Muthyala, Anjani

Systemic sclerosis-associated pulmonary arterial hypertension (SSc-PAH) is a life-threatening vascular complication of SSc, marked by high morbidity and mortality. Early diagnosis remains a major challenge due to nonspecific symptoms and the limitations of conventional tools such as echocardiography (ECHO), pulmonary function tests (PFTs), and serum biomarkers. This review evaluates the emerging role of artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), in improving the diagnostic landscape of SSc-PAH. A comprehensive literature search was conducted across PubMed, Scopus, IEEE Xplore, Embase and Google Scholar to identify studies involving AI applications in SSc, pulmonary arterial hypertension (PAH), and their intersection. Evidence indicates that AI models can assist interpretation across modalities, including heart sounds, ECGs, chest X-rays (CXRs), ECHOs, CT pulmonary angiography (CTPA), and omics-based biomarkers. While several models show encouraging diagnostic performance, their accuracy varies by dataset and modality, and most require external validation against right heart catheterization (RHC)-confirmed cohorts. Integrating multimodal data through AI frameworks may enhance early recognition and individualized risk stratification; however, these tools remain exploratory. Future work should emphasize harmonized hemodynamic definitions, transparent validation protocols, and SSc-specific datasets to ensure clinical applicability and reproducibility.

Heart failure, a significant global health burden, is divided into heart failure with reduced ejection fraction (HFrEF) and preserved ejection fraction (HFpEF), characterized by systolic dysfunction and diastolic stiffness, respectively. While HFrEF benefits from pharmacological and device-based therapies, HFpEF lacks effective treatments, with both conditions leading to high rehospitalization rates and reduced quality of life, especially in older adults with comorbidities. This review explores the role of artificial intelligence (AI) in advancing autonomic neuromodulation for heart failure management. AI enhances patient selection, optimizes stimulation strategies, and enables adaptive, closed-loop systems. In HFrEF, vagus nerve stimulation and baroreflex activation therapy improve functional status and biomarkers, while AI-driven models adjust stimulation dynamically based on physiological feedback. In HFpEF, AI aids in deep phenotyping to identify responsive subgroups for neuromodulatory interventions. Clinical tools support remote monitoring, risk assessment, and symptom detection. However, challenges like data integration, ethical oversight, and clinical adoption limit real-world application. Algorithm transparency, bias minimization, and equitable access are critical for success. Interdisciplinary collaboration and ethical innovation are essential to develop personalized, data-driven, patient-centered heart failure treatment strategies through AI-guided neuromodulation.

Abstract Phonocardiogram (PCG) signals are electrical recording of heart sounds containing vital information of diagnostic importance. Several signal processing methods exist to characterize PCG, however suffers in terms of sensitivity and specificity in accurately discriminating normal and abnormal heart sounds. Recently, a multiscale frequency (MSF) analysis of normal PCG was reported to characterize subtle frequency content changes in PCG which can aid in differentiating normal and abnormal heart sounds. In this work, it was hypothesized that MSF can discriminate normal PCG signal compared to an artifact, PCG with extra systolic heart sounds and murmur based on their varying frequency content. Various samples of PCG with normal and abnormal heart sounds were obtained from Peter Bentley Heart Sounds Database sampled at 44.1 kHz for analysis. The signal was filtered using a 4th order Butterworth lowpass filter with cutoff frequency at 200 Hz to remove higher frequency noise and MSF estimation was performed on the filtered dataset using custom MATLAB software. Mann-Whitney test was performed for statistical significance at p < 0.05. Results indicate that MSF successfully discriminated normal and abnormal heart sounds, which can aid in PCG classification with more sophisticated analysis. Validation of this technique with larger dataset is required.

AbstractBackgroundWe compared the utility of existing and modified versions of high‐resolution manometry for diagnosing defecatory disorders (DD).MethodsIn 64 healthy and 136 constipated women, we compared left lateral (LL) and seated manometry, and analyzed with existing (ManoView™) and new methods, for discriminating between constipated patients with normal and prolonged rectal balloon expulsion time (BET). In both positions, the rectoanal gradient (RAG) and, for the new analysis, the pressure topography pattern during evacuation were used to discriminate between constipated patients without and with DD.Key ResultsThe BET was prolonged, suggestive of a DD, in 52 patients (38%). During evacuation, rectoanal pressures and the RAG were greater in the seated than the LL position (P≤.001). The new analysis identified 4 rectoanal pressure patterns. In the seated position, the BET was associated with the pattern (P=.0001), being prolonged in, respectively, 45%, 15%, 53%, and 0% of patients with minimal change, anal relaxation, paradoxical contraction, and transmission. Within each pattern, the RAG was greater (ie, less negative, P<.0001) in patients with a normal than a prolonged BET. Compared to the ManoView™ RAG in the LL position, the integrated analysis (ie, pattern and new RAG) in the LL position (P<.01) and the seated ManoView™ gradient (P=.02) were more effective for discriminating between constipated patients without and with DD.Conclusions & InferencesAnorectal HRM ideally should be performed in the more physiological seated position and analyzed by a two‐tier approach, which incorporates the overall pattern followed by the rectoanal gradient. These findings reinforce the utility of manometry for diagnosing DD.

AbstractAimsSome patients with upper gastrointestinal symptoms have rapid gastric emptying (GE). We aimed to compare patients with normal and rapid GE and to identify phenotypes among patients with rapid GE.MethodsAmong 2798 patients who underwent GE scintigraphy, we compared patients with normal and rapid GE and separately, patients with rapid GE at 1 hour (GE1), 2 hours (GE2), or both (GE12).ResultsIn 2798 patients, GE was normal (74%), delayed (18%), or rapid (8%). Among 211 patients with rapid GE, patterns were rapid GE1 (48%), 2 hours (17%), or 1 and 2 hours (35%); 42 (20%) had diseases that explain rapid GE. A combination of upper and lower gastrointestinal symptoms (54%) was more common that isolated upper (17%) or lower (28%) gastrointestinal symptoms (P < .001). Constipation was more prevalent in patients with rapid GE 2 (72%) than rapid GE 1 (47%) or rapid GE12 hours (67%) (P < .05). Among 179 diabetes mellitus (DM) patients, 15% had rapid GE, which was not associated with the DM phenotype. By multivariable analysis, insulin therapy (odds ratio [OR], 0.36; 95% confidence interval [CI], 0.15‐0.88), and weight loss (OR, 0.10; 95% CI, 0.01‐0.78) were associated with a lower risk of rapid than normal GE in DM.ConclusionsEight percent of patients undergoing scintigraphy had rapid GE, which is most frequently associated with upper and lower gastrointestinal symptoms; constipation is common. Insulin therapy and weight loss were associated with a lower risk of rapid than normal GE in DM patients.

AbstractBackgroundOur aim is to explain the lack of clarity in the ways in which anxiety and depression, which are common in defecatory disorders (DD), may contribute to the disorder. In this study, we evaluate the effects of mental stress and relaxation on anal pressures and the mechanisms thereof.MethodsIn 38 healthy women and 36 DD patients, rectoanal pressures were assessed at rest and during mental stressors (ie, word‐color conflict [Stroop] and mental arithmetic tests) and mental relaxation, before and after randomization to placebo or the adrenergic α1‐antagonist alfuzosin.Key ResultsDuring the baseline Stroop test, the anal pressure increased by 6 ± 13 mm Hg (mean ± SD, P = 0.004) in healthy women and 9 ± 10 mm Hg (P = 0.0001) in constipated women. During mental arithmetic, the anal pressure increased in healthy (4 ± 8 mm Hg, P = 0.002) and constipated women (5 ± 9 mm Hg, P = 0.004). After relaxation, anal pressure declined (P = 0.0004) by 3 ± 4 mm Hg in DD patients but not in controls. Alfuzosin reduced (P = 0.0001) anal resting pressure (by 31 ± 19 mm Hg) vs placebo (16 ± 18 mm Hg). However, during the postdrug Stroop test, anal pressure increased (P = 0.0001) in participants who received alfuzosin but not placebo.Conclusions & InferencesIn healthy controls and DD patients, mental stressors likely increased anal pressure by contracting the internal anal sphincter; relaxation reduced anal pressure in DD patients. Alfuzosin reduced anal resting pressure but did not block the Stroop‐mediated contractile response, which suggests that this response is not entirely mediated by adrenergic α1 receptors.

AbstractBackgroundHigh‐resolution manometry (HRM) is used to measure rectoanal pressures in defecatory disorders and fecal incontinence. This study sought to define normal values for rectoanal HRM, ascertain the effects of age and BMI on rectoanal pressures, and compare pressures in asymptomatic women with normal and prolonged balloon expulsion time (BET).MethodsHigh‐resolution manometry pressures and BET were measured in 163 asymptomatic healthy participants. Women (96) and men (47) with normal BET were used to estimate normal values and the effects of age/BMI on pressures using a Medtronic 4.2‐mm‐diameter rectoanal catheter.Key ResultsAge is associated with lower resting pressure, higher rectal pressure during evacuation, and a higher rectoanal gradient during evacuation in women and men. In women, the BET is also inversely correlated with age while the BMI is correlated with a higher threshold volume for discomfort and a longer BET. The anal squeeze pressure increment, squeeze duration, and HPZ length are higher in men than women. The rectoanal gradient during evacuation is also lower (ie, more negative) in asymptomatic women with an abnormal than a normal BET.Conclusions & InferencesThese findings provide an expanded database of normal values for anorectal HRM in men and women. Age and sex affect anal resting and squeeze pressures, respectively; rectal pressure during evacuation is also higher in older people. Less than 15% of asymptomatic people have BET >60 seconds, which is associated with manometry features of impaired evacuation.

Sleep apnea is characterized by abnormal interruptions in breathing during sleep due to partial or complete airway obstructions affecting middle-aged men and women on an estimated ∼4% of the population [1]. While the disorder is clinically manageable to relieve patients, the challenge occurs with diagnosis, with many patients going undiagnosed leading to further complications such as ischemic heart diseases, stroke etc. Sleep apnea also significantly affects the quality of day to day life causing sleepiness and fatigue. Polysomnography (PSG) technique is currently a used for detecting sleep apnea which is a comprehensive sleep test to diagnose sleep disorders by recording brain waves, the oxygen level in the blood, heart rate, breathing, eye and leg movements during the study. However, PSG test is very expensive, requires patients to stay overnight and is known to cause inconvenience to the patients.