Cheungpasitporn, Wisit

Background: The goal of this study was to categorize patients with abnormal serum phosphate upon hospital admission into distinct clusters utilizing an unsupervised machine learning approach, and to assess the mortality risk associated with these clusters. Methods: We utilized the consensus clustering approach on demographic information, comorbidities, principal diagnoses, and laboratory data of hypophosphatemia (serum phosphate ≤ 2.4 mg/dL) and hyperphosphatemia cohorts (serum phosphate ≥ 4.6 mg/dL). The standardized mean difference was applied to determine each cluster’s key features. We assessed the association of the clusters with mortality. Results: In the hypophosphatemia cohort (n = 3113), the consensus cluster analysis identified two clusters. The key features of patients in Cluster 2, compared with Cluster 1, included: older age; a higher comorbidity burden, particularly hypertension; diabetes mellitus; coronary artery disease; lower eGFR; and more acute kidney injury (AKI) at admission. Cluster 2 had a comparable hospital mortality (3.7% vs. 2.9%; p = 0.17), but a higher one-year mortality (26.8% vs. 14.0%; p < 0.001), and five-year mortality (20.2% vs. 44.3%; p < 0.001), compared to Cluster 1. In the hyperphosphatemia cohort (n = 7252), the analysis identified two clusters. The key features of patients in Cluster 2, compared with Cluster 1, included: older age; more primary admission for kidney disease; more history of hypertension; more end-stage kidney disease; more AKI at admission; and higher admission potassium, magnesium, and phosphate. Cluster 2 had a higher hospital (8.9% vs. 2.4%; p < 0.001) one-year mortality (32.9% vs. 14.8%; p < 0.001), and five-year mortality (24.5% vs. 51.1%; p < 0.001), compared with Cluster 1. Conclusion: Our cluster analysis classified clinically distinct phenotypes with different mortality risks among hospitalized patients with serum phosphate derangements. Age, comorbidities, and kidney function were the key features that differentiated the phenotypes.

Summary Background There are limited data on the influence of seasons on the outcomes of acute myocardial infarction-cardiac arrest (AMI-CA). Aim To evaluate the outcomes of AMI-CA by seasons in the United States Design Retrospective cohort study Methods Using the National Inpatient Sample from 2000 to 2017, adult (&gt;18 years) admissions with AMI-CA were identified. Seasons were defined by the month of admission as spring, summer, fall and winter. The outcomes of interest were prevalence of AMI-CA, in-hospital mortality, use of coronary angiography, percutaneous coronary intervention (PCI), hospital length of stay, hospitalization costs and discharge disposition. Results Of the 10 880 856 AMI admissions, 546 334 (5.0%) were complicated by CA, with a higher prevalence in fall and winter (5.1% each) compared to summer (5.0%) and spring (4.9%). Baseline characteristics of AMI-CA admissions admitted in various seasons were largely similar. Compared to AMI-CA admissions in spring, summer and fall, AMI-CA admissions in winter had slightly lower rates of coronary angiography (63.3–64.3% vs. 61.4%) and PCI (47.2–48.4% vs. 45.6%). Compared to those admitted in the spring, adjusted in-hospital mortality was higher for winter {46.8% vs. 44.2%; odds ratio (OR) 1.08 [95% confidence interval (CI) 1.06–1.10]; P &lt; 0.001}, lower for summer [43% vs. 44.2%; OR 0.97 (95% CI 0.95–0.98); P &lt; 0.001] and comparable for fall [44.4% vs. 44.2%; OR 1.01 (95% CI 0.99–1.03); P = 0.31] AMI-CA admissions. Length of hospital stay, total hospitalization charges and discharge dispositions for AMI-CA admissions were comparable across the seasons. Conclusions AMI-CA admissions in the winter were associated with lower rates of coronary angiography and PCI, and higher rates of in-hospital mortality compared to the other seasons.

Background: Sleep apnea is one of the most common conditions around the world. This disorder can significantly impact cardiovascular morbidity and mortality. Atrial overdrive pacing (AOP) is a treatment modality that can potentially decrease respiratory events. There is currently a lack of evidence to confirm the benefits of AOP. We aimed to assess the impact of AOP in patients with obstructive sleep apnea (OSA), central sleep apnea (CSA), and mixed type. Methods: A literature search for studies that reported the impact on apnea–hypopnea index (AHI) by cardiac implantable electronic devices with different pacing modes was conducted using MEDLINE, Embase, and Cochrane Database from inception through July 2020. Pooled standard mean difference with 95%CI was calculated using a random-effects model. Results: Fifteen studies, including thirteen randomized studies and two observational studies containing 440 patients, were identified. The standard mean difference in apnea–hypopnea index of atrial overdrive pacing demonstrated less duration of apnea/hypopnea in patients with atrial overdrive pacing (AOP) (SMD −0.29, 95%CI: −0.48, −0.10, I2 = 57%). Additional analysis was performed to assess the effect of atrial overdrive pacing in patients with or without severe sleep apnea syndrome (mean AHI < 30 defined as non-severe). There was no statistically significant difference in standardized mean in AHI in both subgroups between AOP and control groups (SMD −0.25, severe sleep apnea syndrome SMD −0.03, I2 = 0.00%). Conclusions: AOP was associated with a statistically significant reduction in AHI, but the magnitude of reduction was small. AOP may potentially be used as an adjunctive treatment with other modalities in treating patients with sleep apnea.

Abstract BACKGROUND: Rituximab (RTX) has been previously reported as directed treatment in patients with connective-tissue disease-related interstitial lung diseases (CTD-ILD). A systematic assessment of treatment effect size on pulmonary function outcomes and related adverse effects in patients with CTD-ILD has not been previously reported.METHODS: We performed a systematic review and meta-analysis of published reports from PubMed, Embase, and Cochrane Libraries. Randomized and non-randomized controlled trials, case-control, cohort, and case series (with five or more cases) containing individual pulmonary function data and adverse effects were included. Study endpoints were pre and post treatment change in percent predicted forced vital capacity (FVC %) and diffusion capacity for carbon monoxide (DLCO%), along with reported drug-related adverse events. RESULTS: Twenty studies totaling 411 patients were identified with 14 included in the meta-analysis of pulmonary function and six in the descriptive review. Random effects meta-analysis of pre and post-treatment pulmonary function findings demonstrated increases in FVC% (n =296) (mean difference (MD) 4.57%, [95% CI 2.63-6.51]) and DLCO% (n = 246) (MD 5.0% [95% CI 2.71-7.29]) after RTX treatment. RTX treatment-related adverse effects were reported in 13.6% of the pooled cohort. CONCLUSIONS: A systematic assessment of post-treatment effect size suggests a potential role for RTX in stabilizing or improving lung function in patients with CTD-ILD, with a modest but not insignificant adverse effect profile.

Background The presence of atrial fibrillation (AF) in patients with heart failure with preserved ejection fraction (HFpEF) dramatically increases higher morbidity and mortality. Recent studies have suggested that early rhythm control may alleviate the burden of poor outcomes. Currently, there remain limited data on whether rhythm or rate control has better efficacy. This study sought to compare both strategies in HFpEF patients with AF. Methods Databases were searched throughout 2020. Studies that reported cardiovascular outcomes amongst HFpEF patients with AF who received either rhythm or rate control were included. Estimates of the effects from the individual studies were extracted and combined using random-effects, a generic inverse variance method of DerSimonian and Laird. Results Five observational studies were included in the analysis, consisting of 16,953 patients, 13.8% of whom were receiving rhythm control. In comparison with rate control, rhythm control was associated with decreased overall mortality rates (pooled RR 0.85, 95% CI 0.75–0.95, with I2 = 0%, p value = 0.009). Conclusions In HFpEF patients with AF, rhythm control was associated with lower mortality, compared to rate control. Further studies are warranted to validate our observation.

Background and Objectives: Contemporary data on the prevalence, management and outcomes of acute myocardial infarction (AMI) in relation to body mass index (BMI) are limited. Materials and Methods: Using the National Inpatient Sample from 2008 through 2017, we identified adult AMI hospitalizations and categorized them into underweight (BMI < 19.9 kg/m2), normal BMI and overweight/obese (BMI > 24.9 kg/m2) groups. We evaluated in-hospital mortality, utilization of cardiac procedures and resource utilization among these groups. Results: Among 6,089,979 admissions for AMI, 38,070 (0.6%) were underweight, 5,094,721 (83.7%) had normal BMI, and 957,188 (15.7%) were overweight or obese. Over the study period, an increase in the prevalence of AMI was observed in underweight and overweight/obese admissions. Underweight AMI admissions were, on average, older, with higher comorbidity, whereas overweight/obese admissions were younger and had lower comorbidity. In comparison to the normal BMI and overweight/obese categories, significantly lower use of coronary angiography (62.3% vs. 74.6% vs. 37.9%) and PCI (40.8% vs. 47.7% vs. 19.6%) was observed in underweight admissions (all p < 0.001). The underweight category was associated with significantly higher in-hospital mortality (10.0% vs. 5.5%; OR 1.23 (95% CI 1.18–1.27), p < 0.001), whereas being overweight/obese was associated with significantly lower in-hospital mortality compared to normal BMI admissions (3.1% vs. 5.5%; OR 0.73 (95% CI 0.72–0.74), p < 0.001). Underweight AMI admissions had longer lengths of in-hospital stay with frequent discharges to skilled nursing facilities, while overweight/obese admissions had higher hospitalization costs. Conclusions: In-hospital management and outcomes of AMI vary by BMI. Underweight status was associated with worse outcomes, whereas the obesity paradox was apparent, with better outcomes for overweight/obese admissions.

Background and Objectives: Despite the association between hyperchloremia and adverse outcomes, mortality risks among patients with hyperchloremia have not consistently been observed among all studies with different patient populations with hyperchloremia. The objective of this study was to characterize hyperchloremic patients at hospital admission into clusters using an unsupervised machine learning approach and to evaluate the mortality risk among these distinct clusters. Materials and Methods: We performed consensus cluster analysis based on demographic information, principal diagnoses, comorbidities, and laboratory data among 11,394 hospitalized adult patients with admission serum chloride of >108 mEq/L. We calculated the standardized mean difference of each variable to identify each cluster’s key features. We assessed the association of each hyperchloremia cluster with hospital and one-year mortality. Results: There were three distinct clusters of patients with admission hyperchloremia: 3237 (28%), 4059 (36%), and 4098 (36%) patients in clusters 1 through 3, respectively. Cluster 1 was characterized by higher serum chloride but lower serum sodium, bicarbonate, hemoglobin, and albumin. Cluster 2 was characterized by younger age, lower comorbidity score, lower serum chloride, and higher estimated glomerular filtration (eGFR), hemoglobin, and albumin. Cluster 3 was characterized by older age, higher comorbidity score, higher serum sodium, potassium, and lower eGFR. Compared with cluster 2, odds ratios for hospital mortality were 3.60 (95% CI 2.33–5.56) for cluster 1, and 4.83 (95% CI 3.21–7.28) for cluster 3, whereas hazard ratios for one-year mortality were 4.49 (95% CI 3.53–5.70) for cluster 1 and 6.96 (95% CI 5.56–8.72) for cluster 3. Conclusions: Our cluster analysis identified three clinically distinct phenotypes with differing mortality risks in hospitalized patients with admission hyperchloremia.

Background: The objective of this study was to characterize patients with hyponatremia at hospital admission into clusters using an unsupervised machine learning approach, and to evaluate the short- and long-term mortality risk among these distinct clusters. Methods: We performed consensus cluster analysis based on demographic information, principal diagnoses, comorbidities, and laboratory data among 11,099 hospitalized adult hyponatremia patients with an admission serum sodium below 135 mEq/L. The standardized mean difference was utilized to identify each cluster’s key features. We assessed the association of each hyponatremia cluster with hospital and one-year mortality using logistic and Cox proportional hazard analysis, respectively. Results: There were three distinct clusters of hyponatremia patients: 2033 (18%) in cluster 1, 3064 (28%) in cluster 2, and 6002 (54%) in cluster 3. Among these three distinct clusters, clusters 3 patients were the youngest, had lowest comorbidity burden, and highest kidney function. Cluster 1 patients were more likely to be admitted for genitourinary disease, and have diabetes and end-stage kidney disease. Cluster 1 patients had the lowest kidney function, serum bicarbonate, and hemoglobin, but highest serum potassium and prevalence of acute kidney injury. In contrast, cluster 2 patients were the oldest and were more likely to be admitted for respiratory disease, have coronary artery disease, congestive heart failure, stroke, and chronic obstructive pulmonary disease. Cluster 2 patients had lowest serum sodium and serum chloride, but highest serum bicarbonate. Cluster 1 patients had the highest hospital mortality and one-year mortality, followed by cluster 2 and cluster 3, respectively. Conclusion: We identified three clinically distinct phenotypes with differing mortality risks in a heterogeneous cohort of hospitalized hyponatremic patients using an unsupervised machine learning approach.

Acute myocardial infarction with cardiogenic shock (AMI-CS) is associated with high mortality and morbidity despite advancements in cardiovascular care. AMI-CS is associated with multiorgan failure of non-cardiac organ systems. Acute kidney injury (AKI) is frequently seen in patients with AMI-CS and is associated with worse mortality and outcomes compared to those without. The pathogenesis of AMI-CS associated with AKI may involve more factors than previously understood. Early use of renal replacement therapies, management of comorbid conditions and judicious fluid administration may help improve outcomes. In this review, we seek to address the etiology, pathophysiology, management, and outcomes of AKI complicating AMI-CS.