Background: Gastric cancer is one of the deadliest malignant diseases, and the non-invasive screening and diagnostics options for it are limited. In this article, we present a multi-modular device for breath analysis coupled with a machine learning approach for the detection of cancer-specific breath from the shapes of sensor response curves (taxonomies of clusters). Methods: We analyzed the breaths of 54 gastric cancer patients and 85 control group participants. The analysis was carried out using a breath analyzer with gold nanoparticle and metal oxide sensors. The response of the sensors was analyzed on the basis of the curve shapes and other features commonly used for comparison. These features were then used to train machine learning models using Naïve Bayes classifiers, Support Vector Machines and Random Forests. Results: The accuracy of the trained models reached 77.8% (sensitivity: up to 66.54%; specificity: up to 92.39%). The use of the proposed shape-based features improved the accuracy in most cases, especially the overall accuracy and sensitivity. Conclusions: The results show that this point-of-care breath analyzer and data analysis approach constitute a promising combination for the detection of gastric cancer-specific breath. The cluster taxonomy-based sensor reaction curve representation improved the results, and could be used in other similar applications.

The human body emits a multitude of volatile organic compounds (VOCs) via tissues and various bodily fluids or exhaled breath. These compounds collectively create a distinctive chemical profile, which can potentially be employed to identify changes in human metabolism associated with colorectal cancer (CRC) and, consequently, facilitate the diagnosis of this disease. The main goal of this study was to investigate and characterize the VOCs’ chemical patterns associated with the breath of CRC patients and controls and identify potential expiratory markers of this disease. For this purpose, gas chromatography–mass spectrometry was applied. Collectively, 1656 distinct compounds were identified in the breath samples provided by 152 subjects. Twenty-two statistically significant VOCs (p-xylene; hexanal; 2-methyl-1,3-dioxolane; 2,2,4-trimethyl-1,3-pentanediol diisobutyrate; hexadecane; nonane; ethylbenzene; cyclohexanone; diethyl phthalate; 6-methyl-5-hepten-2-one; tetrahydro-2H-pyran-2-one; 2-butanone; benzaldehyde; dodecanal; benzothiazole; tetradecane; 1-dodecanol; 1-benzene; 3-methylcyclopentyl acetate; 1-nonene; toluene) were observed at higher concentrations in the exhaled breath of the CRC group. The elevated levels of these VOCs in CRC patients’ breath suggest the potential for these compounds to serve as biomarkers for CRC.

As of today, there is a lack of a perfect non-invasive test for the surveillance of patients for potential relapse following curative treatment. Breath volatile organic compounds (VOCs) have been demonstrated to be an accurate diagnostic tool for gastric cancer (GC) detection; here, we aimed to prove the yield of the markers in surveillance, i.e., following curative surgical management. Patients were sampled in regular intervals before and within 3 years following curative surgery for GC; gas chromatography-mass spectrometry (GC-MS) and nanosensor technologies were used for the VOC assessment. GC-MS measurements revealed a single VOC (14b-Pregnane) that significantly decreased at 12 months, and three VOCs (Isochiapin B, Dotriacontane, Threitol, 2-O-octyl-) that decreased at 18 months following surgery. The nanomaterial-based sensors S9 and S14 revealed changes in the breath VOC content 9 months after surgery. Our study results confirm the cancer origin of the particular VOCs, as well as suggest the value of breath VOC testing for cancer patient surveillance, either during the treatment phase or thereafter, for potential relapse.

Cancer survivors face numerous challenges, and digital health interventions can empower them by enhancing self-efficacy and patient activation. This prospective study aimed to assess the impact of a mHealth app on self-efficacy and patient activation in 166 breast and colorectal cancer survivors. Participants received a smart bracelet and used the app to access personalized care plans. Data were collected at baseline and follow-ups, including patient-reported outcomes and clinician feedback. The study demonstrated positive impacts on self-efficacy and patient activation. The overall trial retention rate was 75.3%. Participants reported high levels of activation (PAM levels 1–3: P = 1.0; level 4: P = 0.65) and expressed a willingness to stay informed about their disease (CASE-Cancer factor 1: P = 0.98; factor 2: P = 0.66; factor 3: P = 0.25). Usability of the app improved, with an increase in participants rating the system as having excellent usability (from 14.82% to 22.22%). Additional qualitative analysis revealed positive experiences from both patients and clinicians. This paper contributes significantly to cancer survivorship care by providing personalized care plans tailored to individual needs. The PERSIST platform shows promise in improving patient outcomes and enhancing self-management abilities in cancer survivors. Further research with larger and more diverse populations is needed to establish its effectiveness.

Background and Objectives: Acute appendicitis is the most common abdominal emergency requiring surgery and it has an estimated lifetime risk of 6.7 to 8.6%. The COVID-19 pandemic has transformed medical care worldwide, influencing diagnostic tactics, treatment modalities and outcomes. Our study aims to compare and analyze management of acute appendicitis before and during the first and second waves of the pandemic. Materials and Methods: Patients suffering acute appendicitis were enrolled retrospectively in a single-center study for a 10-month period before the pandemic (pre-COVID-19 period: 1 March to 31 December 2019) and during the pandemic (COVID-19 period: 1 March to 31 December 2020). The total number of patients, disease severity, diagnostic methods, complications, length of hospitalization and outcomes were analyzed. Results: A total number of 863 patients were included, 454 patients in the pre-COVID-19 period and 409 patients in the COVID-19 period. Compared to the pre-COVID-19 period, the number of complicated appendicitis increased in the COVID-19 period (24.4% to 37.2%; p < 0.001). The proportion of laparoscopic appendectomies increased during the COVID-19 period but did not show statistically significant differences between periods. In both time periods, we found that open technique was the chosen surgical approach more frequently in elderly patients (p < 0.001). Generalized peritonitis was significantly more common during the COVID-19 period (3.5% vs. 6.1%, p < 0.001). The postoperative course of patients was similar in the pre-COVID-19 period and during the COVID-19 period, with no significant differences in ICU admissions, overall hospital stay or morbidity. Conclusions: The COVID-19 pandemic has led to a significant increase in complicated forms of acute appendicitis; however, no significant impact was observed in terms of diagnostic or treatment approach.

Achalasia is a primary defect of esophageal motility of unknown aetiology, characterised by peristaltic dysfunction of the esophagus and impaired relaxation of the lower esophageal sphincter. The most common symptoms are dysphagia, regurgitation, weight loss, and chest burning. There are various treatment options for achalasia: botulinum toxin injections, pneumatic dilatation, Heller myotomy, and peroral endoscopic myotomy. The aim of the study was to access the efficacy and quality of life of patients with achalasia after surgical treatment — laparoscopic Heller myotomy and Dor fundoplication. All of the patients after surgery had a high gastrointestinal quality of life index. For all patients, during the follow-up period (median 2.4 years), the intensity of clinical symptoms after the procedure declined. Laparoscopic Heller myotomy with Dor fundoplication is a safe and effective method of treating achalasia and can reduce clinical symptoms and improve patients' quality of life.