Proton pump inhibitors associated with an increased risk of mortality in elderly: a systematic review and meta-analysis.

PURPOSE: The increased use of proton pump inhibitors (PPIs) in the elderly has raised concerns about potential severe adverse effects. Our systematic review investigated the mortality associated with PPI use in elderly populations. METHODS: We searched MEDLINE, EMBASE, and the Cochrane Library for relevant publications until August 2022. We included randomized controlled trials (RCTs), quasi-RCTs, and observational studies on the association between proton pump inhibitors and mortality in the elderly. To estimate the pooled relative risk (RR) and 95% confidence interval (CI), the inverse-variance random effect model was used. Heterogeneity was assessed using the I2 test. Subgroup analyses were performed by follow-up period, population, and study design. RESULTS: A total of 4 RCTs and 36 cohort studies were included in the meta-analysis. Four RCTs showed that there was no significant association between PPIs and the risk of death. From 23 observational studies (26 cohorts), the use of proton pump inhibitors was not significantly associated with increased mortality in the elderly (RR 1.14; 95% CI, 0.90-1.45). However, when controlling for covariates from 33 observational studies (41 cohorts), proton pump inhibitors in older adults aged 50 years or more were significantly associated with a 15% higher risk of mortality compared to nonusers (RR 1.15; 95% CI, 1.10-1.20). CONCLUSIONS: Our meta-analysis of RCTs found that PPIs did not show a significant association with increased mortality risk in older adults. However, the meta-analysis of cohort studies and long-term follow-up studies showed a higher increased risk of death with PPI use in older adults. The prescription of PPIs in patients aged 50 years or older should be carefully considered.

Comparing maternal factors associated with postpartum depression between primiparous adolescents and adults: A large retrospective cohort study.

OBJECTIVES: This study aimed to estimate the prevalence of diagnosed postpartum depression (PPD) and the likelihood of PPD among primiparous women. We also evaluated differences in the influence of various maternal factors associated with PPD in adolescent versus adult mothers. METHODS: We conducted a retrospective cohort study using electronic health records linked to birth certificates to evaluate the associations between maternal factors and PPD diagnosis. The study population was stratified into adults and adolescents based on age at delivery. We evaluated socioeconomic, demographic, psychological, and clinical factors associated with PPD in each of the age-defined maternal cohorts using multivariable logistic regression analyses. RESULTS: A total of 61,226 primiparous women, including 6435 (11%) mothers younger than 20 years old, were included in the study. The overall PPD rate was 4.0%, with the age-specific PPD rate measuring 1.6 times higher in adolescents than in adult women (6.1% vs. 3.8%). Compared with adults, adolescents were less likely to obtain firsttrimester prenatal care (33% vs. 16%), more likely to have recent tobacco use (11% vs. 6%), and more likely to have had an infection during pregnancy (5% vs. 1%). In adjusted models, significant factors for PPD in both groups included a history of depression or anxiety, tobacco use, and long-acting reversible contraception use. CONCLUSIONS: In this cohort of first-time mothers, adolescents had higher rates of PPD diagnosis as well as PPD-associated maternal factors than adults. Increased awareness of PPD risk in adolescents and early intervention, including integrating mental healthcare into prenatal care, may help benefit adolescents and reduce the risk and severity of PPD.

Risk of cardiovascular events according to the tricyclic antidepressant dosage in patients with chronic pain: a retrospective cohort study.

PURPOSE: We aimed to examine the risk of cardiovascular adverse events by tricyclic antidepressant (TCA) dosage among patients with chronic pain. METHODS: A retrospective cohort study was conducted using a nationwide sample cohort. Among patients aged ≥ 18 years with a chronic pain diagnosis and no history of cardiovascular events, we extracted users and non-users of TCAs through 1:1 propensity score matching. TCA users were categorized into three groups according to the mean defined daily dose (DDD): very low doses (< 0.15 DDD), low doses (0.15-0.34 DDD), and traditional doses (≥ 0.34 DDD). A 6-month follow-up was conducted with an intention-to-treat approach. We examined the hazard ratio of cardiovascular adverse events using Cox proportional hazards analysis. RESULTS: In total, 16,660 matched patients were followed up (8330 TCA users and 8330 non-users). TCA use did not significantly increase cardiovascular adverse events (hazard ratio [HR] 1.12, 95% confidence interval [CI] 0.94-1.33). Low-dose (0.15-0.34 DDD) TCAs (HR 1.37, 95% CI 1.08-1.74), particularly low-dose (0.15-0.34 DDD) nortriptyline (HR 2.11, 95% CI 1.44-3.08), was associated with an increased risk of cardiovascular adverse events. Administration of TCAs at the traditional dose (≥ 0.34 DDD) increased the risk of ischemic stroke (HR 2.08, 95% CI 1.11-3.88). CONCLUSION: Close monitoring of patients on long-term, low-dose use of TCAs should be conducted to avoid an increase in the cumulative dose, which increases the risk of cardiovascular adverse events.

Non-steroidal anti-inflammatory drug-associated acute kidney injury: does short-term NSAID use pose a risk in hospitalized patients?

PURPOSE: While renal risk associated with short-term use of non-steroidal anti-inflammatory drugs (NSAID) has been anecdotally documented, no conclusive evidence is available on the renal safety, especially among hospitalized patients with reduced renal function. This study is to evaluate the risk of acute kidney injury (AKI) associated with NSAID use in hospital. METHODS: A retrospective matched cohort study utilizing electronic health records from two large academic tertiary-care hospitals was conducted. We defined AKI based on changes in SCr according to published AKI criteria. The hospital acquired AKI risk associated with inpatient NSAID use was assessed using a time-dependent Cox proportional hazard regression in pooled cohort as well as two sub cohorts stratified by baseline renal function. RESULTS: A total of 18,794 admissions were included in the final cohort. Of 9397 admissions exposed to NSAIDs, 7914 and 1483 admissions were in the "without" and "with baseline renal impairment" cohort, with the same number of matching non-exposed admissions in each of the stratified cohort. The AKI incidences were 6 and 22 events per 1000 patient-days in "without" and "with preexisting renal impairment" cohort, respectively. The adjusted analyses suggested that NSAID use increased AKI risk in patients with preexisting renal impairment (hazard ratio [HR]: 1.38 [1.04-1.83]) but not in the patients without preexisting renal impairment (HR: 0.83 [95% CIs: 0.63-1.08]) or in the pooled cohort (HR: 1.01 [95% CIs: 0.83-1.24]). CONCLUSION: Our findings suggested that NSAID use is associated with an increased risk of AKI in the hospitalized patients with preexisting renal impairment but the association is not statistically significant in those who have preserved renal function. Further randomized controlled trials are needed to validate these observational findings.

The association between acid-suppressive agent use and the risk of cancer: a systematic review and meta-analysis.

BACKGROUND: Acid-suppressive agents (ASAs) may be associated with cancer; previous studies reported that the risk of cancer with acid suppressants has differed depending on the site of cancer. Here, we conducted a systematic review and meta-analysis of the association between ASA use and the type of cancer risk. METHODS: MEDLINE, EMBASE, and Cochrane library databases were searched for publications up to the end of September 2019 for MeSH terms and text words related to cancer and ASAs. Studies on the association between ASAs and cancer risk, which included a control group and reported the relative risk of cancer, were included. The inverse-variance random effect model was used to estimate the pooled relative risk (RR) and 95% confidence interval (CI), and subgroup analysis for type of acid suppressants, drug uptake duration, and cumulative doses was performed. Heterogeneity was assessed using the I2 test and Q statistic. RESULTS: Thirty-nine cohort and case-control studies were included. ASA use was found to be significantly associated with a 46% higher risk of gastric cancer (RR, 1.46; 95% CI, 1.18-1.80) and a 53% higher risk of liver cancer (RR, 1.53; 95% CI, 1.31-1.78) compared with nonuse; however, there was no significant association for esophageal, colorectal, pancreatic, lung, breast, prostate, and kidney cancer; melanoma; and lymphoma. CONCLUSIONS: ASAs were significantly associated with an increased risk of gastric and liver cancer; therefore, special attention of ASA use considering the potential risk of gastric and liver cancer is needed.

Comparing pregnancy and pregnancy outcome rates between adolescents with and without pre-existing mental disorders.

BACKGROUND: There are limited population-based data on the role of mental disorders in adolescent pregnancy, despite the presence of mental disorders that may affect adolescents' desires and decisions to become pregnant. OBJECTIVE: This study aimed to examine the relationship between specific types of mental disorders and pregnancy rates and outcome types among adolescents aged 13-19 years, using single-year age groups. METHODS: We conducted a retrospective cohort study using data from the Merative™ MarketScan Research Databases. The study population consisted of females aged 13-19 years with continuous insurance enrollment for three consecutive calendar years between 2005 and 2015. Pregnancy incidence rates were calculated both overall and within the different categories of mental disorders. The presence of mental disorders, identified through diagnosis codes, was classified into 15 categories. Pregnancy and pregnancy outcome types were determined using diagnosis and procedure codes indicating the pregnancy status or outcome. To address potential over- or underestimations of mental disorder-specific pregnancy rates resulting from variations in age distribution across different mental disorder types, we applied age standardization using 2010 U.S. Census data. Finally, multivariable logistic regression models were used to examine the relationships between 15 specific types of mental disorders and pregnancy incidence rates, stratified by age. RESULTS: The age-standardized pregnancy rate among adolescents diagnosed with at least one mental disorder was 15.4 per 1,000 person-years, compared to 8.5 per 1,000 person-years among adolescents without a mental disorder diagnosis. Compared to pregnant adolescents without a mental disorder diagnosis, those with a mental disorder diagnosis had a slightly but significantly higher abortion rate (26.7% vs 23.8%, P-value < 0.001). Multivariable logistic regression models showed that substance use-related disorders had the highest odds ratios (ORs) for pregnancy incidence, ranging from 2.4 [95% confidence interval (CI): 2.1-2.7] to 4.5 [95% CI:2.1-9.5] across different age groups. Overall, bipolar disorders (OR range: 1.6 [95% CI:1.4-1.9]- 1.8 [95% CI: 1.7-2.0]), depressive disorders (OR range: 1.4 [95% CI: 1.3-1.5]- 2.7 [95% CI: 2.3-3.1]), alcohol-related disorders (OR range: 1.2 [95% CI: 1.1-1.4]- 14.5 [95% CI: 1.2-178.6]), and attention-deficit/conduct/disruptive behavior disorders (OR range: 1.1 [95% CI: 1.0-1.1]- 1.8 [95% CI: 1.1-3.0]) were also significantly associated with adolescent pregnancy, compared to adolescents without diagnosed mental disorders of the same age. CONCLUSION: This study emphasizes the elevated rates of pregnancy and pregnancy ending in abortion among adolescents diagnosed with mental disorders, and identifies the particular mental disorders associated with higher pregnancy rates.

Factors associated with the use of traditional doses of amitriptyline for chronic pain management: A cross-sectional study.

There are studies on the effect of low-dose amitriptyline on pain control, but there is a lack of studies on the use of amitriptyline for chronic pain and the factors associated with the prescription of traditional doses. We used a national sample cohort of patients aged ≥ 18 years who were prescribed amitriptyline along with chronic pain, without psychiatric disorders, between 2002 to 2015. We categorized the prescriptions into 2 groups according to the daily dose: low doses (≤25 mg) and traditional doses (>25 mg). Multivariable logistic regression models were used to identify factors associated with traditional dose prescriptions. Among 177,769 prescriptions for amitriptyline, 15,119 (8.5%) were prescribed for chronic pain. The prevalence of prescriptions and proportion of traditional doses of amitriptyline tended to decrease during the study period. Male sex (odds ratio [OR] 1.09, 95% confidence interval [CI] 1.05-1.13); age 65-80 years (OR 1.12, 95% CI 1.08-1.16), especially ≥ 80 years (OR 1.55, 95% CI 1.45-1.65); headaches (OR 1.18, 95% CI 1.10-1.27), receiving medical aids (OR 2.58, 95% CI 2.46-2.71); and being prescribed benzodiazepines or zolpidem concomitantly (OR 1.10, 95% CI 1.06-1.15) were significantly associated with traditional dose prescriptions of amitriptyline. Although traditional dose prescriptions of amitriptyline have been declining, close monitoring is still required in the presence of the above-mentioned factors.

Clinical safety and narcolepsy-like symptoms of dual orexin receptor antagonists in patients with insomnia: a systematic review and meta-analysis.

STUDY OBJECTIVES: Dual orexin receptor antagonists (DORAs) are emerging treatments for insomnia. This meta-analysis study aimed to assess the safety of FDA-approved DORAs (suvorexant, lemborexant, and daridorexant), focusing on narcolepsy-like symptoms associated with these drugs. METHODS: Five prominent databases were searched to identify randomized controlled trials (RCTs) on this topic. Primary safety outcomes included treatment-emergent adverse events (TEAEs), treatment-related TEAEs, TEAEs leading to discontinuation, and serious TEAEs. Excessive daytime sleepiness (EDS), sleep paralysis, and hallucinations were categorized as adverse events (AEs)-related narcolepsy-like symptoms. RESULTS: Eleven RCTs with 7703 patients were included. DORAs were associated with a higher risk of TEAEs (risk ratio [RR], 1.09; 95% confidence interval [CI], 1.03 to 1.15) and treatment-related TEAEs (RR, 1.69; 95% CI: 1.49 to 1.92) when compared to placebo. The DORA group exhibited a significantly higher risk of EDS (RR, 2.15; 95% CI: 1.02 to 4.52) and sleep paralysis (RR, 3.40; 95% CI: 1.18 to 9.80) compared to the placebo group. CONCLUSION: This meta-analysis achieved a comparative evaluation of the clinical safety and tolerability of FDA-approved DORAs for primary insomnia, specifically focusing on AEs-related narcolepsy-like symptoms. This study contributes to understanding the safety profile of FDA-approved DORAs for treating insomnia.

Efficacy and Safety of Fibroblast Growth Factor-21 Analogs for the Treatment of Metabolic Dysfunction-Associated Steatohepatitis: A Systematic Review and Meta-Analysis.

Fibroblast growth factor (FGF)-21 analogs are potential therapeutic candidates for metabolic dysfunction-associated steatohepatitis (MASH). This systematic review and meta-analysis aimed to assess the efficacy and safety of the FGF-21 analogs, efruxifermin, pegbelfermin, and pegozafermin for MASH treatment. A comprehensive systematic review and meta-analysis of randomized controlled trials from five major databases was conducted. Primary efficacy outcomes focused on liver histological improvement, while secondary efficacy outcomes encompassed reductions in liver fat content and improvements in biochemical parameters. Safety outcomes examined included treatment-emergent adverse events (TEAEs), treatment-related TEAEs, TEAEs leading to discontinuation, and serious TEAEs. Eight eligible studies involving 963 patients were included in this review. Compared with the placebo group, the FGF-21 analog-treated group exhibited significantly improved primary efficacy outcomes, specifically ≥1 stage improvement in fibrosis with no worsening of MASH (risk ratio [RR] = 1.83; 95% confidence interval [CI] = 1.27-2.62) and at least two-point improvement in the non-alcoholic fatty liver disease activity score with no worsening of fibrosis (RR = 2.85; 95% CI = 2.06-3.95). Despite an increased risk of TEAEs (RR = 1.17; 95% CI = 1.08-1.27) and treatment-related adverse events (RR = 1.75; 95% CI = 1.40-2.19), FGF-21 analogs exhibited an acceptable safety profile. FGF-21 analogs were significantly better in achieving liver histological improvements and beneficial biochemical outcomes compared with placebo, with a tolerable safety pattern. These findings shed light on the efficacy and safety of FGF-21 analogs and provide valuable evidence for their application as MASH therapeutics.

Comparative Safety of Long-Acting vs. Short-Acting Erythropoiesis-Stimulating Agents Among Patients Undergoing Hemodialysis.

Both short-acting (epoetin alfa or beta) and long-acting (darbepoetin alfa or PEG-epoetin) erythropoiesis-stimulating agents (ESAs) are commonly prescribed for patients with kidney failure undergoing maintenance hemodialysis. We compared the risks of major adverse cardiovascular events (MACE) and of all-cause mortality associated with receipt of short- vs. long-acting ESAs. This retrospective cohort analysis included Medicare hemodialysis beneficiaries aged ≥ 18 years in the United States Renal Data System from January 2015 to December 2017. We included adults who survived > 90 days after initiating hemodialysis and received either short- or long-acting ESAs. Outcomes were MACE (first occurrence of stroke, acute myocardial infarction, or cardiovascular-related mortality) and all-cause mortality. After stabilized inverse probability of treatment weighting, Cox proportional hazards regression models were used to estimate the hazard ratio (HR) and 95% confidence interval (CI) for each outcome. Of 68,607 patients (mean age: 65 years, 45% females), 33,658 (49%) received long-acting ESAs and 34,949 (51%) received short-acting ESAs. There was no difference in the risk of MACE associated with receipt of short- vs. long-acting ESAs (HR: 1.02 (95% CI: 0.98-1.08)). However, long-acting (vs. short-acting) ESA receipt was associated with a lower risk of all-cause mortality (HR: 0.91 (95% CI: 0.87-0.96)). Compared with short-acting ESAs, long-acting ESAs were associated with a lower risk of all-cause mortality, with no difference in the risk of MACE. Future studies with a longer follow-up are needed to confirm these findings.

A Propensity-Matched Retrospective Comparative Study with Historical Control to Determine the Real-World Effectiveness of Durvalumab after Concurrent Chemoradiotherapy in Unresectable Stage III Non-Small Cell Lung Cancer.

This study aimed to add real-world evidence to the literature regarding the effectiveness and safety of durvalumab consolidation (DC) after concurrent chemoradiotherapy (CCRT) in the treatment of unresectable stage III non-small cell lung cancer (NSCLC). Using a hospital-based NSCLC patient registry and propensity score matching in a 2:1 ratio, we conducted a retrospective cohort study of patients with unresectable stage III NSCLC who completed CCRT with and without DC. The co-primary endpoints were 2-year progression-free survival and overall survival. For the safety evaluation, we evaluated the risk of any adverse events requiring systemic antibiotics or steroids. Of 386 eligible patients, 222 patients-including 74 in the DC group-were included in the analysis after propensity score matching. Compared with CCRT alone, CCRT with DC was associated with increased progression-free survival (median: 13.3 vs. 7.6 months, hazard ratio[HR]: 0.63, 95% confidence interval[CI]: 0.42-0.96) and overall survival (HR: 0.47, 95% CI: 0.27-0.82) without an increased risk of adverse events requiring systemic antibiotics or steroids. While there were differences in patient characteristics between the present real-world study and the pivotal randomized controlled trial, we demonstrated significant survival benefits and tolerable safety with DC after the completion of CCRT.

What drugs modify the risk of iatrogenic impulse-control disorders in Parkinson's disease? A preliminary pharmacoepidemiologic study.

INTRODUCTION: Parkinson's disease (PD) patients treated with pramipexole (PPX) and ropinirole (ROP) exhibit a higher risk of developing impulse control disorders (ICDs), including gambling disorder, compulsive shopping, and hypersexuality. The management of ICDs in PD is challenging, due to the limited availability of effective therapeutic alternatives or counteractive strategies. Here, we used a pharmacoepidemiological approach to verify whether the risk for PPX/ROP-associated ICDs in PD patients was reduced by drugs that have been posited to exert therapeutic effects on idiopathic ICDs-including atypical antipsychotics (AAs), selective serotonin reuptake inhibitors (SSRIs), and glutamatergic modulators (GMs). METHODS: To quantify the strength of the associations between PPX/ROP and other medications with respect to ICD risk, odds ratios (ORs) were calculated by multivariable logistic regression, adjusting for age, gender, marital status race, psychiatric comorbidities, and use of cabergoline and levodopa. RESULTS: A total of 935 patients were included in the analysis. Use of GMs, SSRIs, and AAs was not associated with a decreased ICD risk in PD patients treated with PPX/ROP; conversely, ICD risk was significantly increased in patients treated with either GMs (Adjusted Odds Ratio, ORa: 14.00 [3.58-54.44]) or SSRIs (ORa: 3.67 [1.07-12.59]). Results were inconclusive for AAs, as available data were insufficient to compute a reliable ORa. CONCLUSIONS: These results suggest that some of the key pharmacological strategies used to treat idiopathic ICD may not be effective for ICDs associated with PPX and ROP in PD patients. Future studies with larger cohorts are needed to confirm, validate, and extend these findings.

Impact of the Transition from ICD-9-CM to ICD-10-CM on the Identification of Pregnancy Episodes in US Health Insurance Claims Data.

BACKGROUND: Before October 2015, pregnancy cohorts assembled from US health insurance claims have relied on medical encounters with International Classification of Diseases-ninth revision-clinical modification (ICD-9-CM) codes. We aimed to extend existing pregnancy identification algorithms into the ICD-10-CM era and evaluate performance. METHODS: We used national private insurance claims data (2005-2018) to develop and test a pregnancy identification algorithm. We considered validated ICD-9-CM diagnosis and procedure codes that identify medical encounters for live birth, stillbirth, ectopic pregnancy, abortions, and prenatal screening to identify pregnancies. We then mapped these codes to the ICD-10-CM system using general equivalent mapping tools and reconciled outputs with literature and expert opinion. Both versions were applied to the respective coding period to identify pregnancies. We required 45 weeks of health plan enrollment from estimated conception to ensure the capture of all pregnancy endpoints. RESULTS: We identified 7,060,675 pregnancy episodes, of which 50.1% met insurance enrollment requirements. Live-born deliveries comprised the majority (76.5%) of episodes, followed by abortions (20.3%). The annual prevalence for all pregnancy types was stable across the ICD transition period except for postterm pregnancies, which increased from 0.5% to 3.4%. We observed that ICD codes indicating gestational age were available for 86.8% of live-born deliveries in the ICD-10 era compared to 23.5% in the ICD-9 era. Patterns of prenatal tests remained stable across the transition period. CONCLUSION: Translation of existing ICD-9-CM pregnancy algorithms into ICD-10-CM codes provided reasonable consistency in identifying pregnancy episodes across the ICD transition period. New codes for gestational age can potentially improve the precision of conception estimates and minimize measurement biases.

Development and validation of an automated algorithm for identifying patients at higher risk for drug-induced acute kidney injury.

PURPOSE: Using information from institutional electronic health records, we aimed to develop dynamic predictive models to identify patients at high risk of acute kidney injury (AKI) among those who received a nephrotoxic medication during their hospital stay. METHODS: Candidate predictors were measured for each of the first 5 hospital days where a patient received a nephrotoxic medication (risk model days) to predict an AKI, using logistic regression with reduced backward variables elimination in 100 bootstrap samples. An AKI event was defined as an increase of serum creatinine ≥ 200% of a baseline SCr within 5 days after a risk model day. Final models were internally validated by replication in 100 bootstrap samples and a risk score for each patient was calculated from the validated model. As performance measures, the area under the receiver operation characteristic curves (AUC) and the number of AKI events among patients who had high risk scores were estimated. RESULTS: The study population included 62,561 admissions followed by 1,212 AKI events (1.9 events/100 admissions). We constructed 5 risk models corresponding to the first 5 hospital days where patients were exposed to at least one nephrotoxic medication. Validated AUCs of the 5 models ranged from 0.78 to 0.81. Depending on risk model day, admissions ranked in the 90th percentile of the risk score captured between 43% to 49% of all AKI events. CONCLUSION: A dynamic prediction model was built successfully for inpatient AKI with excellent discriminative validity and good calibration, allowing clinicians to focus on a select high-risk population that captures the majority of AKI events.

Predicting medication-associated altered mental status in hospitalized patients: Development and validation of a risk model.

PURPOSE: This study presents a medication-associated altered mental status (AMS) risk model for real-time implementation in inpatient electronic health record (EHR) systems. METHODS: We utilized a retrospective cohort of patients admitted to 2 large hospitals between January 2012 and October 2013. The study population included admitted patients aged ≥18 years with exposure to an AMS risk-inducing medication within the first 5 hospitalization days. AMS events were identified by a measurable mental status change documented in the EHR in conjunction with the administration of an atypical antipsychotic or haloperidol. AMS risk factors and AMS risk-inducing medications were identified from the literature, drug information databases, and expert opinion. We used multivariate logistic regression with a full and backward eliminated set of risk factors to predict AMS. The final model was validated with 100 bootstrap samples. RESULTS: During 194,156 at-risk days for 66,875 admissions, 262 medication-associated AMS events occurred (an event rate of 0.13%). The strongest predictors included a history of AMS (odds ratio [OR], 9.55; 95% confidence interval [CI], 5.64-16.17), alcohol withdrawal (OR, 3.34; 95% CI, 2.18-5.13), history of delirium or psychosis (OR, 3.25; 95% CI, 2.39-4.40), presence in the intensive care unit (OR, 2.53; 95% CI, 1.89-3.39), and hypernatremia (OR, 2.40; 95% CI, 1.61-3.56). With a C statistic of 0.85, among patients scoring in the 90th percentile, our model captured 159 AMS events (60.7%). CONCLUSION: The risk model was demonstrated to have good predictive ability, with all risk factors operationalized from discrete EHR fields. The real-time identification of higher-risk patients would allow pharmacists to prioritize surveillance, thus allowing early management of precipitating factors.

Development and validation of an automated algorithm for identifying patients at high risk for drug-induced hypoglycemia.

PURPOSE: Hypoglycemia is one of the most concerning adverse drug events in hospitalized patients. Using information from institutional electronic health records, we aimed to develop dynamic predictive models to identify patients at high risk for hypoglycemia during antihyperglycemic therapy. METHODS: The study population consisted of 21,840 patients who received antihyperglycemic medication on any of the first 5 hospital days (the "risk model days") at 2 large hospitals. Data on candidate predictors were extracted from discrete electronic health record fields to construct models for predicting hypoglycemia within 24 hours after each risk model day. Final models were internally validated by replication in 100 bootstrap samples and reapplying model parameters to the original risk population. RESULTS: The development and validation sample included 60,762 risk model days followed by 1,256 days with hypoglycemic events (2.07 events per 100 risk model days). The days 3, 4, and 5 models presented similar associations between predictors and the risk of hypoglycemia and were therefore collapsed into a single model. The strongest hypoglycemia risk factors across all 3 risk periods (day 1, day 2, and days 3-5) were blood glucose (BG) fluctuations, BG trend, history of hypoglycemia, lower body weight, lower creatinine clearance, use of long-acting or high-dose insulin, and sulfonylurea use. C statistics for the 3 models ranged from 0.844 to 0.887. Depending on the model used, risk scores in the upper 90th percentile predicted 48.5-63.1% of actual hypoglycemic events. It was estimated that by targeting only patients in the upper 90th percentile, providers would need to intervene during fewer than 9 admissions to prevent 1 hypoglycemic event. CONCLUSION: The developed prediction models were found to have excellent discriminative validity and good calibration, allowing clinicians to focus interventions on a select high-risk population in which the majority of hypoglycemic events occur.

Acute kidney injury risk associated with piperacillin/tazobactam compared with cefepime during vancomycin therapy in hospitalised patients: a cohort study stratified by baseline kidney function.

Recent studies have found an association between piperacillin/tazobactam when added to vancomycin and acute kidney injury (AKI) risk. However, studies were limited by the small sample size and residual confounding. The aim of this study was to compare the risk of AKI with vancomycin plus piperacillin/tazobactam (VPT) versus vancomycin plus cefepime (VC) and to examine whether pre-existing renal impairment mediates the risk. This was a retrospective cohort study using electronic health records for patients admitted to two hospitals in 2012-2013. The outcome, AKI, was defined as an increase in serum creatinine level of ≥0.3 mg/dL or ≥50% from baseline. Patients were stratified by level of renal impairment as estimated by baseline creatinine clearance. Inverse probability of treatment weighting was used to balance baseline covariates between groups. Cox proportional hazards regression was used to evaluate VPT risk of AKI compared with VC. A total of 935 (17.53%) AKI cases were identified among 5335 patients receiving VPT or VC. VPT was associated with a higher risk of AKI relative to VC, with an adjusted hazard ratio (aHR) of 1.25 [95% confidence interval (CI) 1.11-1.42] in the total population and 1.70 (95% CI 1.44-2.02) in patients with normal baseline renal function. However, no elevated risk was found in patients with prior renal impairment (aHR = 0.81, 95% CI 0.65-1.01). VPT was associated with a higher risk of AKI relative to VC. The association was true in patients with normal renal function but not in those with pre-existing renal impairment.

Identifying and characterizing preventable adverse drug events for prioritizing pharmacist intervention in hospitals.

PURPOSE: The approach and results for identifying and characterizing preventable adverse drug events (pADEs) that are key targets for pharmacist medication therapy management (MTM) are summarized. METHODS: This study was part of a larger effort aimed at developing an electronic health record-based prediction model (the complexity score, or C-score) that ranks hospitalized patients according to their risk for pADEs. An environmental scan of published epidemiologic pADE studies and national patient safety priority areas was conducted. The final list of candidate pADEs was then disseminated to ASHP members and a national technical expert panel (TEP) to evaluate the importance, prevalence, severity, preventability, and measurability of these pADEs. Polychoric correlation tests were performed to evaluate and quantify associations between importance and any of the constructs' mean rankings for each individual pADE. RESULTS: The environmental scan yielded a total of 21 candidate pADEs, including drug-induced acute kidney injury, falls, respiratory depression, altered mental status, hemorrhage, hepatic failure, hypoglycemia, seizures, hypotension and bradycardia, ileus, blood dyscrasias, severe electrolyte imbalances, prolonged hyperglycemia, uncontrolled hypertension, uncontrolled arrhythmia, stress ulcers, hospital-acquired infections, uncontrolled hospital-acquired or community-acquired infection, uncontrolled pain, and venous thromboembolism. The survey confirmed all pADEs were important. Ranking of overall importance was mainly driven by perceived pADE severity and, to a lesser extent, by preventability and prevalence ratings. CONCLUSION: A literature review and survey of ASHP and TEP members were used to compile a list of important hospital-acquired pADEs for incorporation into a model for prioritizing patients for MTM services.

Measurement of selected preventable adverse drug events in electronic health records: Toward developing a complexity score.

PURPOSE: The defining of a select number of high-priority preventable adverse drug events (pADEs) for measurement in the electronic health record (EHR) and the estimation of pADE incidences in two tertiary care facilities are described. METHODS: This study was part of a larger effort aimed at developing an automated electronic health record (EHR)-based complexity-score (C-score) that ranks hospitalized patients according to their risk for pADEs for clinical intervention. We developed measures for 16 high-priority pADEs often deemed preventable using discrete clinical and administrative EHR data. For each pADE we specified inclusion and exclusion criteria that were used to define risk populations for each specific pADE. The incidence of each type of pADE was then measured during a designated follow-up period considering all adult admissions to 2 large academic tertiary care hospitals, who were eligible for the pADE-specific risk populations during any of their first 5 hospital days. RESULTS: Utilizing the data from 83,787 admissions who were at risk for at least one pADE during at least one of their first five hospital days, we found that 27,193 admissions (32.5%) developed at least one pADE. Uncontrolled postsurgical pain, uncontrolled pneumonia, and drug-associated hypotension had the highest incidences with the following number of days with pADE per number of patients at risk: 13,484 of 19,640; 527 of 1,530; and 13,394 of 43,630, while drug-associated falls (446 of 75,036), drug-associated acute mental status changes (262 of 66,875) and venous thromboembolism (214 of 74,283) had the lowest incidence rates. CONCLUSION: EHR-based definitions of clinically important pADEs were developed, and the incidence of the pADEs was estimated. These definitions will be advanced for the creation of prediction models to develop a C-score for identifying patients at risk for pADEs to prioritize pharmacist intervention.

Development and validation of a complexity score to rank hospitalized patients at risk for preventable adverse drug events.

PURPOSE: The development of risk models for 16 preventable adverse drug events (pADEs) and their aggregation into the final complexity score (C-score) are described. METHODS: Using data from 2 tertiary care facilities, logistic regression models were constructed for the first 5 hospital days that admissions were at risk for each of 16 pADEs. The best model for each pADE was validated in 100 bootstrap samples. The C-score was then aggregated and predicted individual pADE risk as the probability to develop at least 1 pADE. Using the 100 bootstrap samples for each pADE, 100 C-scores for validation were generated. RESULTS: We utilized electronic health records (EHR) data from 65,518 admissions to UF Health Shands and 18,269 admissions to UF Health Jacksonville to develop risk models for 16 pADEs. Most models had very strong discriminant validity (C-statistic > 0.8), with the highest predicted decile representing about half of manifest pADEs. Among admissions in the highest C-score decile, about two thirds experienced at least 1 pADE (C-statistic, 0.838; 95% confidence interval, 0.838-0.839). C-score precision, defined as the percentage of patients consistently (i.e., at least 95 of 100 samples) ranked in the 90th percentile, was 80-84%. CONCLUSION: The C-score was developed and validated for the identification of hospitalized patients at highest risk for pADEs. Aggregation of individual prediction models into a single score reduced its predictive power for most pADEs, compared with the individual risk models, but concentrated in the highest C-score decile a patient group more than two thirds of whom experienced at least 1 pADE.