Palliative care consultation (PCC) in acute decompensated heart failure (ADHF) may enhance care quality and align treatment with patient goals. However, national trends and predictors of PCC in ADHF remain poorly defined. We used the National Inpatient Sample (2018–2020) to identify hospitalizations for adults (≥18 years) with a primary diagnosis of ADHF using ICD-10-CM codes. PCC was defined by ICD-10-CM code Z51.5. Multivariable survey-weighted logistic regression identified predictors of PCC use, adjusting for demographics, socioeconomic status, comorbidities, and hospital factors. Among 3,655,265 hospitalizations, older age was associated with higher odds of PCC (aOR 1.05 per year; 95 % CI, 1.05–1.05). Compared to White individuals, odds of PCC were lower for Asian or Pacific Islander (aOR 0.74), Black (aOR 0.83), and Hispanic individuals (aOR 0.76). Medicare patients had lower odds than those with Medicaid (aOR 0.72). The highest income quartile was associated with greater PCC use (aOR 1.18). PCC was less common in the Northeast (aOR 0.88), South (aOR 0.93), and West (aOR 0.91) compared to the Midwest. Urban teaching hospitals had higher PCC rates than rural hospitals (aOR 1.48). Patients with greater comorbidity and higher mortality risk were more likely to receive PCC. PCC use in ADHF is influenced by demographic, socioeconomic, clinical, and institutional factors. Racial, regional, and hospital-level disparities suggest a need for interventions to promote equitable access to palliative care for patients with ADHF.

Background: Sepsis-associated respiratory disease, often linked to conditions like pneumonia and acute respiratory distress syndrome (ARDS), is a major contributor to mortality in the United States. Despite its significant impact, national trends and demographic disparities in sepsis-related respiratory deaths, particularly with the influence of the COVID-19 pandemic, remain underexplored. Study Design and Methods: This retrospective cohort study analyzed CDC WONDER mortality data (1999-2023) for adults aged ≥24 years with death records listing both respiratory disease (ICD-10: J00–J98) and sepsis (ICD-10: A02.1, A22.7, A26.7, A32.7, A40.0–A41.9, A42.7, B37.7) as causes. Age-adjusted mortality rates (AAMRs) per 100,000 were calculated using the 2000 U.S. standard population. Joinpoint regression estimated annual percent changes (APCs) and average annual percent changes (AAPCs) to identify temporal trends, stratified by sex, race/ethnicity, age, region, state, and place of death. Results: Of 2,090,242 combined respiratory and sepsis deaths, 51.49% were male. AAMRs increased from 29.83 in 1999 to 41.12 in 2023 (AAPC=1.69%, 95% CI: 0.30-3.10; P = .017), with a rise from 1999–2018 (APC=1.86%), a surge from 2018–2021 (APC=11.47%), and a decline from 2021–2023 (APC=-12.82%). Males, American Indian or Alaska Native populations, middle-aged adults (45-64 years), and Western/Southern states showed the largest increases. Most deaths (88.16%) occurred in medical facilities. Conclusion: Sepsis-associated respiratory mortality rose over 25 years, with a pronounced COVID-19-driven surge (2018-2021) and partial post-2021 decline. Persistent disparities by sex, race, age, and region highlight the need for targeted interventions, improved screening, and equity-focused policies to address systemic vulnerabilities.

Background/Objectives: Right heart catheterization (RHC) is the diagnostic gold standard for pulmonary hypertension (PH), defined as mean pulmonary arterial pressure (mPAP) greater than 20 mmHg at rest. It is invasive and carries procedural risk. Machine learning (ML) and deep learning (DL) applied to non-invasive modalities may provide a non-invasive adjunct for screening, triage, and earlier identification. Methods: Methodological quality was assessed using QUADAS-2. Primary non-comparative pooling was restricted to RHC-confirmed studies using Reitsma hierarchical bivariate random-effects models. Comparative studies were analyzed using a paired hierarchical bivariate model, with between-method differences assessed using paired Wald tests. Sensitivity, specificity, likelihood ratios, and diagnostic odds ratios were estimated; predictive values were evaluated as secondary outcomes. GRADE certainty was assessed separately for non-comparative ML/DL, comparative ML/DL, and traditional methods. Results: Nine studies involving multiple pulmonary hypertension subtypes met the inclusion criteria: five non-comparative (single-arm) studies including approximately 26,530 participants and four comparative (double-arm) studies including 330 paired participants per arm. In the primary synthesis restricted to RHC-confirmed single-arm studies, ML/DL models achieved a pooled sensitivity of 0.720 (95% CI: 0.647–0.783) and specificity of 0.883 (95% CI: 0.796–0.936), with a diagnostic odds ratio of 19.4 (95% CI: 13.6–27.7). Estimates were similar when all five single-arm studies were included (sensitivity 0.716, 95% CI: 0.654–0.771; specificity 0.891, 95% CI: 0.820–0.937). In comparative studies analyzed with a paired hierarchical bivariate model, ML/DL outperformed traditional methods for both sensitivity (0.838, 95% CI: 0.668–0.930 versus 0.707, 95% CI: 0.421–0.889; paired Wald p = 0.019) and specificity (0.849, 95% CI: 0.512–0.968 versus 0.640, 95% CI: 0.376–0.840; paired Wald p = 0.0076). At a 25% pre-test probability, ML/DL was projected to yield 34 additional true positives (95% CI: −30 to 109) and 142 fewer false positives (95% CI: −381 to 129) per 1000 patients tested, although all absolute difference intervals crossed zero. Certainty of evidence was very low across all outcomes. GRADE certainty ranged from low to very low depending on outcome and stratum. Conclusions: ML/DL-based methods showed promising non-invasive diagnostic accuracy for PH, with significantly higher pooled sensitivity and specificity than traditional methods in paired comparisons. However, evidence certainty ranged from low to very low, and projected absolute benefits remained imprecise. These findings are hypothesis-generating; ML/DL tools may serve as adjuncts in the diagnostic pathway but cannot replace RHC at this stage.