World journal of methodology最新文献

The integration of Artificial Intelligence (AI) into healthcare research promises unprecedented advancements in medical diagnostics, treatment personalization, and patient care management. However, these innovations also bring forth significant ethical challenges that must be addressed to maintain public trust, ensure patient safety, and uphold data integrity. This article sets out to introduce a detailed framework designed to steer governance and offer a systematic method for assuring that AI applications in healthcare research are developed and executed with integrity and adherence to medical research ethics.

In the aftermath of the coronavirus disease 2019 (COVID-19) pandemic in Brazil, accountability is crucial for those who denied the severity of the virus, spreading false information and causing harm. Some individuals have already faced legal proceedings against them, revealing economic motivations behind their actions. It is equally important to hold doctors accountable for prescribing ineffective treatments, putting the population at risk. The leaders of the denial movement and the federal government, who mishandled the pandemic, should be held accountable for the high death toll. Seeking justice from the legislative and executive branches is necessary, along with exemplary measures for those who spread misinformation about COVID-19.

The aim of this study is to illustrate the complexity of pain management in chronic pancreatitis (CP). In this context, pain represents the most common and debilitating symptom, and it deeply affects patient's quality of life. Multiple rating scales (unidimensional, bidimensional and multidimensional) have been proposed to quantify CP pain. However, it represents the result of complex mechanisms, involving genetic, neuropathic and neurogenic factors. Considering all these aspects, the treatment should be discussed in a multidisciplinary setting and it should be approached in a stepwise manner. First, a lifestyle change is recommended and nonsteroidal anti-inflammatory drugs represent the gold standard among medical treatments for CP patients. The second step, after medical approach, is endoscopic therapy, especially for complicated CP. In case of failure, tailored surgery represents the third step and decompressive or resection procedures can be chosen. In conclusion, CP pain's management is challenging considering all these complex aspects and the lack of international protocols.

Background: Immunization is a key component of primary health care and an indisputable human right. Vaccines are critical to the prevention and control of infectious disease outbreaks. The coronavirus disease 2019 (COVID-19) pandemic and associated disruptions over the past two years have strained the health systems, with many children missing out on essential childhood vaccines.

Aim: To evaluate the immunization coverage among 12-23-month-old children in the rural areas of Community Health Centre (CHC) Dighal and to determine the factors influencing the existing immunization coverage.

Methods: A coverage evaluation survey was conducted according to the 30-cluster sampling technique, which is the standard methodology for such surveys devised by World Health Organization. A total of 300 children aged 12-23 months were included, whose immunization details were noted from their immunization cards.

Results: Full immunization rate was noted in 86.7% of the children, with partial and non-immunized children accounting for 9% and 4.3% respectively. The full immunization dropout rate was 4.2%. The common reasons for partial or non-immunization were family problem including illness of mother, vaccine not being available and child being ill. Place of birth (P = 0.014) and availability of immunization card (P < 0.001) were significant predictors of the immunization status. Since the study was conducted in 2020/2021, health services were disrupted due to the COVID-19 lockdown.

Conclusion: Due to the coverage being higher than the national average, it was concluded that the immunization coverage was optimal and not affected by the COVID-19 pandemic.

Background: The lymphocyte to monocyte ratio (LMR) is considered a marker of systemic inflammation in cardiovascular disease and acts as predictor of mortality in coronary artery disease.

Aim: To investigate the predictive role of LMR in diabetic coronary artery disease patients.

Methods: This cross-sectional study was conducted at tertiary care super-specialty hospital at New Delhi, India. A total of 200 angiography-proven coronary artery disease (CAD) patients were enrolled and grouped into two categories: Group I [CAD patients with type 2 diabetes mellitus (T2DM) and glycated hemoglobin (HbA1c) levels ≥ 6.5%], and Group II (CAD patients without T2DM and HbA1c levels < 6.5%). Serum lipoproteins, HbA1c, and complete blood count of enrolled patients were analyzed using fully automatic analyzers.

Results: The logistic regression analysis showed an odds ratio of 1.48 (95%CI: 1.28-1.72, P < 0.05) for diabetic coronary artery disease patients (Group I) in unadjusted model. After adjusting for age, gender, diet, smoking, and hypertension history, the odds ratio increased to 1.49 (95%CI: 1.29-1.74, P < 0.01) in close association with LMR. Further adjustment for high cholesterol and triglycerides yielded the same odds ratio of 1.49 (95%CI: 1.27-1.75, P < 0.01). Receiver operating characteristic curve analysis revealed 74% sensitivity, 64% specificity, and 0.74 area under the curve (95%CI: 0.67-0.80, P < 0.001), suggesting moderate predictive accuracy for diabetic CAD patients.

Conclusion: LMR showed positive association with diabetic coronary artery disease, with moderate predictive accuracy. These findings have implications for improving CAD management in diabetics, necessitating further research and targeted interventions.

Background: The first wave of coronavirus disease 2019 (COVID-19) pandemic in Spain lasted from middle March to the end of June 2020. Spanish population was subjected to lockdown periods and scheduled surgeries were discontinued or reduced during variable periods. In our centre, we managed patients previously and newly diagnosed with cancer. We established a strategy based on limiting perioperative social contacts, preoperative screening (symptoms and reverse transcription-polymerase chain reaction) and creating separated in-hospital COVID-19-free pathways for non-infected patients. We also adopted some practice modifications (surgery in different facilities, changes in staff and guidelines, using continuously changing personal protective equipment…), that supposed new inconveniences.

Aim: To analyse cancer patients with a decision for surgery managed during the first wave, focalizing on outcomes and pandemic-related modifications.

Methods: We prospectively included adults with a confirmed diagnosis of colorectal, oesophago-gastric, liver-pancreatic or breast cancer with a decision for surgery, regardless of whether they ultimately underwent surgery. We analysed short-term outcomes [30-d postoperative morbimortality and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection] and outcomes after 3 years (adjuvant therapies, oncological events, death, SARS-CoV-2 infection and vaccination). We also investigated modifications to usual practice.

Results: From 96 included patients, seven didn't receive treatment that period and four never (3 due to COVID-19). Operated patients: 28 colon and 21 rectal cancers; laparoscopy 53.6%/90.0%, mortality 3.57%/0%, major complications 7.04%/25.00%, anastomotic leaks 0%/5.00%, 3-years disease-free survival (DFS) 82.14%/52.4% and overall survival (OS) 78.57%/76.2%. Six liver metastases and six pancreatic cancers: no mortality, one major complication, three grade A/B liver failures, one bile leak; 3-year DFS 0%/33.3% and OS 50.0%/33.3% (liver metastases/pancreatic carcinoma). 5 gastric and 2 oesophageal tumours: mortality 0%/50%, major complications 0%/100%, anastomotic leaks 0%/100%, 3-year DFS and OS 66.67% (gastric carcinoma) and 0% (oesophagus). Twenty breast cancer without deaths/major complications; 3-year OS 100% and DFS 85%. Nobody contracted SARS-CoV-2 postoperatively. COVID-19 pandemic-related changes: 78.2% treated in alternative buildings, 43.8% waited more than 4 weeks, two additional colostomies and fewer laparoscopies.

Conclusion: Some patients lost curative-intent surgery due to COVID-19 pandemic. Despite practice modifications and 43.8% delays higher than 4 weeks, surgery was resumed with minimal changes without impacting outcomes. Clean pathways are essential to continue surgery safely.

Kidney transplantation (KT) is the optimal form of renal replacement therapy for patients with end-stage renal diseases. However, this health service is not available to all patients, especially in developing countries. The deceased donor KT programs are mostly absent, and the living donor KT centers are scarce. Single-center studies presenting experiences from developing countries usually report a variety of challenges. This review addresses these challenges and the opposing strategies by reviewing the single-center experiences of developing countries. The financial challenges hamper the infrastructural and material availability, coverage of transplant costs, and qualification of medical personnel. The sociocultural challenges influence organ donation, equity of beneficence, and regular follow-up work. Low interests and motives for transplantation may result from high medicolegal responsibilities in KT practice, intense potential psychosocial burdens, complex qualification protocols, and low productivity or compensation for KT practice. Low medical literacy about KT advantages is prevalent among clinicians, patients, and the public. The inefficient organizational and regulatory oversight is translated into inefficient healthcare systems, absent national KT programs and registries, uncoordinated job descriptions and qualification protocols, uncoordinated on-site investigations with regulatory constraints, and the prevalence of commercial KT practices. These challenges resulted in noticeable differences between KT services in developed and developing countries. The coping strategies can be summarized in two main mechanisms: The first mechanism is maximizing the available resources by increasing the rates of living kidney donation, promoting the expertise of medical personnel, reducing material consumption, and supporting the establishment and maintenance of KT programs. The latter warrants the expansion of the public sector and the elimination of non-ethical KT practices. The second mechanism is recruiting external resources, including financial, experience, and training agreements.

Continuous glucose monitoring (CGM) is a popular technology among the diabetic population, especially in patients with type 1 diabetes and those with type 2 diabetes treated with insulin. The American Diabetes Association recommends standardization of CGM reports with visual cues, such as the ambulatory glucose profile. Nevertheless, interpreting this report requires training and time for CGM to be cost-efficient. In this work it has been proposed to incorporate Japanese candlestick charts in glucose monitoring. These graphs are used in price analysis in financial markets and are easier to view. Each candle provides extra information to make prudent decisions since it reports the opening, maximum, minimum and closing glucose levels of the chosen time frame, usually the daily one. The Japanese candlestick chart is an interesting tool to be considered in glucose control. This graphic representation allows identification of glucose trends easily through the colors of the candles and maximum and minimum glucose values.

In accordance with the World Health Organization data, cancer remains at the forefront of fatal diseases. An upward trend in cancer incidence and mortality has been observed globally, emphasizing that efforts in developing detection and treatment methods should continue. The diagnostic path typically begins with learning the medical history of a patient; this is followed by basic blood tests and imaging tests to indicate where cancer may be located to schedule a needle biopsy. Prompt initiation of diagnosis is crucial since delayed cancer detection entails higher costs of treatment and hospitalization. Thus, there is a need for novel cancer detection methods such as liquid biopsy, elastography, synthetic biosensors, fluorescence imaging, and reflectance confocal microscopy. Conventional therapeutic methods, although still common in clinical practice, pose many limitations and are unsatisfactory. Nowadays, there is a dynamic advancement of clinical research and the development of more precise and effective methods such as oncolytic virotherapy, exosome-based therapy, nanotechnology, dendritic cells, chimeric antigen receptors, immune checkpoint inhibitors, natural product-based therapy, tumor-treating fields, and photodynamic therapy. The present paper compares available data on conventional and modern methods of cancer detection and therapy to facilitate an understanding of this rapidly advancing field and its future directions. As evidenced, modern methods are not without drawbacks; there is still a need to develop new detection strategies and therapeutic approaches to improve sensitivity, specificity, safety, and efficacy. Nevertheless, an appropriate route has been taken, as confirmed by the approval of some modern methods by the Food and Drug Administration.

Background: It is increasingly common to find patients affected by a combination of type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD), and studies are able to correlate their relationships with available biological and clinical evidence. The aim of the current study was to apply association rule mining (ARM) to discover whether there are consistent patterns of clinical features relevant to these diseases. ARM leverages clinical and laboratory data to the meaningful patterns for diabetic CAD by harnessing the power help of data-driven algorithms to optimise the decision-making in patient care.

Aim: To reinforce the evidence of the T2DM-CAD interplay and demonstrate the ability of ARM to provide new insights into multivariate pattern discovery.

Methods: This cross-sectional study was conducted at the Department of Biochemistry in a specialized tertiary care centre in Delhi, involving a total of 300 consented subjects categorized into three groups: CAD with diabetes, CAD without diabetes, and healthy controls, with 100 subjects in each group. The participants were enrolled from the Cardiology IPD & OPD for the sample collection. The study employed ARM technique to extract the meaningful patterns and relationships from the clinical data with its original value.

Results: The clinical dataset comprised 35 attributes from enrolled subjects. The analysis produced rules with a maximum branching factor of 4 and a rule length of 5, necessitating a 1% probability increase for enhancement. Prominent patterns emerged, highlighting strong links between health indicators and diabetes likelihood, particularly elevated HbA1C and random blood sugar levels. The ARM technique identified individuals with a random blood sugar level > 175 and HbA1C > 6.6 are likely in the "CAD-with-diabetes" group, offering valuable insights into health indicators and influencing factors on disease outcomes.

Conclusion: The application of this method holds promise for healthcare practitioners to offer valuable insights for enhancing patient treatment targeting specific subtypes of CAD with diabetes. Implying artificial intelligence techniques with medical data, we have shown the potential for personalized healthcare and the development of user-friendly applications aimed at improving cardiovascular health outcomes for this high-risk population to optimise the decision-making in patient care.