.2) or urgency UI (OR, 3.0; 95% CI, 2.2-3.9) had greater odds of treatment compared with women with stress UI.

CONCLUSIONS

We estimate that only approximately 1 in 9 older women with self-reported UI underwent treatment within the year before reporting symptoms, of which pharmacotherapy was the most common UI intervention, and women with more severe and longer duration of symptoms were most often treated.

Clinical Risk Scores to Predict Nonsusceptibility to Trimethoprim-Sulfamethoxazole, Fluoroquinolone, Nitrofurantoin, and Third-Generation Cephalosporin Among Adult Outpatient Episodes of Complicated Urinary Tract Infection

Background

Clinical risk scores were developed to estimate the risk of adult outpatients having a complicated urinary tract infection (cUTI) that was nonsusceptible to trimethoprim-sulfamethoxazole (TMP-SMX), fluoroquinolone, nitrofurantoin, or third-generation cephalosporin (3-GC) based on variables available on clinical presentation.

Methods

A retrospective cohort study (1 December 2017-31 December 2020) was performed among adult members of Kaiser Permanente Southern California with an outpatient cUTI. Separate risk scores were developed for TMP-SMX, fluoroquinolone, nitrofurantoin, and 3-GC. The models were translated into risk scores to quantify the likelihood of nonsusceptibility based on the presence of final model covariates in a given cUTI outpatient.

Results

A total of 30 450 cUTIs (26 326 patients) met the study criteria. Rates of nonsusceptibility to TMP-SMX, fluoroquinolone, nitrofurantoin, and 3-GC were 37%, 20%, 27%, and 24%, respectively. Receipt of prior antibiotics was the most important predictor across all models. The risk of nonsusceptibility in the TMP-SMX model exceeded 20% in the absence of any risk factors, suggesting that empiric use of TMP-SMX may not be advisable. For fluoroquinolone, nitrofurantoin, and 3-GC, clinical risk scores of 10, 7, and 11 predicted a ≥20% estimated probability of nonsusceptibility in the models that included cumulative number of prior antibiotics at model entry. This finding suggests that caution should be used when considering these agents empirically in patients who have several risk factors present in a given model at presentation.

Conclusions

We developed high-performing parsimonious risk scores to facilitate empiric treatment selection for adult outpatients with cUTIs in the critical period between infection presentation and availability of susceptibility results.

Impact of Prediabetes on Cardiac Function Among Primary Care Patients

Background: Prediabetes is a novel risk factor recently associated with changes in the left ventricle. Our aim is to determine if prediabetes is associated with heart failure (HF) and structural heart disease. Methods: We conducted a cross-sectional study and performed screening echocardiograms to consecutive primary care patients. We calculated the hemoglobin A1c (HbA1c) within 3 months of the echocardiogram and classified patients as having normal glucose, low-risk or high-risk prediabetes or diabetes. Our primary outcome was HF defined as an ejection fraction (EF) <50% and HF with preserved EF. Our secondary outcome was structural heart disease defined as having either a large atrium, left ventricular hypertrophy, or low EF. Results: We included 15,056 patients who underwent a screening echocardiogram and had a recorded HbA1c. Only 2794 patients had a normal blood glucose, 4201 had low-risk prediabetes, 2499 had high-risk prediabetes, and the remainder had diabetes. The adjusted odds ratio (ORs) of HF for low-risk prediabetes, high-risk prediabetes and diabetes were 1.38 [confidence interval (95% CI) 1.07-1.78] (P = 0.01), 1.47 (95% CI 1.05-2.01) (P = 0.01), and 1.60 (95% CI 1.16-2.01) (P < 0.01), respectively, when compared with normoglycemic patients. The adjusted OR of HF with preserved EF for low- and high-risk prediabetes and diabetes were 1.17 (95% CI 0.86-1.60) (P = 0.30), 1.60 (95% CI 1.15-2.21) (P < 0.01), and 1.63 (95% CI 1.24-2.13) (P < 0.01), respectively, when compared with normoglycemic patients. Conclusions: Prediabetes is a prevalent condition associated with structural heart disease and HF.

Readmission rate and healthcare utilization outcomes of computer-assisted fluoroscopy-based hip navigation versus manual total hip arthroplasty

INTRODUCTION

The study evaluates the technology of fluoroscopy-based hip navigation that has shown to improve implant positioning in total hip arthroplasty (THA).

METHODS

Premier Healthcare data for patients undergoing manual THA or fluoroscopy-based hip navigation THA between 1 January 2016-30 September 2021, were analyzed 90- and 365-day post-THA. The primary outcome was inpatient readmission. Secondary outcomes were operating room (OR) time, length of stay, discharge status, and hospital costs. Baseline covariate differences were balanced using fine stratification and analyzed using generalized linear models.

RESULTS

Among 4,080 fluoroscopy-based hip navigation THA and 429,533 manual THA balanced patients, hip-related readmission rates were statistically significantly lower for the fluoroscopy-based hip navigation THA cohort vs. manual THA for both 90-day (odd ratio [95% CI]: 0.69 [0.52 to 0.91] and 365-day (0.63 [0.49 to 0.81] follow-up. OR time was higher with fluoroscopy-based hip navigation THA vs. manual THA (134.65 vs. 132.04 minutes); however, fluoroscopy-based hip navigation THA patients were more likely to be discharged to home (93.73% vs. 90.11%) vs. manual THA. Hospital costs were not different between cohorts at 90- and 365-day post-operative.

CONCLUSIONS

Fluoroscopy-based hip navigation THA resulted in fewer readmissions, greater discharge to home, and similar hospital costs compared to manual THA.

Benchmarking short-term postoperative mortality across neurosurgery units: is hospital administrative data good enough for risk-adjustment?

BACKGROUND

Surgical mortality indicators should be risk-adjusted when evaluating the performance of organisations. This study evaluated the performance of risk-adjustment models that used English hospital administrative data for 30-day mortality after neurosurgery.

METHODS

This retrospective cohort study used Hospital Episode Statistics (HES) data from 1 April 2013 to 31 March 2018. Organisational-level 30-day mortality was calculated for selected subspecialties (neuro-oncology, neurovascular and trauma neurosurgery) and the overall cohort. Risk adjustment models were developed using multivariable logistic regression and incorporated various patient variables: age, sex, admission method, social deprivation, comorbidity and frailty indices. Performance was assessed in terms of discrimination and calibration.

RESULTS

The cohort included 49,044 patients. Overall, 30-day mortality rate was 4.9%, with unadjusted organisational rates ranging from 3.2 to 9.3%. The variables in the best performing models varied for the subspecialties; for trauma neurosurgery, a model that included deprivation and frailty had the best calibration, while for neuro-oncology a model with these variables plus comorbidity performed best. For neurovascular surgery, a simple model of age, sex and admission method performed best. Levels of discrimination varied for the subspecialties (range: 0.583 for trauma and 0.740 for neurovascular). The models were generally well calibrated. Application of the models to the organisation figures produced an average (median) absolute change in mortality of 0.33% (interquartile range (IQR) 0.15-0.72) for the overall cohort model. Median changes for the subspecialty models were 0.29% (neuro-oncology, IQR 0.15-0.42), 0.40% (neurovascular, IQR 0.24-0.78) and 0.49% (trauma neurosurgery, IQR 0.23-1.68).

CONCLUSIONS

Reasonable risk-adjustment models for 30-day mortality after neurosurgery procedures were possible using variables from HES, although the models for trauma neurosurgery performed less well. Including a measure of frailty often improved model performance.

Medication use and comorbidities in an increasingly younger osteoarthritis population: an 18-year retrospective open-cohort study

OBJECTIVES

As understanding of the pathogenesis and treatment strategies for osteoarthritis (OA) evolves, it is important to understand how patient factors are also changing. Our goal was to examine demographics and known risk factors of patients with OA over time.

DESIGN

Open-cohort retrospective study using electronic health records.

SETTING

Large US integrated health system with 7 hospitals, 2.6 million outpatient clinic visits and 97 300 hospital admissions annually in a mostly rural geographic region.

PARTICIPANTS

Adult patients with at least two encounters and a diagnosis of OA or OA-relevant surgery between 2001 and 2018. Because of geographic region, over 96% of participants were white/Caucasian.

INTERVENTIONS

None.

PRIMARY AND SECONDARY OUTCOME MEASURES

Descriptive statistics were used to examine age, sex, body mass index (BMI), Charlson Comorbidity Index, major comorbidities and OA-relevant prescribing over time.

RESULTS

We identified 290 897 patients with OA. Prevalence of OA increased significantly from 6.7% to 33.5% and incidence increased 37% (from 3772 to 5142 new cases per 100 000 patients per year) (p<0.0001). Percentage of females declined from 65.3% to 60.8%, and percentage of patients with OA in the youngest age bracket (18-45 years) increased significantly (6.2% to 22.7%, p<0.0001). The percentage of patients with OA with BMI ≥30 remained above 50% over the time period. Patients had low comorbidity overall, but anxiety, depression and gastro-oesophageal reflux disease showed the largest increases in prevalence. Opioid use (tramadol and non-tramadol) showed peaks followed by declines, while most other medications increased slightly in use or remained steady.

CONCLUSIONS

We observe increasing OA prevalence and a greater proportion of younger patients over time. With better understanding of how characteristics of patients with OA are changing over time, we can develop better approaches for managing disease burden in the future.

Perioperative Nephrectomy Outcomes for Patients with Liver Disease: Implications for Liver Transplant Candidates

OBJECTIVE

To improve the management of cirrhotic patients diagnosed with new renal masses, we used a nationally representative cohort to assess the perioperative outcomes of nephrectomy in the setting of liver disease. The incidences of liver disease and renal masses are both rising in the US. Delaying liver transplantation to address other health concerns may have life changing consequences in these patients, thus these results help to guide treatment decisions at this critical junction in care.

METHODS

A retrospective study of the 2016-2019 Nationwide Readmissions Database was performed in adults undergoing nephrectomy for non-emergent indications. Outcomes were compared between 3 cohorts: no chronic liver disease (no CLD), chronic liver disease (CLD), and decompensated cirrhosis (DC). Mixed regression models were used to evaluate the association between CLD and DC with outcomes of interest including morbidity, mortality, readmission rates, non-home discharges, length of stay, and costs.

RESULTS

A total of 183,362 patients were evaluated. The mortality rate in the DC cohort (7%) was higher than with CLD (0.4%) and no CLD (0.3%), (P <.001). DC was associated with higher mortality (OR 8.29, 95% CI 4.07 - 16.88), postoperative bleeding requiring transfusion (OR 5.55, 95% CI 3.72 - 8.26), non-home discharge (OR 5.12, 95% CI 3.16 - 8.30) and readmission (OR 1.79, 95% CI 1.09 - 2.94) compared to no CLD. The DC cohort had the greatest length of stay and costs.

CONCLUSION

Patients undergoing nephrectomy with DC have increased morbidity, mortality, readmission rates, non-home discharges, LOS and costs. Alternative management strategies may be considered in these patients.

Can extant comorbidity indices identify patients who experience poor outcomes following total joint arthroplasty?

INTRODUCTION

It is uncertain if generic comorbidity indices commonly used in orthopedics accurately predict outcomes after total hip (THA) or knee arthroplasty (TKA). The purpose of this study was to determine the predictive ability of such comorbidity indices for: (1) 30-day mortality; (2) 30-day rate of major and minor complications; (3) discharge disposition; and (4) extended length of stay (LOS).

METHODS

The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was retrospectively reviewed for all patients who underwent elective THA (n = 202,488) or TKA (n = 230,823) from 2011 to 2019. The American Society of Anesthesiologists (ASA) physical status classification system score, modified Charlson Comorbidity Index (mCCI), Elixhauser Comorbidity Measure (ECM), and 5-Factor Modified Frailty Index (mFI-5) were calculated for each patient. Logistic regression models predicting 30-day mortality, discharge disposition, LOS greater than 1 day, and 30-day major and minor complications were fit for each index.

RESULTS

The ASA classification (C-statistic = 0.773 for THA and TKA) and mCCI (THA: c-statistic = 0.781; TKA: C-statistic = 0.771) were good models for predicting 30-day mortality. However, ASA and mCCI were not predictive of major and minor complications, discharge disposition, or LOS. The ECM and mFI-5 did not reliably predict any outcomes of interest.

CONCLUSION

ASA and mCCI are good models for predicting 30-day mortality after THA and TKA. However, similar to ECM and mFI-5, these generic comorbidity risk-assessment tools do not adequately predict 30-day postoperative outcomes or in-hospital metrics. This highlights the need for an updated, data-driven approach for standardized comorbidity reporting and risk assessment in arthroplasty.

Regional Variation in Outpatient Antibiotic Prescribing for Acute Respiratory Tract Infections in a Commercially Insured Population, United States, 2017

Background

Studies have shown that the Southern United States has higher rates of outpatient antibiotic prescribing rates compared with other regions in the country, but the reasons for this variation are unclear. We aimed to determine whether the regional variability in outpatient antibiotic prescribing for respiratory diagnoses can be explained by differences in prescriber clinical factors found in a commercially insured population.

Methods

We analyzed the 2017 IBM MarketScan Commercial Database of commercially insured individuals aged <65 years. We included visits with acute respiratory tract infection (ARTI) diagnoses from retail clinics, urgent care centers, emergency departments, and physician offices. ARTI diagnoses were categorized based on antibiotic indication. We calculated risk ratios and 95% CIs stratified by ARTI tier and region using log-binomial models controlling for patient age, comorbidities, care setting, prescriber type, and diagnosis.

Results

Of the 14.9 million ARTI visits, 40% received an antibiotic. The South had the highest proportion of visits with an antibiotic prescription (43%), and the West the lowest (34%). ARTI visits in the South are 34% more likely receive an antibiotic for rarely antibiotic-appropriate ARTI visits when compared with the West in multivariable modeling (relative risk, 1.34; 95% CI, 1.33-1.34).

Conclusions

It is likely that higher antibiotic prescribing in the South is in part due to nonclinical factors such as regional differences in clinicians' prescribing habits and patient expectations. There is a need for future studies to define and characterize these factors to better inform regional and local stewardship interventions and achieve greater health equity in antibiotic prescribing.

Age-adjusted Charlson Comorbidity Index as effective predictor for in-hospital mortality of patients with cardiac arrest: a retrospective study

BACKGROUND

Cardiac arrest is currently one of the leading causes of mortality in clinical practice, and the Charlson Comorbidity Index (CCI) is widely utilized to assess the severity of comorbidities. We aimed to evaluate the relationship between the age-adjusted CCI score and in-hospital mortality in intensive care unit (ICU) patients with the diagnosis of cardiac arrest, which is important but less explored previously.

METHODS

This was a retrospective study including patients aged over 18 years from the MIMIC-IV database. We calculated the age-adjusted CCI using age information and ICD codes. The univariate analysis for varied predictors' differences between the survival and the non-survival groups was performed. In addition, a multiple factor analysis was conducted based on logistic regression analysis with the primary result set as hospitalization death. An additional multivariate regression analysis was conducted to estimate the influence of hospital and ICU stay.

RESULTS

A total of 1772 patients were included in our study, with median age of 66, among which 705 (39.8%) were female. Amongst these patients, 963 (54.3%) died during the hospitalization period. Patients with higher age-adjusted CCI scores had a higher likelihood of dying during hospitalization (P < 0.001; OR: 1.109; 95% CI: 1.068-1.151). With the age-adjusted CCI incorporated into the predictive model, the area under the receiver operating characteristic curve was 0.794 (CI: 0.773-0.814), showing that the prediction model is effective. Additionally, patients with higher age-adjusted CCI scores stayed longer in the hospital (P = 0.026, 95% CI: 0.056-0.896), but there was no significant difference between patients with varied age-adjusted CCI scores on the days of ICU stay.

CONCLUSION

The age-adjusted CCI is a valid indicator to predict death in ICU patients with cardiac arrest, which can offer enlightenment for both theory literatures and clinical practice.

Machine Learning in Colorectal Cancer Risk Prediction from Routinely Collected Data: A Review

The inclusion of machine-learning-derived models in systematic reviews of risk prediction models for colorectal cancer is rare. Whilst such reviews have highlighted methodological issues and limited performance of the models included, it is unclear why machine-learning-derived models are absent and whether such models suffer similar methodological problems. This scoping review aims to identify machine-learning models, assess their methodology, and compare their performance with that found in previous reviews. A literature search of four databases was performed for colorectal cancer prediction and prognosis model publications that included at least one machine-learning model. A total of 14 publications were identified for inclusion in the scoping review. Data was extracted using an adapted CHARM checklist against which the models were benchmarked. The review found similar methodological problems with machine-learning models to that observed in systematic reviews for non-machine-learning models, although model performance was better. The inclusion of machine-learning models in systematic reviews is required, as they offer improved performance despite similar methodological omissions; however, to achieve this the methodological issues that affect many prediction models need to be addressed.

Convergence of four measures of multi-morbidity

Objectives

To compare the agreement between percentile ranks from 4 multi-morbidity scores.

Design

Population-based descriptive study.

Setting

Olmsted County, Minnesota (USA).

Participants

We used the medical records-linkage system of the Rochester Epidemiology Project (REP; http://www.rochesterproject.org) to identify all residents of Olmsted County, Minnesota who reached one or more birthdays between 1 January 2005 and 31 December 2014 (10 years).

Methods

For each person, we calculated 4 multi-morbidity scores using readily available diagnostic code lists from the US Department of Health and Human Services, the Clinical Classifications Software, and the Elixhauser Comorbidity Index. We calculated scores using diagnostic codes received in the 5 years before the index birthday and fit quantile regression models across age and separately by sex to transform unweighted, simple counts of conditions into percentile ranks as compared to peers of same age and of same sex. We compared the percentile ranks of the 4 multi-morbidity scores using intra-class correlation coefficients (ICCs).

Results

We assessed agreement in 181,553 persons who reached a total of 1,075,433 birthdays at ages 18 years through 85 years during the study period. In general, the percentile ranks of the 4 multi-morbidity scores exhibited high levels of agreement in 6 score-to-score pairwise comparisons. The agreement increased with older age for all pairwise comparisons, and ICCs were consistently greater than 0.65 at ages 50 years and older.

Conclusions

The assignment of percentile ranks may be a simple and intuitive way to assess the underlying trait of multi-morbidity across studies that use different measures.

Ensemble machine learning methods in screening electronic health records: A scoping review

Background

Electronic health records provide the opportunity to identify undiagnosed individuals likely to have a given disease using machine learning techniques, and who could then benefit from more medical screening and case finding, reducing the number needed to screen with convenience and healthcare cost savings. Ensemble machine learning models combining multiple prediction estimates into one are often said to provide better predictive performances than non-ensemble models. Yet, to our knowledge, no literature review summarises the use and performances of different types of ensemble machine learning models in the context of medical pre-screening.

Method

We aimed to conduct a scoping review of the literature reporting the derivation of ensemble machine learning models for screening of electronic health records. We searched EMBASE and MEDLINE databases across all years applying a formal search strategy using terms related to medical screening, electronic health records and machine learning. Data were collected, analysed, and reported in accordance with the PRISMA scoping review guideline.

Results

A total of 3355 articles were retrieved, of which 145 articles met our inclusion criteria and were included in this study. Ensemble machine learning models were increasingly employed across several medical specialties and often outperformed non-ensemble approaches. Ensemble machine learning models with complex combination strategies and heterogeneous classifiers often outperformed other types of ensemble machine learning models but were also less used. Ensemble machine learning models methodologies, processing steps and data sources were often not clearly described.

Conclusions

Our work highlights the importance of deriving and comparing the performances of different types of ensemble machine learning models when screening electronic health records and underscores the need for more comprehensive reporting of machine learning methodologies employed in clinical research.

Development and validation of novel multimorbidity indices for older adults

BACKGROUND

Measuring multimorbidity in claims data is used for risk adjustment and identifying populations at high risk for adverse events. Multimorbidity indices such as Charlson and Elixhauser scores have important limitations. We sought to create a better method of measuring multimorbidity using claims data by incorporating geriatric conditions, markers of disease severity, and disease-disease interactions, and by tailoring measures to different outcomes.

METHODS

Health conditions were assessed using Medicare inpatient and outpatient claims from subjects age 67 and older in the Health and Retirement Study. Separate indices were developed for ADL decline, IADL decline, hospitalization, and death, each over 2 years of follow-up. We validated these indices using data from Medicare claims linked to the National Health and Aging Trends Study.

RESULTS

The development cohort included 5012 subjects with median age 76 years; 58% were female. Claims-based markers of disease severity and disease-disease interactions yielded minimal gains in predictive power and were not included in the final indices. In the validation cohort, after adjusting for age and sex, c-statistics for the new multimorbidity indices were 0.72 for ADL decline, 0.69 for IADL decline, 0.72 for hospitalization, and 0.77 for death. These c-statistics were 0.02-0.03 higher than c-statistics from Charlson and Elixhauser indices for predicting ADL decline, IADL decline, and hospitalization, and <0.01 higher for death (p < 0.05 for each outcome except death), and were similar to those from the CMS-HCC model. On decision curve analysis, the new indices provided minimal benefit compared with legacy approaches. C-statistics for both new and legacy indices varied substantially across derivation and validation cohorts.

CONCLUSIONS

A new series of claims-based multimorbidity measures were modestly better at predicting hospitalization and functional decline than several legacy indices, and no better at predicting death. There may be limited opportunity in claims data to measure multimorbidity better than older methods.

Specialist Availability and Drug Adherence in Older Adults with Dementia Across Regions of the United States

BACKGROUND

Access to specialists facilitates appropriate Alzheimer's disease and related dementia (ADRD) medication use and adherence. However, there is little information on the impact of specialists' availability on ADRD medication adherence, especially in regions of the United States (US) where specialists are scarce, e.g., the Deep South (DS).

OBJECTIVE

To ascertain whether the availability of specialty physicians in the DS and other US regions predicts ADRD medication adherence among community-dwelling older adultsMethods:We conducted secondary analyses of claims data for 54,194 Medicare beneficiaries with ADRD in 2013-2015. Medication adherence was measured using the proportion of days covered (PDC). Multivariable-adjusted Modified Poisson regression was used to examine associations of adherence with physicians' availability by region.

RESULTS

The race/ethnicity distribution was 81.44% white, 9.17% black, 6.24% Hispanic, 2.25% Asian, and 1% other; 71.81% were female, and 42.36% were older than 85 years. Beneficiaries across regions differed in all individual and contextual characteristics except sex and comorbidities. Neurologists and psychiatrists' availability was not significantly associated with adherence (DS = 1.00, 0.97-1.03 & non-DS = 1.01, 1.00-1.01). Race and having ≥1 specialist visits were associated with a lower risk of adherence in both regions (p < 0.0001). Advanced age, dual Medicare/Medicaid eligibility, and living in non-large metropolitan areas, were associated with adherence in the non-DS region.

CONCLUSION

Among older Americans with ADRD, a context defined by specialist availability does not affect adherence, but other context characteristics related to socioeconomic status may. Research should further examine the influence of individual and contextual factors on ADRD treatment among older adults.

Differences Between General Internal Medicine and Family Medicine Physicians' Initiation of Pre-Exposure Prophylaxis

OBJECTIVE

Preexposure Prophylaxis (PrEP) is under-utilized in primary care. Given differences in treatment approaches for other conditions between family medicine (FM) and general internal medicine (GIM), this study compared PrEP-prescribing between FM and GIM physicians.

METHODS

De-identified electronic health record data from a multi-state health care system was used in this retrospective observational study. The time period from 1/1/13 to 9/30/21 was used to identify PrEP eligible patients using measures of current sexually transmitted disease and condomless sex at the time of eligibility. Receipt of PrEP was measured in the 12 months after PrEP eligibility. The odds of receiving PrEP in GIM as compared to FM was computed before and after adjusting for demographics and physical and psychiatric comorbidities.

RESULTS

The majority of eligible patients were 18 to 39 years of age, 60.9% were female and 71.6% were White race. Among PrEP eligible patients, 1.1% received PrEP in the first year after index date. Receiving PrEP was significantly more likely among patients treated in GIM versus FM (OR = 2.30; 95% CI:1.63-3.25). After adjusting for covariates, this association remained statistically significant (OR = 2.02; 95% CI:1.41-2.89).

CONCLUSIONS

PrEP is grossly under-utilized in primary care. The majority of Americans enter the health care system through primary care and not through HIV providers or other specialties. Therefore, educational interventions are needed to increase confidence and knowledge and to encourage PrEP prescribing by FM and GIM physicians.

Prescription stimulant use during long-term opioid therapy and risk for opioid use disorder

Background

Concurrent therapeutic prescribing of prescription stimulants with opioid analgesics is increasing in the United States. Stimulant medication use is associated with increased risk for long-term opioid therapy (LTOT), and LTOT is associated with increased risk for opioid use disorder (OUD).

Aims

To determine if stimulant prescriptions among those with LTOT (≥90 days) are associated with greater risk for opioid use disorder (OUD).

Methods

This retrospective cohort study from 2010 to 2018 used a United States, nationally distributed Optum© analytics Integrated Claims-Clinical dataset. Patients ≥18 years of age, and free of prevalent OUD in the two years prior to index were eligible. All patients had a new ≥90-day opioid prescription. The index date was day 91. We compared risk for new OUD diagnoses in patients with and without a prescription stimulant overlapping LTOT. Entropy balancing and weighting controlled for confounding factors.

Results

Patients (n = 5,712), were 57.7 (SD±14.9) years of age on average, majority female (59.8%) and 73.3% White race. Among patients with LTOT, 2.8% had overlapping stimulant prescriptions. Before controlling for confounding, dual stimulant-opioid prescriptions, compared to opioid only, were associated with OUD risk (HR = 1.75; 95%CI:1.17-2.61). After controlling for confounding, this association was no longer present (HR = 0.89; 95%CI:0.47-1.71). Results did not differ in sensitivity analyses limiting the cohort to those <56 years of age.

Conclusions

Dual stimulant use among patients with LTOT does not increase risk for OUD. Stimulants prescribed for ADHD and other conditions may not worsen opioid outcomes for some patients with LTOT.

Disease-Specific Factors Associated with Readmissions or Mortality After Hospital Discharge in COVID-19 Patients: a Retrospective Cohort Study

BACKGROUND

Understanding the implications of disease-specific factors beyond baseline patient characteristics for coronavirus disease 2019 (COVID-19) may allow for identification of indicators for safe hospital discharge.

OBJECTIVE

Assess whether disease-specific factors are associated with adverse events post-discharge using a data-driven approach.

DESIGN

Retrospective cohort study.

SETTING

Fifteen medical centers within Kaiser Permanente Southern California.

PARTICIPANTS

Adult patients (n=3508) discharged alive following hospitalization for COVID-19 between 05/01/2020 and 09/30/2020.

INTERVENTIONS

None.

MAIN MEASURES

Adverse events defined as all-cause readmission or mortality within 14 days of discharge. Least absolute shrinkage and selection operator (LASSO) was used for variable selection and logistic regression was performed to estimate odds ratio (OR) and 95% confidence interval (CI).

KEY RESULTS

Four variables including age, Elixhauser index, treatment with remdesivir, and symptom duration at discharge were selected by LASSO. Treatment with remdesivir was inversely associated with adverse events (OR: 0.46 [95%CI: 0.36-0.61]), while symptom duration ≤ 10 days was associated with adverse events (OR: 2.27 [95%CI: 1.79-2.87]) in addition to age (OR: 1.02 [95%CI: 1.01-1.03]) and Elixhauser index (OR: 1.15 [95%CI: 1.11-1.20]). A significant interaction between remdesivir and symptom duration was further observed (p=0.01). The association of remdesivir was stronger among those with symptom duration ≤10 days vs >10 days at discharge (OR: 0.30 [95%CI: 0.19-0.47] vs 0.62 [95%CI: 0.44-0.87]), while the association of symptom duration ≤ 10 days at discharge was weaker among those treated with remdesivir vs those not treated (OR: 1.31 [95%CI: 0.79-2.17] vs 2.71 [95%CI 2.05-3.59]).

CONCLUSIONS

Disease-specific factors including treatment with remdesivir, symptom duration, and their interplay may help guide clinical decision making at time of discharge.

Demographic factors, psychiatric and physical comorbidities associated with starting preexposure prophylaxis in a nationally distributed cohort

Due to a large number of small studies and limited control for confounding, existing evidence regarding patient characteristics associated with PrEP initiation is inconsistent. We used a large electronic health record cohort to determine which demographic, physical morbidity and psychiatric conditions are associated with PrEP initiation. Eligible adult (≥18 years) patients were selected from the Optum® de-identified Electronic Health Record dataset (2010-2018). Non-HIV sexually transmitted diseases and high risk sexual behavior was used to identify patients eligible for PrEP. A fully adjusted Poisson regression model estimated the association between age, gender, race, insurance status, comorbidity index, depression, anxiety, dysthymia, severe mental illness, substance use disorder and nicotine dependence/smoking and rate of PrEP initiation. The cohort (n = 30,909) was mostly under 40 years of age (64.3%), 67.6% were female and 58.2% were White. The cumulative incidence of PrEP initiation was 1.3% (n = 408). Patients ≥60 years of age, compared to 18-29 year olds and Black compared to White patients had significantly lower rates of PrEP initiation. Anxiety disorder was significantly associated with higher rate of PrEP initiation (RR = 1.67; 95%CI:1.20-2.33) and nicotine dependence/smoking with a lower rate (RR = 0.73; 95%CI:0.54-0.97). PrEP is underutilized, and a race disparity exists in PrEP initiation. In the context of existing research, nicotine dependence/smoking is the patient characteristic most consistently associated lower rates of starting PrEP. Given the high prevalence of smoking in PrEP eligible patients, physicians may want to integrate discussions of smoking cessation in patient-provider decisions to start PrEP.

Distal radius fractures and risk of incident neurocognitive disorders in older adults: a retrospective cohort study

INTRODUCTION

Distal radius fractures (DRF) are associated with increased risk of subsequent fractures and physical decline in older adults. This study aims to evaluate the risk cognitive decline following DRF and potential for timely screening and intervention.

METHODS

A cohort of 1046 individuals 50-75 years of age with DRF were identified between 1995 and 2015 (81.5% female; mean age 62.5 [± 7.1] years). A control group (N = 1044) without history of DRF was matched by age, sex, and fracture date (i.e., index). The incidence of neurocognitive disorders (NCD) in relation to DRF/index was determined. Group comparisons were adjusted by age and comorbidity measured by the Elixhauser index.

RESULTS

The DRF group had a greater incidence of NCD compared to the control group (11.3% vs. 8.2%) with a 56% greater relative risk (HR = 1.56, 95% Cl: 1.18, 2.07; p = 0.002) after adjusting for age and comorbidity. For every 10-year age increase, the DRF group was over three times more likely to develop a NCD (HR = 3.23, 95% Cl: 2.57, 4.04; p < 0.001).

CONCLUSION

DRF in adults ages 50 to 75 are associated with increased risk of developing neurocognitive disorders. DRF may represent a sentinel opportunity for cognitive screening and early intervention. Distal radius fractures (DRF) have been associated with greater risk of future fractures and physical decline. This study reports that DRF are also associated with greater risk of developing neurocognitive disorders in older adults. Timely intervention may improve early recognition and long-term outcomes for older adults at risk of cognitive decline.

Association of statewide stay-at-home orders with utilization of case management and supportive services for veterans experiencing housing insecurity

The US Department of Housing and Urban Development-Department of Veterans Affairs (VA) Supportive Housing (HUD-VASH) program provides Veterans with a subsidy for rent and case management. In response to the Coronavirus 2019 pandemic, many states enacted stay-at-home orders that may have limited access to case managers. Therefore, we examined the association between statewide stay-at-home orders and utilization of HUD-VASH case management. We linked data on whether a state implemented a statewide stay-at-home order between March 1, 2020 and April 30, 2020 with VA medical records. Analysis time was centered on the date of a state's stay-at-home order (exposed states). For Veterans in states without a stay-at home-order (unexposed states), we used the average date exposed states implemented an order (March 27, 2020). We used a difference-in-difference design and adjusted linear regression models to compare total, in-person, telephone, and video case management encounters per Veteran in the 60 days after a stay-at-home order relative to the prior year. There was no significant difference in utilization of case management between Veterans who lived in states that did and did not issue a stay-at-home order. Across all states and in the 60 days after the index date relative to the prior year, Veterans had more total, telephone and video, and fewer in-person encounters. Statewide stay-at-home orders did not differentially affect utilization of case management. Virtual case management in HUD-VASH can increase program reach; however, the effect of virtual case management on outcomes such as quality of life and Veteran satisfaction is unknown.

Inferential Pluralism in Causal Reasoning from Randomized Experiments

Causal pluralism can be defended not only in respect to causal concepts and methodological guidelines, but also at the finer-grained level of causal inference from a particular source of evidence for causation. An argument for this last variety of pluralism is made based on an analysis of causal inference from randomized experiments (RCTs). Here, the causal interpretation of a statistically significant association can be established via multiple paths of reasoning, each relying on different assumptions and providing distinct elements of information in favour of a causal interpretation.

Benefits of Adding Glucagon-Like Peptide 1 Receptor Agonists to Sodium-Glucose Co-Transporter 2 Inhibitors in Diabetic Patients With Atherosclerotic Disease and Heart Failure

Sodium-glucose co-transporter 2 inhibitors (SGLT2i) reduce the risk of cardiovascular events and heart failure hospitalization (HFH) in patients with heart failure with reduced ejection fraction (HFrEF), diabetes mellitus type 2 (DM2), and atherosclerotic cardiovascular disease (ASCVD). The role of glucagon-like peptide 1 agonists (GLP1a) in these patients is unclear. We designed this study to assess if the addition of GLP1a to SGLT2i therapy improves outcomes in patients with HFrEF, DM2, and ASCVD. This was a retrospective cohort study of patients with DM2, ASCVD, and HFrEF in the national Veterans Affairs database. Patients on SGLT2i were propensity matched to patients on both SGTL2i and GLP1a. The co-primary outcomes were HFH and the composite of all-cause death, myocardial infarction, and stroke. We assessed them through a Cox regression model including unbalanced baseline characteristics. From a cohort of 5,576 patients, 343 were propensity matched to each study arm. The addition of GLP1a was associated with a 67% reduction in the 1-year risk of a composite event compared with therapy with SGLT2i (confidence interval 0.138 to 0.714, p = 0.007). The risk of HFH was not significantly different between both arms (p = 0.199). Sensitivity analyses in the unmatched dataset confirmed these findings. In conclusion, the addition of GLP1a to SGLT2i may reduce the risk of adverse events in patients with HFrEF who have DM2 and ASCVD, but it does not affect the risk of HFH.

Evaluation of risk adjustment performance of diagnosis-based and medication-based comorbidity indices in patients with chronic obstructive pulmonary disease

Objectives

This study assessed risk adjustment performance of six comorbidity indices in two categories of comorbidity measures: diagnosis-based comorbidity indices and medication-based ones in patients with chronic obstructive pulmonary disease (COPD).

Methods

This was a population–based retrospective cohort study. Data used in this study were sourced from the Taiwan National Health Insurance Research Database. The study population comprised all patients who were hospitalized due to COPD for the first time in the target year of 2012. Each qualified patient was individually followed for one year starting from the index date to assess two outcomes of interest, medical expenditures within one year after discharge and in-hospital mortality of patients. To assess how well the added comorbidity measures would improve the fitted model, we calculated the log-likelihood ratio statistic G2. Subsequently, we compared risk adjustment performance of the comorbidity indices by using the Harrell c-statistic measure derived from multiple logistic regression models.

Results

Analytical results demonstrated that that comorbidity measures were significant predictors of medical expenditures and mortality of COPD patients. Specifically, in the category of diagnosis-based comorbidity indices the Elixhauser index was superior to other indices, while the RxRisk-V index was a stronger predictor in the framework of medication-based codes, for gauging both medical expenditures and in-hospital mortality by utilizing information from the index hospitalization only as well as the index and prior hospitalizations.

Conclusions

In conclusion, this work has ascertained that comorbidity indices are significant predictors of medical expenditures and mortality of COPD patients. Based on the study findings, we propose that when designing the payment schemes for patients with chronic diseases, the health authority should make adjustments in accordance with the burden of health care caused by comorbid conditions.