Postdischarge functional outcomes in older patients with acute heart failure in Japan: the Longevity Improvement & Fair Evidence study.

BACKGROUND: The association between care needs level (CNL) at hospitalisation and postdischarge outcomes in older patients with acute heart failure (aHF) has been insufficiently investigated. METHODS: This population-based cohort study was conducted using health insurance claims and CNL data of the Longevity Improvement & Fair Evidence study. Patients aged ≥65 years, discharged after hospitalisation for aHF between April 2014 and March 2022, were identified. CNLs at hospitalisation were classified as no care needs (NCN), support level (SL) and CNL1, CNL2-3 and CNL4-5 based on total estimated daily care time as defined by national standard criteria, and varied on an ordinal scale between SL&CNL1 (low level) to CNL4-5 (fully dependent). The primary outcomes were changes in CNL and death 1 year after discharge, assessed by CNL at hospitalisation using Cox proportional hazard models. RESULTS: Of the 17 724 patients included, 7540 (42.5%), 4818 (27.2%), 3267 (18.4%) and 2099 (11.8%) had NCN, SL&CNL1, CNL2-3 and CNL4-5, respectively, at hospitalisation. One year after discharge, 4808 (27.1%), 3243 (18.3%), 2968 (16.7%), 2505 (14.1%) and 4200 (23.7%) patients had NCN, SL&CNL1, CNL2-3, CNL4-5 and death, respectively. Almost all patients' CNLs worsened after discharge. Compared to patients with NCN at hospitalisation, patients with SL&CNL1, CNL2-3 and CNL4-5 had an increased risk of all-cause death 1 year after discharge (hazard ratio [95% confidence interval]: 1.19 [1.09-1.31], 1.88 [1.71-2.06] and 2.56 [2.31-2.84], respectively). CONCLUSIONS: Older patients with aHF and high CNL at hospitalisation had a high risk of all-cause mortality in the year following discharge.

Extensive ablation for persistent atrial fibrillation patients with mitral regurgitation: Insights from the EARNEST-PVI prospective randomized trial.

BACKGROUND: Extensive ablation in addition to pulmonary vein isolation (PVI) in patients with persistent atrial fibrillation (AF) has not yielded consistent results, indicating diversity in their efficacy. Mitral regurgitation (MR) associated with AF may indicate a higher prevalence of arrhythmogenic substrate, suggesting potential benefits of extensive ablation for these patients. METHODS: This post-hoc analysis of the EARNEST-PVI trial compared PVI alone versus an extensive ablation strategy (PVI-plus) in persistent AF patients, stratified by MR presence. The primary endpoint of the study was the recurrence of AF. The secondary endpoints included death, cerebral infarction, and procedure-related complications. RESULTS: The trial included 495 eligible patients divided into MR and non-MR groups. The MR group consisted of 192 patients (89 in the PVI-alone arm and 103 in the PVI-plus arm), while the non-MR group had 303 patients (158 in the PVI-alone arm and 145 in the PVI-plus arm). In the non-MR group, recurrence rates were similar between PVI-alone and PVI-plus arms (Log-rank P = 0.47, Hazard ratio = 0.85 [95%CI: 0.54-1.33], P = 0.472). However, in the MR group, PVI-plus was significantly more effective in preventing AF recurrence (Log-rank P = 0.0014, Hazard ratio = 0.40 [95%CI: 0.22-0.72], P = 0.0021). No significant differences were observed in secondary endpoints between the two arms. CONCLUSIONS: For persistent AF patients with mild or greater MR, receiving PVI-plus was superior to PVI-alone in preventing AF recurrence. Conversely, for patients without MR, the effectiveness of extensive ablation was not demonstrated. These findings suggest tailoring ablation strategies based on MR presence can lead to better outcomes in AF management.

Impact of left atrial appendage flow velocity on thrombus resolution and clinical outcomes in patients with atrial fibrillation and silent left atrial thrombi: insights from the LAT study.

AIMS: Blood stasis is crucial in developing left atrial (LA) thrombi. LA appendage peak flow velocity (LAAFV) is a quantitative parameter for estimating thromboembolic risk. However, its impact on LA thrombus resolution and clinical outcomes remains unclear. METHODS AND RESULTS: The LAT study was a multicentre observational study investigating patients with atrial fibrillation (AF) and silent LA thrombi detected by transoesophageal echocardiography (TEE). Among 17 436 TEE procedures for patients with AF, 297 patients (1.7%) had silent LA thrombi. Excluding patients without follow-up examinations, we enrolled 169 whose baseline LAAFV was available. Oral anticoagulation use increased from 85.7% at baseline to 97.0% at the final follow-up (P < 0.001). During 1 year, LA thrombus resolution was confirmed in 130 (76.9%) patients within 76 (34-138) days. Conversely, 26 had residual LA thrombi, 8 had thromboembolisms, and 5 required surgical removal. These patients with failed thrombus resolution had lower baseline LAAFV than those with successful resolution (18.0 [15.8-22.0] vs. 22.2 [17.0-35.0], P = 0.003). Despite limited predictive power (area under the curve, 0.659; P = 0.001), LAAFV ≤ 20.0 cm/s (best cut-off) significantly predicted failed LA thrombus resolution, even after adjusting for potential confounders (odds ratio, 2.72; 95% confidence interval, 1.22-6.09; P = 0.015). The incidence of adverse outcomes including ischaemic stroke/systemic embolism, major bleeding, or all-cause death was significantly higher in patients with reduced LAAFV than in those with preserved LAAFV (28.4% vs. 11.6%, log-rank P = 0.005). CONCLUSION: Failed LA thrombus resolution was not rare in patients with AF and silent LA thrombi. Reduced LAAFV was associated with failed LA thrombus resolution and adverse clinical outcomes.

Effect of olfactory stimulation from aromatherapy on the autonomic nervous activity during aerobic exercises.

Variations in the autonomic nervous system activity during exercise therapy in patients with cardiovascular diseases may lead to adverse events. Aromatherapy may reduce these adverse events by enhancing parasympathetic nervous activity (PNA). However, the effects of aromatherapy during exercise remain relatively unknown. This study aimed to evaluate the effect of aromatherapy on autonomic nervous activity during exercise and recovery. This randomized crossover study included 20 healthy men subjected to both aroma and placebo conditions which involved rest and moderate-intensity aerobic exercise on a cycle ergometer, followed by recovery. Blood pressure, heart rate variability indices, and SpO2 were measured during the rest, exercise, and recovery phases. Moreover, aroma preferences and emotional changes in response to the aroma were assessed. Under the placebo condition, high frequency (HF), root mean square of successive differences indices, and heart rate showed delayed recovery (P < 0.05). Furthermore, a moderate positive correlation was identified between aroma preference, pleasant emotions induced by aromatherapy, and the HF index (P < 0.05). These results indicate that aromatherapy facilitates the recovery of PNA after exercise. Furthermore, these effects were more pronounced among individuals who exhibited a stronger preference for and more positive emotions toward aromas.

Oversampling effect in pretraining for bidirectional encoder representations from transformers (BERT) to localize medical BERT and enhance biomedical BERT.

BACKGROUND: Pretraining large-scale neural language models on raw texts has made a significant contribution to improving transfer learning in natural language processing. With the introduction of transformer-based language models, such as bidirectional encoder representations from transformers (BERT), the performance of information extraction from free text has improved significantly in both the general and medical domains. However, it is difficult to train specific BERT models to perform well in domains for which few databases of a high quality and large size are publicly available. OBJECTIVE: We hypothesized that this problem could be addressed by oversampling a domain-specific corpus and using it for pretraining with a larger corpus in a balanced manner. In the present study, we verified our hypothesis by developing pretraining models using our method and evaluating their performance. METHODS: Our proposed method was based on the simultaneous pretraining of models with knowledge from distinct domains after oversampling. We conducted three experiments in which we generated (1) English biomedical BERT from a small biomedical corpus, (2) Japanese medical BERT from a small medical corpus, and (3) enhanced biomedical BERT pretrained with complete PubMed abstracts in a balanced manner. We then compared their performance with those of conventional models. RESULTS: Our English BERT pretrained using both general and small medical domain corpora performed sufficiently well for practical use on the biomedical language understanding evaluation (BLUE) benchmark. Moreover, our proposed method was more effective than the conventional methods for each biomedical corpus of the same corpus size in the general domain. Our Japanese medical BERT outperformed the other BERT models built using a conventional method for almost all the medical tasks. The model demonstrated the same trend as that of the first experiment in English. Further, our enhanced biomedical BERT model, which was not pretrained on clinical notes, achieved superior clinical and biomedical scores on the BLUE benchmark with an increase of 0.3 points in the clinical score and 0.5 points in the biomedical score. These scores were above those of the models trained without our proposed method. CONCLUSIONS: Well-balanced pretraining using oversampling instances derived from a corpus appropriate for the target task allowed us to construct a high-performance BERT model.

Uplift modeling to identify patients who require extensive catheter ablation procedures among patients with persistent atrial fibrillation.

Identifying patients who would benefit from extensive catheter ablation along with pulmonary vein isolation (PVI) among those with persistent atrial fibrillation (AF) has been a subject of controversy. The objective of this study was to apply uplift modeling, a machine learning method for analyzing individual causal effect, to identify such patients in the EARNEST-PVI trial, a randomized trial in patients with persistent AF. We developed 16 uplift models using different machine learning algorithms, and determined that the best performing model was adaptive boosting using Qini coefficients. The optimal uplift score threshold was 0.0124. Among patients with an uplift score ≥ 0.0124, those who underwent extensive catheter ablation (PVI-plus) showed a significantly lower recurrence rate of AF compared to those who received only PVI (PVI-alone) (HR 0.40; 95% CI 0.19-0.84; P-value = 0.015). In contrast, among patients with an uplift score < 0.0124, recurrence of AF did not significantly differ between PVI-plus and PVI-alone (HR 1.17; 95% CI 0.57-2.39; P-value = 0.661). By employing uplift modeling, we could effectively identify a subset of patients with persistent AF who would benefit from PVI-plus. This model could be valuable in stratifying patients with persistent AF who need extensive catheter ablation before the procedure.

Development of the Clinical Specimen Information Management System for Multicenter Clinical Studies.

Some multicenter clinical studies require the acquisition of clinical specimens from patients, and the centralized management and analysis of clinical specimens at a research institution. In such cases, it is necessary to manage clinical specimens with anonymized patient information. In addition, clinical specimens need to be managed in connection with clinical information in clinical studies. In this study, we have developed a clinical specimen information management system that works with electronic data capture system for efficient specimen information management and the system workflow has verified at Osaka University Hospital. In addition, by combining this system with medical image collection system that we have developed previously, the integrated management of clinical information, medical image, and clinical specimen information will become possible. This specimen information management system may be expected to provide the platform for integrated analysis utilizing clinical information, medical image, and data from clinical specimens in multicenter clinical studies.

Classification of Diagnostic Certainty in Radiology Reports with Deep Learning.

A radiology report is prepared for communicating clinical information about observed abnormal structures and clinically important findings with referring clinicians. However, such observations and findings are often accompanied by ambiguous expressions, which can prevent clinicians from accurately interpreting the content of reports. To systematically assess the degree of diagnostic certainty for each observation and finding in a report, we defined an ordinal scale comprising five classes: definite, likely, may represent, unlikely, and denial. Furthermore, we applied a deep learning classification model to determine its applicability to in-house radiology reports. We trained and evaluated the model using 540 in-house chest computed tomography reports. The deep learning model achieved a micro F1-score of 97.61%, which indicated that our ordinal scale was suitable for measuring the diagnostic certainty of observations and findings in a report.

Implementation of a Multilingual Electronic Medical Questionnaire: For Use Inside or Outside the Hospital.

We implemented a multilingual medical questionnaire system, which allows patients to answer questionnaires both in and out of the hospital. The response data are sent to and stored as structured data on the server in hospital information system, and could be converted to Japanese and quoted as part of progress notes in the electronic medical record.

The Prognostic Impact of In-Hospital Major Bleeding and Recurrence of Myocardial Infarction during Acute Phase after Percutaneous Coronary Intervention for Acute Myocardial Infarction.

AIM: Both recurrent myocardial infarction (ReMI) and bleeding events after acute myocardial infarction (AMI) were reportedly associated with increased mortality. To date, the prognostic impact of these events on subsequent outcomes in East Asians is still unclear. In this study, we aimed to investigate the impact of bleeding or thrombotic events during acute phase on subsequent mortality and time-dependent change of the impact in patients with AMI undergoing percutaneous coronary intervention (PCI). METHOD: We conducted a prospective, multicenter, observational study of patients with AMI (n=12,093). The patients who did not undergo emergent PCI were excluded. In addition, the patients registered before 2003 were excluded because the data of bleeding severity was not obtained. Eligible patients were divided into two groups based on the occurrence of major bleeding within 7 days of PCI, and the same approach was performed for ReMI within 7 days of PCI. The endpoint of this study was all-cause death. We assessed the impact of major bleeding and ReMI, which occurred within 7 days of index PCI, on the subsequent clinical outcomes up to 5 years. RESULTS: A total of 6,769 patients were found to be eligible. All-cause death occurred in 898 (13.3%) patients during a median follow-up period of 1,726 [511-1,840] days. After adjustment for multiple confounders, major bleeding in 7 days from index PCI was independently associated with higher 30-day and 30-day to 1-year mortality (odds ratio [OR]: 2.06 [1.45-2.92] p＜0.001, OR: 2.03 [1.28-3.15] p=0.002), whereas ReMI was not (OR: 1.93 [0.92-3.80] p=0.07, OR: 0.81 [0.24-2.03] p=0.68). Major bleeding and ReMI did not affect mortality between 1 and 5 years (hazard ratio [HR]: 1.32 [0.77-2.26] p=0.31, HR: 0.48 [0.12-1.94] p=0.30). CONCLUSION: Major bleeding in 7 days from admission was independently associated with higher 30-day and 1-year mortality but not during 1-5 years. ReMI did not affect mortality in all phases. We should be more concerned about bleeding event during acute phase after PCI.

Pathophysiological insights into machine learning-based subphenotypes of acute heart failure with preserved ejection fraction.

OBJECTIVE: The heterogeneous pathophysiology of the diverse heart failure with preserved ejection fraction (HFpEF) phenotypes needs to be examined. We aim to assess differences in the biomarkers among the phenotypes of HFpEF and investigate its multifactorial pathophysiology. METHODS: This study is a retrospective analysis of the PURSUIT-HFpEF Study (N=1231), an ongoing, prospective, multicentre observational study of acute decompensated HFpEF. In this registry, there is a predefined subcohort in which we perform multibiomarker tests (N=212). We applied the previously established machine learning-based clustering model to the subcohort with biomarker measurements to classify them into four phenotypes: phenotype 1 (n=69), phenotype 2 (n=49), phenotype 3 (n=41) and phenotype 4 (n=53). Biomarker characteristics in each phenotype were evaluated. RESULTS: Phenotype 1 presented the lowest value of N-terminal pro-brain natriuretic peptide (NT-proBNP), high-sensitive C reactive protein, tumour necrosis factor-α, growth differentiation factor (GDF)-15, troponin T and cystatin C, whereas phenotype 2, which is characterised by hypertension and cardiac hypertrophy, showed the highest value of these markers. Phenotype 3 showed the second highest value of GDF-15 and cystatin C. Phenotype 4 presented a low NT-proBNP value and a relatively high GDF-15. CONCLUSIONS: Distinctive characteristics of biomarkers in HFpEF phenotypes would indicate differential underlying mechanisms to be elucidated. The contribution of inflammation to the pathogenesis varied considerably among different HFpEF phenotypes. Systemic inflammation substantially contributes to the pathophysiology of the classic HFpEF phenotype with cardiac hypertrophy. TRIAL REGISTRATION NUMBER: UMIN-CTR ID: UMIN000021831.

Oral anticoagulation after atrial fibrillation catheter ablation: benefits and risks.

BACKGROUND AND AIMS: Few recent large-scale studies have evaluated the risks and benefits of continuing oral anticoagulant (OAC) therapy after catheter ablation (CA) for atrial fibrillation (AF). This study evaluated the status of continuation of OAC therapy and the association between continuation of OAC therapy and thromboembolic and bleeding events according to the CHADS2 score. METHODS: This retrospective study included data from the Japanese nationwide administrative claims database of patients who underwent CA for AF between April 2014 and March 2021. Patients without AF recurrence assessed by administrative data of the treatment modalities were divided into two groups according to continuation of OAC therapy 6 months after the index CA. The primary outcomes were thromboembolism and major bleeding after a landmark period of 6 months. After inverse probability of treatment weighting analysis, the association between OAC continuation and outcomes was determined according to the CHADS2 score. RESULTS: Among 231 374 patients included, 69.7%, 21.6%, and 8.7% had CHADS2 scores of ≤1, 2, and ≥3, respectively. Of these, 71% continued OAC therapy at 6 months. The OAC continuation rate was higher in the high CHADS2 score group than that in the low CHADS2 score group. Among all patients, 2451 patients (0.55 per 100 person-years) had thromboembolism and 2367 (0.53 per 100 person-years) had major bleeding. In the CHADS2 score ≤1 group, the hazard ratio of the continued OAC group was 0.86 [95% confidence interval (CI): 0.74-1.01, P = .06] for thromboembolism and was 1.51 (95% CI: 1.27-1.80, P < .001) for major bleeding. In the CHADS2 score ≥3 group, the hazard ratio of the continued OAC group was 0.61 (95% CI: 0.46-0.82, P = .001) for thromboembolism and was 1.05 (95% CI: 0.71-1.56, P = 0.81) for major bleeding. CONCLUSIONS: This observational study suggests that the benefits and risks of continuing OAC therapy after CA for AF differ based on the patient's CHADS2 score. The risk of major bleeding due to OAC continuation seems to outweigh the risk reduction of thromboembolism in patients with lower thromboembolic risk.

Extracting Clinical Information From Japanese Radiology Reports Using a 2-Stage Deep Learning Approach: Algorithm Development and Validation.

Background: Radiology reports are usually written in a free-text format, which makes it challenging to reuse the reports. Objective: For secondary use, we developed a 2-stage deep learning system for extracting clinical information and converting it into a structured format. Methods: Our system mainly consists of 2 deep learning modules: entity extraction and relation extraction. For each module, state-of-the-art deep learning models were applied. We trained and evaluated the models using 1040 in-house Japanese computed tomography (CT) reports annotated by medical experts. We also evaluated the performance of the entire pipeline of our system. In addition, the ratio of annotated entities in the reports was measured to validate the coverage of the clinical information with our information model. Results: The microaveraged F1-scores of our best-performing model for entity extraction and relation extraction were 96.1% and 97.4%, respectively. The microaveraged F1-score of the 2-stage system, which is a measure of the performance of the entire pipeline of our system, was 91.9%. Our system showed encouraging results for the conversion of free-text radiology reports into a structured format. The coverage of clinical information in the reports was 96.2% (6595/6853). Conclusions: Our 2-stage deep system can extract clinical information from chest and abdomen CT reports accurately and comprehensively.

ß-blockers may be detrimental in frail patients with heart failure with preserved ejection fraction.

BACKGROUND: The effectiveness of ß-blocker in patients with heart failure with preserved ejection fraction (HFpEF) remains to be determined. We aimed to clarify the association between the use of ß-blocker and prognosis according to the status of frailty. METHODS: We compared prognosis between HFpEF patients with and without ß-blockers stratified with the Clinical Frailty Scale (CFS), using data from the PURSUIT-HFpEF registry (UMIN000021831). RESULTS: Among 1159 patients enrolled in the analysis (median age, 81.4 years; male, 44.7%), 580 patients were CFS ≤ 3, while 579 were CFS ≥ 4. Use of ß-blockers was associated with a worse composite endpoint of all-cause death and heart failure readmission in patients with CFS ≥ 4 (adjusted hazard ratio (HR) 1.43, 95% CI 1.10-1.85, p = 0.007), but was not significantly associated with this endpoint in those with CFS ≤ 3 (adjusted HR 0.95, 95% CI 0.71-1.26, p = 0.719) in multivariable Cox proportional hazard models. These results were confirmed in a propensity-matched analysis (HR in those with CFS ≥ 4: 1.42, 95% CI 1.05-1.90, p = 0.020; that in those with CFS ≤ 3: 0.83, 95% CI 0.60-1.14, p = 0.249), and in an analysis in which patients were divided into CFS ≤ 4 and CFS ≥ 5. CONCLUSIONS: Use of ß-blockers was significantly associated with worse prognosis specifically in patients with HFpEF and high CFS, but not in those with low CFS. Use of ß-blockers in HFpEF patients with frailty may need careful attention.

The efficacy and safety of adaptive servo-ventilation therapy for heart failure with preserved ejection fraction.

It is unclear whether adaptive servo-ventilation (ASV) therapy for heart failure with preserved ejection fraction (HFpEF) is effective. The aim of this study was to investigate the details of ASV use, and to evaluate the effectiveness and safety of ASV in real-world HFpEF patients. We retrospectively enrolled 36 HFpEF patients at nine cardiovascular centers who initiated ASV therapy during hospitalization or on outpatient basis and were able to continue using it at home from 2012 to 2017 and survived for at least one year thereafter. The number of hospitalizations for heart failure (HF) during the 12 months before and 12 months after introduction of ASV at home was compared. The median number of HF hospitalizations for each patient was significantly reduced from 1 [interquartile range: 1-2] in the 12 months before introduction of ASV to 0 [0-0] in the 12 months after introduction of ASV (p < 0.001). In subgroup analysis, reduction in heart failure hospitalization was significantly greater in female patients, patients with a body mass index < 25, and those with moderate or severe tricuspid valve regurgitation. In patients with HFpEF, the number of HF hospitalizations was significantly decreased after the introduction of ASV. HFpEF patients with female sex, BMI < 25, or moderate to severe tricuspid valve regurgitation are potential candidates who might benefit from ASV therapy.

Impact of an Electronic Medical Record-Connected Questionnaire on Efficient Nursing Documentation: Usability and Efficacy Study.

BACKGROUND: Documentation tasks comprise a large percentage of nurses' workloads. Nursing records were partially based on a report from the patient. However, it is not a verbatim transcription of the patient's complaints but a type of medical record. Therefore, to reduce the time spent on nursing documentation, it is necessary to assist in the appropriate conversion or citation of patient reports to professional records. However, few studies have been conducted on systems for capturing patient reports in electronic medical records. In addition, there have been no reports on whether such a system reduces the time spent on nursing documentation. OBJECTIVE: This study aims to develop a patient self-reporting system that appropriately converts data to nursing records and evaluate its effect on reducing the documenting burden for nurses. METHODS: An electronic medical record-connected questionnaire and a preadmission nursing questionnaire were administered. The questionnaire responses entered by the patients were quoted in the patient profile for inpatient assessment in the nursing system. To clarify its efficacy, this study examined whether the use of the electronic questionnaire system saved the nurses' time entering the patient profile admitted between August and December 2022. It also surveyed the usability of the electronic questionnaire between April and December 2022. RESULTS: A total of 3111 (78%) patients reported that they answered the electronic medical questionnaire by themselves. Of them, 2715 (88%) felt it was easy to use and 2604 (85%) were willing to use it again. The electronic questionnaire was used in 1326 of 2425 admission cases (use group). The input time for the patient profile was significantly shorter in the use group than in the no-use group (P<.001). Stratified analyses showed that in the internal medicine wards and in patients with dependent activities of daily living, nurses took 13%-18% (1.3 to 2 minutes) less time to enter patient profiles within the use group (both P<.001), even though there was no difference in the amount of information. By contrast, in the surgical wards and in the patients with independent activities of daily living, there was no difference in the time to entry (P=.50 and P=.20, respectively), but there was a greater amount of information in the use group. CONCLUSIONS: The study developed and implemented a system in which self-reported patient data were captured in the hospital information network and quoted in the nursing system. This system contributes to improving the efficiency of nurses' task recordings.

P2Y12 inhibitor monotherapy after complex percutaneous coronary intervention: a systematic review and meta-analysis of randomized clinical trials.

It remains unknown whether the recent trend of short dual antiplatelet therapy (DAPT) followed by P2Y12 inhibitor monotherapy can simply be applied to patients undergoing complex percutaneous coronary intervention (PCI). We performed a systematic review and meta-analysis to evaluate P2Y12 inhibitor monotherapy vs. conventional DAPT in patients undergoing complex PCI and non-complex PCI (PROSPERO: CRD42022335723). Primary endpoint was the 1-year Net Adverse Clinical Event (NACE). Among 5,323 screened studies, six randomized trials fulfilled the eligibility criteria. A total of 10,588 complex PCI patients (5,269 vs. 5,319 patients) and 25,618 non-complex PCI patients (12,820 vs 12,798 patients) were randomly assigned to P2Y12 inhibitor monotherapy vs. conventional DAPT. In complex PCI patients, P2Y12 inhibitor monotherapy was associated with a lower risk of NACE than conventional DAPT [Odds ratio (OR) 0.76, 95% confidence interval (CI) 0.63-0.91, P = 0.003], whereas in non-complex PCI patients, P2Y12 inhibitor monotherapy was associated with a trend toward lowering the risk of NACE (OR 0.86, 95% CI 0.72-1.02, P = 0.09). This meta-analysis across randomized trials demonstrated that a strategy of short DAPT followed by P2Y12 inhibitor monotherapy reduces the risk of 1-year NACE in patients undergoing complex PCI.

Sodium-glucose cotransporter 2 inhibitor use in early-phase acute coronary syndrome with severe heart failure.

AIMS: Sodium-glucose cotransporter 2 inhibitor (SGLT2i) improves clinical outcomes in patients with heart failure (HF), but has limited evidence of SGLT2i use in early-phase acute coronary syndrome (ACS). We determined association of early SGLT2i use compared with either non-SGLT2i or dipeptidyl peptidase 4 inhibitor (DPP4i) use in hospitalized patients with ACS. METHODS AND RESULTS: This retrospective cohort study that used the Japanese nationwide administrative claims database included patients hospitalized with ACS aged ≥20 years between April 2014 and March 2021. The primary outcome was a composite of all-cause mortality or HF/ACS rehospitalization. Using 1:1 propensity score matching, the association with outcomes of the early SGLT2i use (≤14 days after admission) compared with non-SGLT2i or DPP4i use was determined according to the HF treatment. Among 388 185 patients included 115 612 and 272 573 with and without severe HF, respectively. Compared to non-SGLT2i users, the SGLT2i users had a lower hazard ratio (HR) with the primary outcome [HR: 0.83, 95% confidence interval (CI): 0.76-0.91; P < 0.001] in the severe HF group; however, there was no significant difference in the non-severe HF group (HR: 0.92, 95% CI: 0.82-1.03; P = 0.16). SGLT2i use showed a lower risk of the outcome in patients with severe HF and diabetes compared with DPP4i use (HR: 0.83, 95% CI: 0.69-1.00; P = 0.049). CONCLUSION: SGLT2i use in patients with early-phase ACS showed a lower risk of primary outcome in patients with severe HF, but the effect was not apparent in patients without severe HF.

Medications for specific phenotypes of heart failure with preserved ejection fraction classified by a machine learning-based clustering model.

OBJECTIVE: Our previously established machine learning-based clustering model classified heart failure with preserved ejection fraction (HFpEF) into four distinct phenotypes. Given the heterogeneous pathophysiology of HFpEF, specific medications may have favourable effects in specific phenotypes of HFpEF. We aimed to assess effectiveness of medications on clinical outcomes of the four phenotypes using a real-world HFpEF registry dataset. METHODS: This study is a posthoc analysis of the PURSUIT-HFpEF registry, a prospective, multicentre, observational study. We evaluated the clinical effectiveness of the following four types of postdischarge medication in the four different phenotypes: angiotensin-converting enzyme inhibitors (ACEi) or angiotensin-receptor blockers (ARB), beta blockers, mineralocorticoid-receptor antagonists (MRA) and statins. The primary endpoint of this study was a composite of all-cause death and heart failure hospitalisation. RESULTS: Of 1231 patients, 1100 (83 (IQR 77, 87) years, 604 females) were eligible for analysis. Median follow-up duration was 734 (398, 1108) days. The primary endpoint occurred in 528 patients (48.0%). Cox proportional hazard models with inverse-probability-of-treatment weighting showed the following significant effectiveness of medication on the primary endpoint: MRA for phenotype 2 (weighted HR (wHR) 0.40, 95% CI 0.21 to 0.75, p=0.005); ACEi or ARB for phenotype 3 (wHR 0.66 0.48 to 0.92, p=0.014) and statin therapy for phenotype 3 (wHR 0.43 (0.21 to 0.88), p=0.020). No other medications had significant treatment effects in the four phenotypes. CONCLUSIONS: Machine learning-based clustering may have the potential to identify populations in which specific medications may be effective. This study suggests the effectiveness of MRA, ACEi or ARB and statin for specific phenotypes of HFpEF. TRIAL REGISTRATION NUMBER: UMIN000021831.