Tag: pubmed

J Surg Res. 2026 Feb 10;319:125-133. doi: 10.1016/j.jss.2026.01.006. Online ahead of print.

ABSTRACT

INTRODUCTION: Surgical treatment of noncolorectal, non-neuroendocrine liver metastases (NCNNLM) remains unclear. This nationwide study evaluated the outcome of patients with NCNNLM, evaluated at multidisciplinary team conferences and included in the Danish Liver Cancer Group Database, according to surgery or no surgery.

METHODS: We identified all patients with NCNNLM evaluated at multidisciplinary team conferences at the four specialized centers in Denmark between October 2013 and November 2023. Patient characteristics and survival were analyzed using descriptive statistics and illustrated by Kaplan-Meier curves, respectively. Prognostic factors were assessed with logistic regression, Cox regression, and accelerated failure time models.

RESULTS: 605 patients were included in the analyses. The median follow-up was 20 mo, none were lost to follow-up. The median age of patients was 64 y, with a female predominance (58%). Most patients (93%) had World Health Organization (WHO) performance status 0-1. The overall 5-y survival rate was 29%, with a median survival of 27 mo. Surgery was performed in 307 patients (51%). Surgical intervention was associated with better survival compared with nonsurgical treatment (median survival 39 versus 13 mo, P < 0.05). Poor prognostic factors included age exceeding 64 y (hazard ratio = 1.022, P < 0.0001) and WHO performance status 2-4 (odds ratio 6.89, P = 0.007).

CONCLUSIONS: NCNNLM carries a poor prognosis. Surgery of liver metastasis is associated with improved survival with age, WHO performance status, and primary cancer type serving as important prognostic factors. However, from our study we could not establish a causal effect of surgery and confounding by indication is likely.

PMID:41671599 | DOI:10.1016/j.jss.2026.01.006

J Surg Res. 2026 Feb 10;319:100-107. doi: 10.1016/j.jss.2026.01.017. Online ahead of print.

ABSTRACT

INTRODUCTION: This study aims to evaluate the association between unplanned ICU admission and clinical outcomes in adult and geriatric trauma patients with severe sepsis. Additionally, this study assesses predictors of worsened outcomes in this population.

METHODS: This retrospective cohort study analyzed the ACS-TQIP database (2017-2023) to analyze outcomes associated with unplanned ICU admission in adult and geriatric trauma patients (ISS ≥ 15) with severe sepsis. The primary outcome was in-hospital mortality, and secondary outcomes included discharge disposition, ICU-LOS, ventilator-free days, and complications.

RESULTS: In both adult and geriatric patients, unplanned ICU admission was associated with significantly lower in-hospital mortality (aOR: 0.460, 95% CI: 0.346-0.610, P < 0.001, SE: 0.145) (aOR: 0.657, 95% CI: 0.438-0.987, P = 0.043, SE: 0.207) and more ventilator-free days (β = 5.067, 95% CI: 3.981-6.153, P < 0.001, SE: 0.554) (β = 2.402, 95% CI: 0.625-4.180, P = 0.008, SE: 0.905). Advanced age (over 64 years) (aOR: 1.487, 95% CI: 1.140-1.924, P = 0.003, SE: 0.134), ISS over 25 (aOR: 1.487, 95% CI: 1.251-1.768, P < 0.001, SE: 0.088), and having multiple comorbidities (aOR: 1.402, 95% CI: 1.152-1.706, P < 0.001, SE: 0.100) were found to be associated with worse outcomes.

CONCLUSIONS: Findings from this national analysis highlighted predictors associated with worsening outcomes in adult and geriatric trauma patients with severe sepsis. Additionally, while unplanned ICU admission was associated with improved outcomes in both adult and geriatric trauma patients with severe sepsis compared to those admitted to hospital floors, its high resource utilization emphasizes the importance of developing targeted care strategies to prevent resource overutilization and clinical deterioration in this patient population.

PMID:41671596 | DOI:10.1016/j.jss.2026.01.017

J Infect Public Health. 2026 Feb 6;19(4):103169. doi: 10.1016/j.jiph.2026.103169. Online ahead of print.

ABSTRACT

BACKGROUND: Rifampicin-resistant tuberculosis (RR-TB) remains a global health challenge, which is often characterized by limited treatment options and increased morbidity and mortality. Despite advances in diagnostics and the introduction of new drug regimens, treatment success for drug-resistant TB remains low. There is limited data on clinical, sociodemographic, and microbiological factors that influence patient outcomes. The aim of the study is to evaluate TB treatment outcomes among individuals diagnosed with RR-TB and to identify predictors of favourable and unfavourable treatment outcomes.

METHODS: We conducted a retrospective study to analyse treatment outcomes of 162 individuals diagnosed with RR-TB using GeneXpert MTB/RIF and phenotypic drug susceptibility testing (pDST) from 2016 to 2023. Treatment outcome proportions were estimated using the binomial exact method with 95 % confidence intervals (CI). Predictors associated with unfavourable treatment outcomes were assessed using logistic regression models.

RESULTS: Of the 162 individuals, 102(62.7 %) were male with a median age of 39 (interquartile range (IQR): 29-50). Most individuals, 78(48.1 %), were from the Greater Gaborone health district, and 88(54.3 %) were people living with HIV (PLWH). Among included individuals, 137(84.6 %, 95 % CI: 78.2-89.7) were successfully treated. Males had higher odds of unfavourable treatment outcomes compared to females (OR = 1.70; 95 % CI: 0.73-3.98). Among those cured, a slightly higher proportion was observed among PLWH (71.8 %, 95 % CI: 62.1-80.3) compared to people not living with HIV (PNLWH) (69.2 %, 95 % CI: 58.7-78.5). However, the mortality rate was higher among PLWH (10.7 %; 95 % CI: 5.5-18.3) than among PNLWH (6.6 %; 95 % CI: 2.5-13.8). Those with a history of TB treatment had 1.03 odds of unfavourable treatment outcomes (95 % CI: 0.40-2.73); however, this association was not statistically significant.

CONCLUSION: Our study shows a high rate of successful treatment outcomes among individuals with RR-TB, with no significant difference based on sex, TB treatment history, or HIV status. Higher mortality among PLWH highlights the need for targeted interventions among high-risk groups.

PMID:41671595 | DOI:10.1016/j.jiph.2026.103169

JMIR Perioper Med. 2026 Feb 11;9:e82472. doi: 10.2196/82472.

ABSTRACT

BACKGROUND: Enhanced recovery after surgery (ERAS) programs bundle evidence-based interventions to standardize care, expedite recovery, and improve outcomes. As ERAS programs have expanded, it has become clear that a major challenge is monitoring the compliance of bundle elements and outcomes to feedback performance to stakeholders and guide changes. Manual data abstraction is onerous and not feasible. Reliance on receiving new reports from busy health system IT groups is challenging. Therefore, we sought to address this unmet need at our hospital by developing a novel ERAS Datamart system.

OBJECTIVE: Our objectives were to develop a novel Datamart and Tableau dashboard to (1) enable continuous analysis of data, harvested directly from the electronic medical record (EMR), measure compliance and outcomes, and (2) enable end users (e.g., an ERAS coordinator) to create reports customized based on surgical procedure types, requested data variables, and custom date ranges.

METHODS: After “buy-in” from hospital leadership and other stakeholders, data metrics were identified and categorized according to phase of care, that is, preoperative, intraoperative, and postoperative. A multidisciplinary team reviewed International Classification of Diseases, Tenth Revision procedure codes to capture EMR data for patients undergoing ERAS procedures. IT was given a master list with metric names, definitions, and screenshots of the discrete field in the EMR to assist with building the metrics. Validations of the novel Datamart were done against known ERAS patient populations maintained by the surgery clinic.

RESULTS: The Datamart and Tableau dashboard has been built, is functional, and contains over 17,000 patients across 5 ERAS service lines: colorectal (n=1742), joint replacement (n=4235), surgical oncology (n=941), bariatric (n=1130), and cesarean section (n=9390). Currently, 56 metrics spanning the perioperative period have been validated across these populations. Reports can be tailored according to patients, time frames, and metrics. If desired, patient-level raw data can be exported for statistical analyses. Two use cases (total joint replacement and surgical oncology ERAS programs) are presented showing how the Datamart can be used.

CONCLUSIONS: Discrete fields within an EMR can be successfully captured into a novel Datamart and visualized using a custom Tableau dashboard for providing stakeholder feedback, facilitating quality improvement analyses, and auditing pathways.

PMID:41671571 | DOI:10.2196/82472

Neuroradiol J. 2026 Feb 11:19714009261423695. doi: 10.1177/19714009261423695. Online ahead of print.

ABSTRACT

This meta-analysis investigated endovascular thrombectomy (EVT) efficacy and safety versus best medical treatment (BMT), including intravenous thrombolysis or other treatments when applicable, in acute ischemic stroke (AIS) patients with pre-stroke disability (mRS >2), a group frequently excluded from large vessel occlusion trials. Following PRISMA 2020 guidelines, systematic searches of PubMed, Cochrane Central, Web of Science, Scopus, and Embase databases (inception-July 2025) identified English studies (≥4 patients) comparing EVT versus BMT. Data on all-cause mortality, return to baseline mRS, and symptomatic intracranial hemorrhage (sICH) were extracted. OR with 95% CI was estimated via a random-effects model. Five studies (1400 patients; 897 EVT and 503 BMT) with pre-stroke mRS 2-4 were included. EVT significantly reduced all-cause mortality (OR: 0.49, 95% CI: 0.29-0.82, p = .007), demonstrating moderate heterogeneity (I² = 66.9%). It also improved return to baseline mRS (OR: 3.21, 95% CI: 2.02-6.09, p < .001) with negligible heterogeneity (I² = 0%). sICH was more frequent in EVT (OR: 2.24, 95% CI: 0.84-5.94) but not statistically significant (p = .11). EVT offers survival benefits and increased return to baseline functional status for AIS patients with pre-stroke disability, without definitively increasing sICH. Prospective studies are crucial for informing inclusive clinical guidelines.

PMID:41671570 | DOI:10.1177/19714009261423695

JMIR Mhealth Uhealth. 2026 Feb 11;14:e74071. doi: 10.2196/74071.

ABSTRACT

BACKGROUND: Wearable devices enable the remote collection of health parameters, supporting the outpatient care plans recommended by the World Health Organization to manage chronic diseases. While disease-specific monitoring is accurate, a comprehensive analysis of wearables across various chronic diseases helps to standardize remote patient monitoring systems.

OBJECTIVE: This review aimed to identify wearables for remote monitoring of chronic diseases, focusing on (1) wearable devices, (2) sensor types, (3) health parameters, (4) body locations, and (5) medical applications.

METHODS: We developed a search strategy and conducted searches across three databases: PubMed, Web of Science, and Scopus. After reviewing 1160 articles, we selected 61 that addressed cardiovascular, cancer, neurological, metabolic, respiratory, and other diseases. We created a data analysis method based on our 5 objectives to organize the articles for a comprehensive analysis.

RESULTS: From the 61 articles, 39 (64%) used wearable bands such as smartwatches, wristbands, armbands, and straps to monitor chronic diseases. Wearable devices commonly included various sensor types, such as accelerometers (n=39, 64%), photoplethysmographic sensors (n=18, 30%), biopotential meters (n=17, 28%), pressure meters (n=11, 18%), and thermometers (n=9, 15%). These sensors collected diverse health parameters, including acceleration (n=39, 64%), heart rate (n=24, 39%), body temperature (n=9, 15%), blood pressure (n=8, 13%), and peripheral oxygen saturation (n=7, 11%). Common sensor body locations were the wrist, followed by the upper arm and the chest. The medical applications of wearable devices were neurological (n=21, 34%) and cardiovascular diseases (n=15, 25%). Additionally, researchers applied wearable devices for wellness and lifestyle monitoring (n=39, 64%), mainly for activity (n=39, 100%) and sleep (n=10, 26%).

CONCLUSIONS: This review underscores that wearable devices primarily function as bands, commonly worn on the wrist, to monitor chronic diseases. These devices collect data on acceleration, heart rate, body temperature, blood pressure, and peripheral oxygen saturation, with a focus on neurological and cardiovascular diseases. Our findings provide a foundational road map for designing generalized remote patient monitoring systems to manage multimorbidity and support standardized terminology for interoperability across digital health systems. To translate this into practice, we recommend that future research prioritize pragmatic clinical trials with medically certified devices.

PMID:41671558 | DOI:10.2196/74071

JMIR Cancer. 2026 Feb 11;12:e69525. doi: 10.2196/69525.

ABSTRACT

BACKGROUND: Mobile health (mHealth) represents a promising instrument for optimizing symptom management and important lifestyle strategies that enhance self-care and the quality of health care for patients with cancer. The ALIBIRD mHealth platform is a digital health solution specifically designed for the telemonitoring of oncology patients, fostering patient empowerment and supporting clinical decision-making.

OBJECTIVE: The primary objective of this study was to evaluate the patient experience with the ALIBIRD platform. In addition, the study aimed to assess clinical outcomes, particularly in symptom management, nutritional status, and lifestyle, using patient-reported outcome measures (PROMs).

METHODS: The evaluation was conducted over a 30-week period in patients with advanced lung cancer receiving active treatment. Outcome variables included usability, patient experience, symptom burden, lifestyle behaviors (diet, physical activity, and sleep), nutritional status, PROMs, and system-generated clinical alerts. Through the mobile app, patients reported symptoms and completed integrated REDCap (Research Electronic Data Capture) questionnaires assessing lifestyle behaviors and PROMs, while receiving personalized recommendations informed by nutrigenetic and gut microbiota assessments. Daily activity and sleep data were automatically captured using the Fitbit Inspire wearable. Clinicians remotely monitored patient data using a web-based dashboard and performed clinical actions when required, including phone calls, therapeutic adjustments, referrals, and appointment rescheduling. Statistical analysis included descriptive summaries and pre-post comparisons of clinical and patient-reported outcomes.

RESULTS: Out of 20 patients recruited for the study, 14 completed the intervention. The System Usability Scale yielded a score of 90, indicating high usability. Among the 14 completers, adherence to scheduled questionnaires ranged from 94% to 100% for several instruments, and wearable-based monitoring ranged from 66% to 96% across visits. Overall, the ALIBIRD platform collected and processed 3589 patient-reported outcomes related to physical activity, 3468 related to sleep, 679 on-demand symptom entries, and 1524 completed questionnaires. Clinically, 143 alerts were resolved within an average of 2.05 days, resulting in 2 referrals to emergency rooms and 2 early detections of disease progressions. Furthermore, more than 2100 personalized recommendations contributed to a 21% (3/14 patients) increase in adherence to the Mediterranean diet and a 14% (2/14 patients) increase in moderate physical activity.

CONCLUSIONS: The evaluation of the ALIBIRD implementation yielded promising results in that it facilitated the adoption of healthier lifestyle habits while enhancing health self-management among oncology patients. The ALIBIRD mHealth platform emerges as an effective digital health tool that enables closer monitoring of patients and thereby more informed clinical decision-making.

PMID:41671557 | DOI:10.2196/69525

JMIR Mhealth Uhealth. 2026 Feb 11;14:e73651. doi: 10.2196/73651.

ABSTRACT

BACKGROUND: Driven by technological advancements, the proliferation of mobile sports and health apps has revolutionized health management by improving efficiency, cost-effectiveness, and accessibility. While the widespread adoption of these platforms has transformed public health practices and social well-being in China, emerging evidence suggests that inadequacies in their privacy policies may compromise personal information (PI) protection.

OBJECTIVE: This study aimed to conduct a systematic evaluation of privacy policy compliance among 286 mobile sports and health apps in the Chinese Mainland, benchmarking them against the Personal Information Protection Law and associated PI regulatory guidelines.

METHODS: This study develops a privacy policy compliance indicator scale based on the information life cycle and the legal framework for PI protection in the Chinese Mainland. This scale consists of 5 level 1 indicators and 37 level 2 indicators that assess the privacy policy compliance.

RESULTS: The privacy policy compliance of 286 sports and health apps generally performed worse, with only a minimal number (n=11, 3.8%) of apps scoring above 90 points (rated as excellent), nearly half (n=121, 42.3%) of apps scored below 60 points (rated as unqualified). Among the 5 level 1 evaluation indicators for privacy compliance in sports and health apps, the compliance rate for PI collection (mean 74%, SD 25.8%) is the highest, while the compliance rate for PI storage (mean 53.5%, SD 28.4%) is the lowest. The compliance rates for privacy policies across the remaining 3 level 1 evaluation indicators, such as PI usage (mean 54.2%, SD 24.4%), PI entrusted processing, sharing, transferring, and disclosing (mean 62.2%, SD 19.8%), and PI security and feedback (mean 61.7%, SD 21.3%), fall around 60%. Out of 37, 17 level 2 evaluation indicators show a compliance rate below 60%. The compliance rate with privacy policies for 5 level 2 evaluation indicators is exceptionally high, including collection subject (mean 97.2%, SD 16.5%), collection type (mean 99%, SD 10.2%), collection purpose (mean 96.2%, SD 19.3%), reasons for sharing, transferring, and disclosing PI (mean 91.6%, SD 27.8%), and feedback channel (mean 93.4%, SD 24.9%). Notably, 3 indicators exhibit compliance rates below 20%, including sensitive information storage (mean 14%, SD 34.7%), constraints of automatic decision-making (mean 9.4%, SD 29.3%), and deceased user rule (mean 5.2%, SD 22.3%). Authorization for sensitive information (mean 29.4%, SD 45.6%) lagged behind general information (mean 83.6%, SD 37.1%).

CONCLUSIONS: Although some apps have established commendable policies, there are gaps that compromise the efficacy of PI protection. Considering this, this paper proposes targeted actions for 3 stakeholders: users, regulators, and legislators. Only through coordinated action can the app ecosystem close the compliance gaps, reduce PI protection risks, and restore user trust in digital services.

PMID:41671556 | DOI:10.2196/73651

J Med Internet Res. 2026 Feb 11;28:e83075. doi: 10.2196/83075.

ABSTRACT

BACKGROUND: Mobile health (mHealth) technologies can improve hypertension self-management, yet real-world adoption remains limited and unequally distributed.

OBJECTIVE: This study aimed to characterize the profiles, usage patterns, and engagement of active users of a hypertension self-management app (Hypertension.APP) in Germany, with a focus on user engagement and potential digital divides.

METHODS: We conducted a cross-sectional online survey among adult users of Hypertension.APP in Germany between January and September 2023. An 88-item questionnaire assessed app usage patterns, perceived utility, integration into clinical care, sociodemographic and clinical data, and digital health literacy (eHealth Literacy Scale; scores 16-40). Digital health literacy was categorized as low (16-23.99), moderate (24-31.99), or high (32-40). Descriptive statistics and univariable ordinal logistic regression were used to explore associations between sociodemographic and clinical variables and app usage frequency.

RESULTS: Of 254 respondents, the mean age was 53.6 years, and 54.3% (138/254) were male. A total of 44.5% (113/254) had a university or technical college degree, and 44.5% (113/254) reported a monthly net income higher than €2500 (US $2950). Most participants (224/254, 88.2%) reported access to at least two digital devices. Overall, 88.2% (224/254) had moderate or high digital health literacy (eHealth Literacy Scale ≥24). App engagement was high: 80.7% (205/254) reported using the app at least weekly, and 52.4% (133/254) reported using the app to prepare for medical visits. However, only 20.1% (51/254) reported that the app was formally integrated into their medical care, and 11.8% (30/254) indicated that medication had been adjusted based on app data. In univariable ordinal logistic regression analyses, higher education, longer duration of hypertension, and living in a small town (5000-20,000 inhabitants) were associated with more frequent app use, whereas systolic blood pressure of 140 mm Hg or higher was associated with less frequent use. Digital health literacy was not clearly associated with app usage frequency among current users.

CONCLUSIONS: Users of this hypertension self-management app were predominantly well-educated, digitally literate individuals with established hypertension, reinforcing concerns about a persistent digital divide. While app usability and engagement were high, formal clinical integration remained limited. Simply making an app available is insufficient; strategies to promote equitable access, strengthen clinical integration, and support patients with lower digital health literacy are needed for mHealth to contribute effectively to hypertension management.

PMID:41671553 | DOI:10.2196/83075

Am J Public Health. 2026 Mar;116(3):368-371. doi: 10.2105/AJPH.2025.308325.

ABSTRACT

Objectives. To determine the completeness of providers’ COVID-19 vaccine reporting to the Georgia Registry of Immunization Transactions and Services between October 1, 2023, and December 31, 2023. Methods. We performed active, population, and laboratory surveillance in metropolitan Atlanta, Georgia, to identify all residents hospitalized with COVID-19. We selected a subset of patients by using age-stratified random sampling. We telephoned patients or their proxies, pharmacies, and primary care physicians to verify vaccination status and obtain date of unrecorded vaccination (if applicable) for cases without recorded vaccination on or after September 1, 2023. Results. In the 8-county metro Atlanta catchment area, 2165 patients were hospitalized for COVID-19 during the study period, with 135 patients sampled for full chart reviews. Eighty-six patients required follow-up calls, resulting in 525 telephone calls and approximately 120 person-hours. From follow-up, we identified only 1 vaccine dose not in the registry. Conclusions. The registry is relatively reliable for obtaining information on COVID-19 vaccination status for patients in metropolitan Atlanta. Additional follow-up does not elucidate additional information. (Am J Public Health. 2026;116(3):368-371. https://doi.org/10.2105/AJPH.2025.308325).

PMID:41671540 | DOI:10.2105/AJPH.2025.308325