OBJECTIVE: To quantify the association of ambient air pollution (particulate matter, PM2.5) exposure with medically attended acute respiratory illness among infants with bronchopulmonary dysplasia (BPD).
METHODS: Single center, retrospective cohort study of preterm infants with BPD in Metropolitan Philadelphia. Multivariable logistic regression quantified associations of annual mean PM2.5 exposure (per μg/m3) at the census block group level with medically attended acute respiratory illness, defined as emergency department (ED) visits or hospital readmissions within a year after first hospital discharge adjusting for age at neonatal intensive care unit (NICU) discharge, year, sex, race, insurance, BPD severity, and census tract deprivation. As a secondary analysis, we examined whether BPD severity modified the associations.
RESULTS: Of the 378 infants included in the analysis, 189 were non-Hispanic Black and 235 were publicly insured. Census block PM2.5 level was not significantly associated with medically attended acute respiratory illnesses, ED visits, or hospital readmissions in the full study cohort. We observed significant effect modification by BPD grade; each 1 µg/m3 higher annual PM2.5 exposure was medically attended acute respiratory illness (adjusted odds ratio [aOR] 1.65, 95% CI: 1.06-2.63) among infants with Grade 1 BPD but not among infants with grade 3 BPD (aOR 0.83, 95% CI: 0.47-1.48) (interaction p = .024).
CONCLUSIONS: Cumulative PM2.5 exposure in the year after NICU discharge was not significantly associated with medically attended acute respiratory illness among infants with BPD. However, infants with Grade 1 BPD had significantly higher odds with higher exposures. If replicated, these findings could inform anticipatory guidance for families of these infants to avoid outdoor activities during high pollution days after NICU discharge.

OBJECTIVE: Patients surviving acute pulmonary embolism (PE) necessitate long-term treatment and follow-up. However, the chronic economic impact of PE on European healthcare systems remains to be determined.
RESULTS: We calculated the direct cost of illness during the first year after discharge for the index PE, analyzing data from a multicentre prospective cohort study in Germany. Main and accompanying readmission diagnoses were used to calculate DRG-based hospital reimbursements; anticoagulation costs were estimated from the exact treatment duration and each drug\'s unique national identifier; and outpatient post-PE care costs from guidelines-recommended algorithms and national reimbursement catalogues. Of 1017 patients enrolled at 17 centres, 958 (94%) completed ≥ 3-month follow-up; of those, 24% were rehospitalized (0.34 [95% CI 0.30-0.39] readmissions per PE survivor). Age, coronary artery, pulmonary and kidney disease, diabetes, and (in the sensitivity analysis of 837 patients with complete 12-month follow-up) cancer, but not recurrent PE, were independent cost predictors by hurdle gamma regression accounting for zero readmissions. Estimated rehospitalization cost was €1138 (95% CI 896-1420) per patient. Anticoagulation duration was 329 (IQR 142-365) days, with estimated average per-patient costs of €1050 (median 972; IQR 458-1197); costs of scheduled ambulatory follow-up visits amounted to €181. Total estimated direct per-patient costs during the first year after PE ranged from €2369 (primary analysis) to €2542 (sensitivity analysis).
CONCLUSIONS: By estimating per-patient costs and identifying cost drivers of post-PE care, our study may inform decisions concerning implementation and reimbursement of follow-up programmes aiming at improved cardiovascular prevention. (Trial registration number: DRKS00005939).

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UNASSIGNED: Identifying predictors of readmissions after transcatheter aortic valve implantation (TAVI) is an important unmet need.
UNASSIGNED: We sought to explore the role of machine learning (ML) in predicting readmissions after TAVI.
UNASSIGNED: We included patients who underwent TAVI between 2016 and 2019 in the Nationwide Readmission Database. A total of 917 candidate predictors representing all International Classification of Diseases, Tenth Revision, diagnosis and procedure codes were included. First, we used lasso regression to remove noninformative variables and rank informative ones. Next, we used an unsupervised ML model (K-means) to identify patterns/clusters in the data. Furthermore, we used Light Gradient Boosting Machine and Shapley Additive exPlanations to specify the impact of individual predictors. Finally, we built a parsimonious model to predict 30-day readmission.
UNASSIGNED: A total of 117,398 and 93,800 index TAVI hospitalizations were included in the 30- and 90-day analyses, respectively. Lasso regression identified 138 and 199 informative predictors for the 30- and 90-day readmission, respectively. Next, K-means recognized 2 distinct clusters: low risk and high risk. In the 30-day cohort, the readmission rate was 10.1% in the low risk group and 23.3% in the high risk group. In the 90-day cohort, the rates were 17.4% and 35.3%, respectively. The top predictors were the length of stay, frailty score, total discharge diagnoses, acute kidney injury, and Elixhauser score. These predictors were incorporated into a risk score (TAVI readmission score), which exhibited good performance in an external validation cohort (area under the curve 0.74 [0.7-0.78]).
UNASSIGNED: ML methods can leverage widely available administrative databases to identify patients at risk for readmission after TAVI, which could inform and improve post-TAVI care.

UNASSIGNED: Heart failure (HF) is a leading cause of readmission after cardiac surgery, yet risk factors for HF readmission after cardiac surgery remain poorly characterized.
UNASSIGNED: This study aimed to identify risk factors associated with 30-day HF-specific readmissions after cardiac surgery using a national database.
UNASSIGNED: We queried the 2016 to 2018 National Readmissions Database to identify U.S. patients who underwent coronary artery bypass grafting (CABG), mitral valve repair/replacement, and/or aortic valve repair/replacement. Exclusion criteria included history of ventricular assist device or heart transplant, dialysis-dependent renal insufficiency, and death during index admission. Clinical variables were defined using International Classification of Diseases-10th Revision codes. The primary outcome was a 30-day readmission for HF following discharge. Multivariable logistic regression was used to account for relevant clinical and demographic covariates and identify independent risk factors for HF readmissions following cardiac surgery.
UNASSIGNED: Our study included 394,050 patients who underwent cardiac surgery (mean age 66 ± 12 years, 63% isolated CABG, 27% isolated valve, 11% CABG + valve). Of these patients, 7,318 were readmitted within 30 days of discharge for a principal diagnosis of HF. Independent risk factors of HF-specific readmission included older age, female sex, prolonged length of stay, comorbid congestive HF, nondialysis dependent chronic kidney disease, chronic obstructive pulmonary disease, chronic liver disease, obesity, atrial fibrillation, and acute kidney injury. Prior CABG was marginally protective for HF-specific readmission.
UNASSIGNED: Using a national registry, we identified risk factors associated with HF readmission after cardiac surgery. Further analysis of these risk factors and their association with HF readmission is warranted.

Pediatric heart failure (HF) is associated with high readmission rates, but the optimal serum potassium range for this population remains unclear. In this single-center retrospective cohort study, 180 pediatric patients hospitalized for HF between January 2016 and January 2022 were stratified into low-potassium (<3.7 mmol/L), middle-potassium (3.7-4.7 mmol/L), and high-potassium (≥4.7 mmol/L) groups based on the distribution of potassium levels in the study population. The primary outcome was readmission for HF within 1 year of discharge. Cox regression and restricted cubic spline models were used to assess the association between potassium levels and 1-year HF readmission rates. Notably, 38.9% of patients underwent 1 or more 1-year readmissions for HF within 1 year. The high-potassium group had a significantly higher readmission frequency than the middle-potassium group. In multivariate Cox regression models, potassium levels of ≥4.7 mmol/L were independently associated with increased 1-year readmission risk. A J-shaped relationship was observed between baseline potassium levels and 1-year readmission risk, with the lowest risk at 4.1 mmol/L. In pediatric patients with HF, a serum potassium level ≥ 4.7 mmol/L was independently associated with increased 1-year readmission risk. Maintaining potassium levels within a narrow range may improve outcomes in this population.

OBJECTIVE: To evaluate the effect of a novel, co-designed, digital AF educational program, \'INFORM-AF\', to reduce re-hospitalisation of people with AF. The secondary aims are to examine the effect of the intervention on: (a) reducing cardiovascular-related hospitalisation, (b) increasing medication adherence, AF-related knowledge, and Atrial fibrillation (AF)-related quality of life and (c) determining the cost-effectiveness of the intervention.
BACKGROUND: AF is an increasingly prevalent cardiac arrythmia that involves complex clinical management. Comprehensive education is essential for successful self-management of AF and is associated with positive health-related outcomes. There has been an increase in technology-based education for AF. However, its effects on hospitalisation, medication adherence and patient-reported outcomes are unclear.
METHODS: A prospective, randomised (1:1), open-label, blinded-endpoint, multicentre clinical trial.
METHODS: Eligible participants are aged 18 years or above, diagnosed with AF, and own a smartphone. The study will be conducted at two metropolitan hospitals. In the intervention group, participants will receive the AF educational program delivered via Qstream®. In the control group, participants will receive the Stroke Foundation \'Living with AF\' booklet. The primary outcome is re-hospitalisation within 12 months from an indexed presentation or hospital admission.
CONCLUSIONS: This clinical trial is part of a developing program of work that will examine mHealth educational-behavioural interventions on cardiovascular outcomes. Findings from this pilot study will inform the development of a digital educational framework for patients living with AF.
UNASSIGNED: There remain many gaps in providing high-quality patient education for patients with AF. This trial will test a new theory-driven, smartphone-based education program on important clinical outcomes, including rehospitalisation.
CONCLUSIONS: This study evaluates a novel, co-designed, digital AF educational program, \'INFORM-AF\', to reduce the re-hospitalisation of people with AF. Study results are expected to be reported in 2025. Findings are expected to inform practice recommendations for AF patient education that may be included in future clinical practice guideline recommendations.
UNASSIGNED: SPIRIT Checklist.
UNASSIGNED: JL is a consumer co-researcher on the project and provided critical input into intervention design, and feedback and input across the study duration.

UNASSIGNED: People living with schizophrenia spectrum disorder (SSD) have a higher death rate which is caused, in part, by poorer adherence to treatment as compared to those with other mental illnesses. Using long-acting injectable antipsychotic (LAI) medications can improve medication adherence and reduce hospitalizations for people living with SSD but are often underutilized.
UNASSIGNED: As compared to oral antipsychotic medications provided to patients with SSD at discharge from a psychiatric hospitalization, being provided with an LAI antipsychotic medication may reduce subsequent rehospitalization. Specifically, patients discharged on an atypical or second-generation LAI medication are less likely to be readmitted to the hospital when compared to those discharged on a typical first-generation oral medication.
CONCLUSIONS: Because LAI antipsychotic medications are often underutilized as treatment options, the study findings suggest that this modality may be considered for patients with SSD when being discharged from a psychiatric hospitalization. Ideally, psychiatric-mental health nurses can educate patients about indications, benefits, and risks of using atypical or second-generation LAI antipsychotic medications during hospitalization and at discharge prevent the risk for future rehospitalizations.
UNASSIGNED: INTRODUCTION: People living with schizophrenia spectrum disorder (SSD) have poorer medication adherence compared to those with other mental illnesses. Long-acting injectable antipsychotic (LAI) medication use is associated with greater adherence, reduced re-hospitalizations, and improved recovery outcomes when compared to oral formulations.
OBJECTIVE: To compare LAI antipsychotic medication use versus oral formulations on readmission to an inpatient hospital.
METHODS: Medical records (N = 707) from a state psychiatric hospital in the southern region of the United States were reviewed. Controlling for demographic variables, logistic regression analyses were used to examine LAI compared to oral formulations on readmission.
RESULTS: Compared to patients discharged with oral antipsychotic medications, those with LAIs had a lower proportion of readmission rates in 6-month and 1-year periods, but not 30-day or 2-year periods. When controlling for demographic variables, those discharged with an atypical LAI had significantly lower odds of being readmitted within the 24-year period compared to those discharged on a typical oral antipsychotic.
CONCLUSIONS: Compared to orals, LAIs do not increase and may mitigate readmissions to psychiatric hospitalization.
CONCLUSIONS: Psychiatric-mental health nurses and other professionals may recommend LAIs when indicated for those with SSD.

BACKGROUND: Robot-assisted ventral hernia repair is associated with decreased length of stay and lower complication rates compared with open repair, but acquisition and maintenance of the robotic system is costly. The aim of this was study was to compare the procedure-specific cost of robot-assisted and open ventral and incisional hernia repair including cost of procedure-related readmissions and reoperations within 90 days postoperatively.
METHODS: Single-center retrospective cohort study of 100 patients undergoing robot-assisted ventral hernia. Patients were propensity-score matched 1:1 with 100 patients undergoing open repairs on age, type of hernia (primary/incisional), and horizontal defect size. The primary outcome of the study was the total cost per procedure in Euros including the cost of a robotic approach, extra ports, mesh, tackers, length of stay, length of readmission, and operative reintervention. The cost of the robot itself was not included in the cost calculation.
RESULTS: The mean length of stay was 0.3 days for patients undergoing robot-assisted ventral hernia repair, which was significantly shorter compared with 2.1 days for patients undergoing open repair, P < 0.005. The readmission rate was 4% for patients undergoing robot-assisted ventral hernia repairs and was significantly lower compared with open repairs (17%), P = 0.006. The mean total cost of all robot-assisted ventral and incisional hernia repairs was 1,094 euro compared with 1,483 euro for open repairs, P = 0.123. The total cost of a robot-assisted incisional hernia repair was significantly lower (1,134 euros) compared with open ventral hernia repair (2,169 euros), P = 0.005.
CONCLUSIONS: In a Danish cohort of patients with incisional hernia, robot-assisted incisional hernia repair was more cost-effective than an open repair due to shortened length of stay, and lower rates of readmission and reintervention within 90 days.

OBJECTIVE: To develop and externally validate a prognostic model built on important factors predisposing multimorbid patients to all-cause readmission and/or death. In addition to identify patients who may benefit most from a comprehensive clinical pharmacist intervention.
METHODS: A multivariable prognostic model was developed based on data from a randomised controlled trial investigating the effect of pharmacist-led medicines management on readmission rate in multimorbid, hospitalised patients. The derivation set comprised 386 patients randomised in a 1:1 manner to the intervention group, i.e. with a pharmacist included in their multidisciplinary treatment team, or the control group receiving standard care at the ward. External validation of the model was performed using data from an independent cohort, in which 100 patients were randomised to the same intervention, or standard care. The setting was an internal medicines ward at a university hospital in Norway.
RESULTS: The number of patients who were readmitted or had died within 18 months after discharge was 297 (76.9 %) in the derivation set, i.e. the randomized controlled trial, and 69 (71.1 %) in the validation set, i.e. the independent cohort. Charlson comorbidity index (CCI; low, moderate or high), previous hospital admissions within the previous six months and heart failure were the strongest prognostic factors and were included in the final model. The efficacy of the pharmaceutical intervention did not prove significant in the model. A prognostic index (PI) was constructed to estimate the hazard of readmission or death (low, intermediate or high-risk groups). Overall, the external validation replicated the result. We were unable to identify a subgroup of the multimorbid patients with better efficacy of the intervention.
CONCLUSIONS: A prognostic model including CCI, previous admissions and heart failure can be used to obtain valid estimates of risk of readmission and death in patients with multimorbidity.