Innovative Healthcare in Medicine and Nursing

Objective: This review critically evaluates the paradigm shift from traditional to online medical research training systems, addressing systemic challenges, technological innovations, and implementation strategies. 

Methods: Through a systematic analysis of 27 peer-reviewed studies (2016-2024) from PubMed, Web of Science, and CNKI databases, we employed a mixed-methods approach combining bibliometric analysis and case study comparisons across 15 countries. 

Results: Key findings demonstrate: (1) 78% of institutions using AI-curated curricula reported ≥30% improvement in research output quality; (2) VR-based surgical simulations reduced critical error rates from 18.7% to 5.2% (p<0.01); (3) Blockchain-enhanced credential verification decreased academic misconduct incidents by 64%. 

Conclusion: The convergence of adaptive learning architectures with decentralized education models presents an unprecedented opportunity to democratize medical research capabilities globally, particularly benefiting resource-limited regions.

Background: Gastric cancer (GC) is easy to recur after operation and the prognosis is poor. Smoking is closely related to the risk of multiple malignant tumors, but the relationship between smoking and the recurrence of GC is not clear. The purpose of this study is to further explore the relationship between smoking cessation and the recurrence of GC based on the data of the National Health and Nutrition Examination Survey (NHANES).

Gastric cancer; Smoking; Smoking cessation; recurrence

Methods: Based on ten surveys of NHANES (1999-2000, 2001-2002, 2003-2004, 2005-2006, 2007-2008, 2009-2010, 2011-2012, 2013-2014, 2015-2016, 2017-2018), the patients with GC were included and matched with non-cancer individuals according to age and sex to analyze the factors related to GC. The patients with GC were further divided into recurrence group and non-recurrence group, and the factors related to recurrence were analyzed by multivariate logistic regression.

Results: Multivariate logistic regression analysis showed that there was significant statistical correlation between heavy drinking, smoking history and GC. The average age, the ratio of male, the ratio of heavy drinking and the ratio of smoking history in the recurrence group were significantly higher than those in the non-recurrence group (P<0.05). The recurrence rate of GC patients without smoking cessation was the highest, while the recurrence rate of GC patients without smoking history was the lowest (P<0.05). Multivariate logistic regression analysis showed that age, male, heavy drinking and smoking history were closely related to the recurrence of GC (P<0.05).

Conclusion: Smoking is closely related to the recurrence of GC. The recurrence rate of GC in patients who quit smoking is lower than that in patients who do not quit smoking.

Background: Colorectal cancer can be treated by surgical resection combined with radiotherapy and chemotherapy to achieve satisfactory short-term efficacy, but it is easy to relapse. Smoking is closely related to the risk of a variety of malignant tumors, but the relationship between smoking and colorectal cancer recurrence is not clear. The purpose of this study is to further explore the relationship between smoking cessation and colorectal recurrence based on the data from the National Health and Nutrition Examination Survey (NHANES).

Methods: Based on  ten surveys conducted by the NHANES project from 1999 to 2018 (1999-2000, 2001-2002, 2003-2004, 2005-2006, 2007-2008, 2009-2010, 2011-2012, 2013-2014, 2015-2016, 2017-2018), the patients with established colorectal cancer were included as the case group. Non-cancer individuals were included in a 1:1 matching according to age and sex as the control group.. Factors related to colorectal cancer were analyzed. The colorectal cancer patients were further divided into the recurrence group and the non-recurrence group, and multivariate logistic regression analysis was used to analyze the factors related to recurrence.

Results: In the matched study of colorectal cancer patients and non-cancer individuals, the results of multivariate Logistic regression analysis showed that alcohol consumption, smoking history, and aspirin use were all significantly associated with colorectal cancer. Among colorectal cancer patients, the average age, the rate of alcohol consumption, and the rate of having a smoking history in the recurrence group were significantly higher than those in the non-recurrence group (P < 0.05), while the rate of aspirin use was lower than that in the non-recurrence group (P < 0.05). Among patients with different smoking statuses, the recurrence rate was the highest in current smokers with colorectal cancer and the lowest in those without a smoking history (P < 0.05).The results of multivariate Logistic regression analysis showed that age, aspirin use, alcohol consumption history, and smoking history were all closely related to the recurrence of colorectal cancer (P < 0.05).

Conclusion: Smoking is closely related to the recurrence of colorectal cancer. Smoking cessation may be beneficial to reduce the recurrence rate of colorectal cancer after surgery.

Objective: The aim of the study is to investigate acid-base in patients receiving hemodialysis (HD) and the effect of HD on metabolic acidosis.

Methods: We designed this single-center retrospective study. We collected all data of the pre-dialysis total carbon dioxide (tCO2). We used tCO2 and anion gap (AG) to access metabolic acidosis. The differences of tCO2 and AG between pre-dialysis and post-dialysis were compared. Metabolic acidosis was considered when tCO2< 22.0mmol/l. Metabolic acidosis was defined as high AG metabolic if AG>10.

Results: Totally, we included 1452 pre-dialysis electrolyte tests. The mean pre-HD tCO2 was 21.35 ± 3.19 mmol/l. The prevalence of metabolic acidosis (pre-HD tCO2<22 mmol/L) was 58.20 %. The mean of pre-HD AG was 15.06 ± 3.69mmol/l [Median and quartile:14.9(12.78,17.4)]. 828 cases complicated with high AG metabolic acidosis. We analyzed 141 pairs of pre-dialysis & post-dialysis metabolic acidosis parameters. Before dialysis, patients had the mean of tCO2 and AG 20.77 ± 3.14 mmol/L and 15.50 ± 3.35 mmol/L, respectively. Δ[HCO3-] was 3.23 ± 3.14 mmol/L. Δ[AG] was 5.78 ± 3.29 mmol/L. After HD, the mean tCO2 was 24.90 ± 2.99 mmol/L. Although post-dialysis tCO2 was significantly higher than pre-dialysis tCO2,23 (16.31%) patients still had metabolic acidosis (tCO2<22mmol/L). The average increase of post-dialysis tCO2 concentration was only 4.13 mmol/L.

Conclusion: How to correct metabolic acidosis in HD patients remains a challenge.  Alkaline dialysate can increase the level of post-dialysis [HCO3-]. At that time, the increase of bicarbonate was not as high as we expected.

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