The Identification of Subphenotypes and Associations with Health Outcomes in Patients with Opioid-Related Emergency Department Encounters Using Latent Class Analysis.
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ABSTRACT:
SUBMITTER: Chhabra N
PROVIDER: S-EPMC9321801 | biostudies-literature | 2022 Jul
REPOSITORIES: biostudies-literature
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The Identification of Subphenotypes and Associations with Health Outcomes in Patients with Opioid-Related Emergency Department Encounters Using Latent Class Analysis.
Chhabra Neeraj N Smith Dale L DL Maloney Caitlin M CM Archer Joseph J Sharma Brihat B Thompson Hale M HM Afshar Majid M Karnik Niranjan S NS
International journal of environmental research and public health 20220721 14
The emergency department (ED) is a critical setting for the treatment of patients with opioid misuse. Detecting relevant clinical profiles allows for tailored treatment approaches. We sought to identify and characterize subphenotypes of ED patients with opioid-related encounters. A latent class analysis was conducted using 14,057,302 opioid-related encounters from 2016 through 2017 using the National Emergency Department Sample (NEDS), the largest all-payer ED database in the United States. The ...[more]
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Project description:Study objectiveWe describe the prevalence, trends, and factors associated with repeated emergency department (ED) encounters for opioid usage across multiple, independent hospital systems.MethodsA statewide regional health information exchange system provided ED encounters from 4 Indiana hospital systems for 2012 to 2017. In accordance with a series of International Classification of Diseases, Ninth Revision (ICD-9) and ICD-10 diagnosis codes for opioid abuse, adverse effects of opioids, opioid dependence and unspecified use, and opioid poisoning, we identified patients with an ED encounter associated with opioid usage (9,295 individuals; 12,642 encounters). Multivariate logistic regression models then described the patient, encounter, prescription history, and community characteristics associated with the odds of a patient's incurring a subsequent opioid-related ED encounter.ResultsThe prevalence of repeated nonfirst opioid-related ED encounters increased from 9.0% of all opioid encounters in 2012 to 34.3% in 2017. The number of previous opioid-related ED encounters, unique institutions at which the individual had had encounters, the encounter's being heroin-related, the individual's having a benzodiazepine prescription filled within 30 days before the encounter, and being either Medicaid insured or uninsured compared with private insurance were associated with significantly greater odds of having a subsequent encounter.ConclusionThe ED is increasingly a site utilized as the setting for repeated opioid-related care. Characteristics of the individual, encounter, and community associated with repeated opioid-related encounters may inform real-time risk-prediction tools in the ED setting. Additionally, the number of institutions to which the individual has presented may suggest the utility of health information exchange data and usage in the ED setting.
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Project description:ObjectiveTo determine the rate at which commercially-insured patients fill prescriptions for naloxone after an opioid-related ED encounter as well as patient characteristics associated with obtaining naloxone.MethodsThis is a retrospective cohort study of adult patients discharged from the ED following treatment for an opioid-related condition from 2016 to 2018 using a commercial insurance claims database (Optum Clinformatics® Data Mart). The primary outcome was a pharmacy claim for naloxone in the 30 days following the ED encounter. A multivariable logistic regression model examined the association of patient characteristics with filled naloxone prescriptions, and predictive margins were used to report adjusted probabilities with 95% confidence intervals.Results21,700 patients had opioid-related ED encounters during the study period, of which 1743 (8.0%) had encounters for heroin overdose, 8825 (40.7%) for overdose due to other opioids, 5400 (24.9%) for withdrawal, and 5732 (26.4%) for other opioid use disorder conditions. 230 patients (1.1%) filled a prescription for naloxone within 30 days. Patients with heroin overdose (2.6%; 95%CI 1.7 to 3.4), recent prescriptions for opioid analgesics (1.4%; 95%CI 1.1 to 1.7), recent prescriptions for buprenorphine (1.9%; 95%CI 1.0 to 2.9), and naloxone prescriptions in the prior year (3.3%; 95%CI 1.8 to 4.8) were more likely to obtain naloxone. The rate was significantly higher in 2018 [1.9% (95%CI 1.5 to 2.2)] as compared to 0.4% (95%CI 0.3 to 0.6) in 2016.ConclusionsFew patients use insurance to obtain naloxone by prescription following opioid-related ED encounters. Clinical and policy interventions should expand distribution of this life-saving medication in the ED.
| S-EPMC8608552 | biostudies-literature
Project description:ObjectivesFrequent emergency department users represent a small proportion of users while cumulating many visits. Previously identified factors of frequent use include high physical comorbidity, mental health disorders, poor socioeconomic status and substance abuse. However, frequent users do not necessarily exhibit all these characteristics and they constitute a heterogeneous population. This study aims to establish profiles of frequent emergency department users in an adult population with chronic conditions.DesignThis is a retrospective cohort study using administrative databases.SettingAll adults who visited the emergency department between 2012 and 2013 (index date) in the province of Quebec (Canada), diagnosed with at least one chronic condition, and without dementia were included. Patients living in remote areas and who died in the year following their index date were excluded. We used latent class analysis, a probability-based model to establish profiles of frequent emergency department users. Frequent use was defined as having five visits or more during 1 year. Patient characteristics included sociodemographic characteristics, physical and mental comorbidities and prior healthcare utilisation.ResultsOut of 4 51 775 patients who visited emergency departments at least once in 2012-2013, 13 676 (3.03%) were frequent users. Four groups were identified: (1) 'low morbidity' (n=5501, 40.2%), (2) 'high physical comorbidity' (n=3202, 23.4%), (3) 'injury or chronic non-cancer pain' (n=2313, 19.5%) and (4) 'mental health or alcohol/substance abuse' (n=2660, 16.9%).ConclusionsThe four profiles have distinct medical and socioeconomic characteristics. These profiles provide useful information for developing tailored interventions that would address the specific needs of each type of frequent emergency department users.
| S-EPMC9528600 | biostudies-literature
Project description:ImportancePatients treated in emergency departments (EDs) for opioid overdose often need drug treatment yet are rarely linked to services after discharge. Emergency department-based peer support is a promising approach for promoting treatment linkage, but evidence of its effectiveness is lacking.ObjectiveTo examine the association of the Opioid Overdose Recovery Program (OORP), an ED peer recovery support service, with postdischarge addiction treatment initiation, repeat overdose, and acute care utilization.Design, setting, and participantsThis intention-to-treat retrospective cohort study used 2014 to 2020 New Jersey Medicaid data for Medicaid enrollees aged 18 to 64 years who were treated for nonfatal opioid overdose from January 2015 to June 2020 at 70 New Jersey acute care hospitals. Data were analyzed from August 2022 to November 2023.ExposureHospital OORP implementation.Main outcomes and measuresThe primary outcome was medication for opioid use disorder (MOUD) initiation within 60 days of discharge. Secondary outcomes included psychosocial treatment initiation, medically treated drug overdoses, and all-cause acute care visits after discharge. An event study design was used to compare 180-day outcomes between patients treated in OORP hospitals and those treated in non-OORP hospitals. Analyses adjusted for patient demographics, comorbidities, and prior service use and for community-level sociodemographics and drug treatment access.ResultsA total of 12 046 individuals were included in the study (62.0% male). Preimplementation outcome trends were similar for patients treated in OORP and non-OORP hospitals. Implementation of the OORP was associated with an increase of 0.034 (95% CI, 0.004-0.064) in the probability of 60-day MOUD initiation in the half-year after implementation, representing a 45% increase above the preimplementation mean probability of 0.075 (95% CI, 0.066-0.084). Program implementation was associated with fewer repeat medically treated overdoses 4 half-years (-0.086; 95% CI, -0.154 to -0.018) and 5 half-years (-0.106; 95% CI, -0.184 to -0.028) after implementation. Results differed slightly depending on the reference period used, and hospital-specific models showed substantial heterogeneity in program outcomes across facilities.Conclusions and relevanceIn this cohort study of patients treated for opioid overdose, OORP implementation was associated with an increase in MOUD initiation and a decrease in repeat medically treated overdoses. The large variation in outcomes across hospitals suggests that treatment effects were heterogeneous and may depend on factors such as implementation success, program embeddedness, and availability of other hospital- and community-based OUD services.
| S-EPMC10964115 | biostudies-literature
Project description:IntroductionOpioid addiction and misuse constitute a public health crisis in the United States. Recent research supports buprenorphine induction in the emergency department (ED) setting for patients with opioid use disorder (OUD). However, education regarding buprenorphine induction for emergency medicine (EM) physicians, residents, and students is still limited.MethodsWe created a 1-hour introductory workshop for the identification and treatment of opioid withdrawal and OUD in the ED for medical students going into EM and for EM interns. The workshop consisted to two distinct curricular sections: (1) a didactic session providing an overview of the basic knowledge and skills to identify and treat patients with OUD in the ED and (2) a case-based session in which students worked through the identification of opioid withdrawal; discussion of opioid use with the patient, going through the steps of SBIRT (screening, brief intervention, and referral to treatment); and considerations when starting buprenorphine. The workshop was evaluated using a pre- and posttest examining medical knowledge around buprenorphine use in the ED.ResultsA total of 48 students and interns participated in the curriculum. The students showed a significant improvement in medical knowledge between the pre- and posttests, with an average 45% higher score on the posttest (p < .001).DiscussionOur workshop resulted in a short-term improvement in medical students' and interns' knowledge of the identification and treatment of patients with OUD in the ED.
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Project description:ObjectiveTo characterise subphenotypes of self-reported symptoms and outcomes (SRSOs) in postacute sequelae of COVID-19 (PASC).DesignProspective, observational cohort study of subjects with PASC.SettingAcademic tertiary centre from five clinical referral sources.ParticipantsAdults with COVID-19 ≥20 days before enrolment and presence of any new self-reported symptoms following COVID-19.ExposuresWe collected data on clinical variables and SRSOs via structured telephone interviews and performed standardised assessments with validated clinical numerical scales to capture psychological symptoms, neurocognitive functioning and cardiopulmonary function. We collected saliva and stool samples for quantification of SARS-CoV-2 RNA via quantitative PCR.Outcomes measuresDescription of PASC SRSOs burden and duration, derivation of distinct PASC subphenotypes via latent class analysis (LCA) and relationship with viral load.ResultsWe analysed baseline data for 214 individuals with a study visit at a median of 197.5 days after COVID-19 diagnosis. Participants reported ever having a median of 9/16 symptoms (IQR 6-11) after acute COVID-19, with muscle-aches, dyspnoea and headache being the most common. Fatigue, cognitive impairment and dyspnoea were experienced for a longer time. Participants had a lower burden of active symptoms (median 3 (1-6)) than those ever experienced (p<0.001). Unsupervised LCA of symptoms revealed three clinically active PASC subphenotypes: a high burden constitutional symptoms (21.9%), a persistent loss/change of smell and taste (20.6%) and a minimal residual symptoms subphenotype (57.5%). Subphenotype assignments were strongly associated with self-assessments of global health, recovery and PASC impact on employment (p<0.001) as well as referral source for enrolment. Viral persistence (5.6% saliva and 1% stool samples positive) did not explain SRSOs or subphenotypes.ConclusionsWe identified three distinct PASC subphenotypes. We highlight that although most symptoms progressively resolve, specific PASC subpopulations are impacted by either high burden of constitutional symptoms or persistent olfactory/gustatory dysfunction, requiring prospective identification and targeted preventive or therapeutic interventions.
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Project description:Background: Transarterial chemoembolization (TACE) is the standard first-line therapy for intermediate-stage hepatocellular carcinoma (HCC). However, no latent-classing indices, concerning repeat conventional TACE or switching to another treatment, have been incorporated into the guidelines. Methods: The unsupervised latent class modeling was applied to identify subphenotypes using the clinical and medical imaging data of 1517 HCC patients after the first TACE from four hospitals (derivation cohort: 597 cases; validation cohort: 920 cases); modeling was conducted independently in each cohort. We then explored the relationship of subphenotypes with clinical outcomes in both cohorts and response to treatment strategies after the first TACE in the derivation cohort. Results: Independent latent class models suggested that a three-class model was optimal for both cohorts. In both cohorts, we identified a TACE-refractory subphenotype (Phenotype 1: PS score 1, stage progress, more intrahepatic lesions, and new intrahepatic lesions), TACE-responsive subphenotype (Phenotype 3: PS score 0, No intrahepatic lesions and new intrahepatic lesions), compared to TACE-intermediate subphenotype (Phenotype 2). Compared to Phenotype 1 or 2, patients in Phenotype 3 had significantly lower 3-month or 3-year mortality (all P<0.001). In the derivation cohort, the effects of treatment strategy (surgery/ablation vs. repeat TACE vs. stop TACE) differed significantly in phenotype 2 but not in phenotype 3 (P=0.721 for interaction). Conclusions: Latent class models identified three subphenotypes for HCC after the first TACE treatment. Differences were significant in clinical outcome and response to treatment strategy after the first TACE among three subphenotypes.
| S-EPMC9516009 | biostudies-literature
Project description:BackgroundSince COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.Research questionDoes the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes?Study design and methodsWe included adult patients (≥ 18 years) positive for laboratory-confirmed SARS-CoV-2 infection from a prospective COVID-19 registry database in the Cleveland Clinic Health System in Ohio and Florida. The patients were split into training and testing sets. Using latent class analysis (LCA), we first identified phenotypic clusters of patients with COVID-19 based on demographics, comorbidities, and presenting symptoms. We then identified subphenotypes of hospitalized patients with additional blood biomarker data measured on hospital admission. The associations of phenotypes/subphenotypes and clinical outcomes were investigated. Multivariable prediction models were established to predict assignment to the LCA-defined phenotypes and subphenotypes and then evaluated on an independent testing set.ResultsWe analyzed data for 20,572 patients. Seven phenotypes were identified on the basis of different profiles of presenting COVID-19 symptoms and existing comorbidities, including the following groups: young, no symptoms; young, symptoms; middle-aged, no symptoms; middle-aged, symptoms; middle-aged, comorbidities; old, no symptoms; and old, symptoms. The rates of inpatient hospitalization for the phenotypes were significantly different (P < .001). Five subphenotypes were identified for the subgroup of hospitalized patients, including the following subgroups: young, elevated WBC and platelet counts; middle-aged, lymphopenic with elevated C-reactive protein; middle-aged, hyperinflammatory; old, leukopenic with comorbidities; and old, hyperinflammatory with kidney dysfunction. The hospital mortality and the times from hospitalization to ICU transfer or death were significantly different (P < .001). The models for predicting the LCA-defined phenotypes and subphenotypes showed high discrimination (concordance index, 0.92 and 0.91).InterpretationHypothesis-free LCA-defined phenotypes and subphenotypes of patients with COVID-19 can be identified. These may help clinical investigators conduct stratified analyses in clinical trials and assist basic science researchers in characterizing the pathobiology of the spectrum of COVID-19 presentations.
| S-EPMC7907753 | biostudies-literature
Project description:PurposeSeptic shock is a highly heterogeneous condition which is part of the challenge in its diagnosis and treatment. In this study we aim to identify clinically relevant subphenotypes of septic shock using a novel statistic al approach.MethodsBaseline patient data from a large global clinical trial of septic shock (n = 1696) was analysed using latent class analysis (LCA). This approach allowed investigators to identify subgroups in a heterogeneous population by estimating a categorical latent variable that detects relatively homogeneous subgroups within a complex phenomenon.ResultsLCA identified six different, clinically meaningful subphenotypes of septic shock each with a typical profile: (1) "Uncomplicated Septic Shock, (2) "Pneumonia with adult respiratory distress syndrome (ARDS)", (3) "Postoperative Abdominal", (4) "Severe Septic Shock", (5): "Pneumonia with ARDS and multiple organ dysfunction syndrome (MODS)", (6) "Late Septic Shock". The 6-class solution showed high entropy approaching 1 (i.e., 0.92), indicating there was excellent separation between estimated classes.ConclusionsLCA appears to be an applicable statistical tool in analysing a heterogenous clinical cohort of septic shock. The results may lead to a better understanding of septic shock complexity and form a basis for considering targeted therapies and selecting patients for future clinical trials.
| S-EPMC7416734 | biostudies-literature
Project description:ImportanceThe health care system has undergone major changes in the past decade, and emergency department (ED) crowding has worsened over time; however, the most recent patterns in ED capacity and use in California have yet to be studied.ObjectiveTo analyze patterns in ED capacity and utilization in California hospitals from 2011 to 2021.Design, setting, and participantsThis retrospective cohort study used data from the California Department of Health Care Access and Information and the US Census Bureau to analyze ED facility characteristics from more than 400 general acute care hospitals with more than 320 EDs in California as well as patients who presented to those EDs between January 1, 2011, and December 31, 2021.Main outcomes and measuresLinear patterns (measured by percentage change) in total annual ED capacity (volume of hospital beds, EDs, ED treatment stations, and trauma centers) and ED use (ED visits by disposition and acuity) were assessed as primary outcomes. Patterns in ambulance diversion hours and the number of patients who left the ED without being seen were also examined as secondary outcomes. Visit acuity was categorized into 5 levels by increasing severity (minor, low to moderate, moderate, severe without threat, and severe with threat) based on California Department of Health Care Access and Information descriptions corresponding to Current Procedural Terminology codes.ResultsIn the prepandemic period (2011-2019), the total population of California increased from 37 638 369 to 39 512 223 (5.0%; 95% CI, 4.1%-5.8%), then decreased to 39 237 836 in 2021 (0.7%; 95% CI, -3.9% to 2.5%). Over the entire study period (2011-2021), the total California population increased by 4.2% (95% CI, 3.3%-5.2%). From 2011 to 2019, the annual number of ED visits increased from 12 054 885 to 14 876 653 (23.4%; 95% CI, 20.0%-26.8%) before decreasing to 12 944 692 in 2021 (-13.0%; 95% CI, -33.1% to 7.1%); from 2011 to 2021, total ED visits increased by 7.4% (95% CI, 5.6%-9.1%). From 2011 to 2021, the total number of EDs decreased from 339 to 326 (-3.8%; 95% CI, -4.4% to -3.2%) and the total number of hospital beds decreased from 75 940 to 74 052 (-2.5%; 95% CI, -3.3% to -1.6%), while the number of ED treatment stations in these fewer EDs increased from 7159 to 8667 (21.1%; 95% CI, 19.7%-22.4%). The number of visits rated as severe with threat also increased, from 2 011 637 in 2011 to 3 375 539 in 2021 (67.8%; 95% CI, 59.7%-75.9%), while visits rated as minor decreased from 913 712 to 336 071 (-63.2%; 95% CI, -75.2% to -51.2%) over the same period.Conclusions and relevanceIn this cohort study, multiple measures of ED capacity did not proportionally increase with the increasing demand for services; however, the COVID-19 pandemic appears to have substantially affected some of these patterns. These findings may be helpful to policy makers and health care stakeholders when planning resource allocation of limited health care resources.
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