Retrospective Investigations Research Articles

Sex discrepancies in cancer research: a systematic review of prospective and retrospective investigations in lung, melanoma, and colorectal cancers

IntroductionAccording to the latest Cancer Statistics, colorectal, lung, and melanoma are three of the most common cancers that affect both males and females. While males have consistently had a higher incidence and mortality rate in all three types of cancers, females have been shown to have better outcomes. Sex discrepancies in cancer research can impact the efficacy and effectiveness of novel drugs and diagnostic tools. Study results may not accurately represent how the treatment or diagnostic tool performs in the underrepresented sex. To comprehensively assess sex representation in top non-sex-specific cancer research, this systematic review aims to identify if there is equal representation of males and females in colorectal, lung, and melanoma cancer research.MethodsWe explored retrospective and prospective clinical studies published in Pubmed from 2014 to 2023 to identify possible sex discrepancies in colorectal, lung, and melanoma cancer. MeSH terms were employed to retrieve relevant studies for each cancer type (colorectal, lung, melanoma). MeSH terms used include “lung cancer”, “melanoma”, and “colorectal cancer”, in combination with “trials”, “retrospective”, and “prospective”. Extracted data included study characteristics (author, year of publication), study design (prospective or retrospective), sample size, and the number of male and female participants.ResultsThe complete study population consisted of 515,003 patients, of which 275,231 (53%) were males and 237,488 (46%) were females. Specifically, retrospective studies included a total of 302,974 patients with 163,473 (54%) of them identifying as male and 139,072 (46%) patients identifying as female. While prospective studies included a total of 212,029 patients with 111,758 (53%) of these being male and 98,416 (46%) being female. Overall, male representation in the studies included in this systematic review was higher than female representation.DiscussionDisparities in representation were identified in colorectal cancer, lung cancer, and melanoma cancer studies underscoring the need for equitable inclusion of both sexes in cancer research to advance precision medicine and improve patient outcomes. Further exploration of the impact of sex, race, and socioeconomic status on study representation is warranted.

Streamlined detection of Nipah virus antibodies using a split NanoLuc biosensor

ABSTRACT Nipah virus (NiV) is an emerging zoonotic RNA virus that can cause fatal respiratory and neurological diseases in animals and humans. Accurate NiV diagnostics and surveillance tools are crucial for the identification of acute and resolved infections and to improve our understanding of NiV transmission and circulation. Here, we have developed and validated a split NanoLuc luciferase NiV glycoprotein (G) biosensor for detecting antibodies in clinical and animal samples. This assay is performed by simply mixing reagents and measuring luminescence, which depends on the complementation of the split NanoLuc luciferase G biosensor following its binding to antibodies. This anti-NiV-G “mix-and-read” assay was validated using the WHO's first international standard for anti-NiV antibodies and more than 700 serum samples from the NiV-endemic country of Bangladesh. Anti-NiV antibodies from survivors persisted for at least 8 years according to both ⍺NiV-G mix-and-read and NiV neutralization assays. The ⍺NiV-G mix-and-read assay sensitivity (98.6%) and specificity (100%) were comparable to anti-NiV IgG ELISA performance but failed to detect anti-NiV antibodies in samples collected less than a week following the appearance of symptoms. Overall, the anti-NiV-G biosensor represents a simple, fast, and reliable tool that could support the expansion of NiV surveillance and retrospective outbreak investigations.

The Clinical Severity of COVID-19 Variants of Concern: Retrospective Population-Based Analysis.

SARS-CoV-2 variants of concern (VOCs) emerged and rapidly replaced the original strain worldwide. The increased transmissibility of these new variants led to increases in infections, hospitalizations, and mortality. However, there is a scarcity of retrospective investigations examining the severity of all the main VOCs in presence of key public health measures and within various social determinants of health (SDOHs). This study aims to provide a retrospective assessment of the clinical severity of COVID-19 VOCs in the context of heterogenous SDOHs and vaccination rollout. We used a population-based retrospective cohort design with data from the British Columbia COVID-19 Cohort, a linked provincial surveillance platform. To assess the relative severity (hospitalizations, intensive care unit [ICU] admissions, and deaths) of Gamma, Delta, and Omicron infections during 2021 relative to Alpha, we used inverse probability treatment weighted Cox proportional hazard modeling. We also conducted a subanalysis among unvaccinated individuals, as assessed severity differed across VOCs and SDOHs. We included 91,964 individuals infected with a SARS-CoV-2 VOC (Alpha: n=20,487, 22.28%; Gamma: n=15,223, 16.55%; Delta: n=49,161, 53.46%; and Omicron: n=7093, 7.71%). Delta was associated with the most severe disease in terms of hospitalization, ICU admissions, and deaths (hospitalization: adjusted hazard ratio [aHR] 2.00, 95% CI 1.92-2.08; ICU: aHR 2.05, 95% CI 1.91-2.20; death: aHR 3.70, 95% CI 3.23-4.25 relative to Alpha), followed generally by Gamma and then Omicron and Alpha. The relative severity by VOC remained similar in the unvaccinated individual subanalysis, although the proportion of individuals infected with Delta and Omicron who were hospitalized was 2 times higher in those unvaccinated than in those fully vaccinated. Regarding SDOHs, the proportion of hospitalized individuals was higher in areas with lower income across all VOCs, whereas among Alpha and Gamma infections, 2 VOCs that cocirculated, differential distributions of hospitalizations were found among racially minoritized groups. Our study provides robust severity estimates for all VOCs during the COVID-19 pandemic in British Columbia, Canada. Relative to Alpha, we found Delta to be the most severe, followed by Gamma and Omicron. This study highlights the importance of targeted testing and sequencing to ensure timely detection and accurate estimation of severity in emerging variants. It further sheds light on the importance of vaccination coverage and SDOHs in the context of pandemic preparedness to support the prioritization of allocation for resource-constrained or minoritized groups.

From a validated targeted method to a retrospective UHPLC-HRMS non-targeted analysis unveiling COVID-19-related contaminants in clams. Have we bias in marine model organisms for ecotoxicological studies?

This study explores a retrospective non-targeted analysis (NTA), based on Ultra High-Performance Liquid Chromatography coupled to High-Resolution Mass Spectrometry (UHPLC-HRMS), to assess hidden chemicals of emerging concern (CECs) in marine model organisms. Conventional ecotoxicological studies do not include evaluating the natural habitats of the collected organisms, missing the possibility of highlighting unexpected pollutants, and thus compromising the correctness and reliability of the experimental results. In this paper we reprocessed samples previously collected from the Venice Lagoon for ecotoxicological studies and used for targeted analysis of three bisphenols-related compounds (i.e. BPS, BPF and BPAF) on seawater and specimens of the clam Ruditapes philippinarum. Results from the validation were the following: accuracy, expressed as percentage recoveries (R%), in the range 80%<R%<120% for all the considered compounds and matrices, and precision, expressed as relative standard deviation of the absolute areas of IS, was <20% for clams (N = 24) and <15% for seawater (N = 30). LODs ranged from 5 to 50 ng/L for seawater and 5–12 ng/g for clam tissues.After validation, a retrospective NTA was carried out on control samples, showing the presence of some CECs, i.e. Lopinavir, Ritonavir, DEHS, and DEHA, two antiviral drugs used during the COVID-19 pandemic and two plasticizers, respectively, reported here for the first time in the Mediterranean Sea. CEC identifications were confirmed by matching MS/MS spectra with libraries. The present study emphasizes the importance of retrospective investigations to describe the contamination scenario of environmental matrices and the related effect in biota, to correctly address studies on model animals, also including possible “cocktail effects”.

Prevalence of surgical site infections following extraction of impacted mandibular third molars: A systematic review and meta-analysis

Our research aims to assess the prevalence of surgical site infections (SSI) following impacted mandibular third molar extractions. Two independent reviewers conducted a comprehensive systematic literature search across Medline, Scopus and Cochrane Central databases. The pooled prevalence, accompanied by 95% confidence intervals (CI), was calculated. Quality assessments, outlier and influential analyses were performed. Our meta-analysis included seventeen eligible studies, encompassing a total of 37,585 impacted mandibular third molar extractions. The overall prevalence of SSI following impacted mandibular third molar extractions was estimated at 1.7% (95% CI 1%-2.6%), indicating considerable heterogeneity among the studies. No study was identified as critically influential. This study highlights the imperative for future well-constructed prospective and retrospective investigations to deepen our understanding of the etiological nuances and refine management approaches for this prevalent postoperative complication.

RETROSPECTIVE STUDY OF MORBIDITY AND MORTALITY IN A CAPTIVE POPULATION OF CRYPTOSPORIDIUM-POSITIVE LOUISIANA PINE SNAKES (PITUOPHIS RUTHVENI).

The Louisiana pine snake (Pituophis ruthveni) is a diurnal colubrid species native to Louisiana and eastern Texas whose free-ranging populations have been declining over at least the past 30 yr. The creation and maintenance of sustainable captive breeding programs of P. ruthveni to restore native populations has also provided ample opportunity for research into this species and for P. ruthveni to serve as a research model for other colubrid snakes. However, no investigation into prevalent causes of morbidity and mortality in captive populations of this species has been described. A research population of P. ruthveni was maintained at Louisiana State University (LSU) for over 4 yr due to unsuitability for breeding after testing positive for Cryptosporidium serpentis. Since arrival at LSU, the snakes were under close veterinary surveillance. Complete postmortem examinations were performed on 12 snakes that died or were euthanized. The aim of this study was to further understanding of common factors influencing morbidity and mortality in captive P. ruthveni infected with C. serpentis, by retrospectively reviewing postmortem exam findings from the 12 deceased members of the population at LSU. A predominant finding across individuals included bacterial infections, which were responsible for major illness or death in 37.5% of the animals. Fifty percent of snakes tested positive for Cryptosporidium sp. based on PCR performed from postmortem samples; it was directly implicated as cause of death or morbidity in 83.3% of positive cases. Although infectious disease represented the most common pathologic postmortem finding, several noninfectious disease processes were identified, including gout, goiter, and neoplasia. These findings mirror those of other retrospective investigations of reptile collections at various institutions and highlight the need for appropriate emphasis on the identification, treatment, and prevention of infectious disease as part of routine veterinary care.

A rapid assessment tool for systemic treatment outcomes in colorectal cancer with deep bidirectional transformers.

e15567 Background: Retrospective investigations involving cancer treatment encounter the challenge of manually reviewing voluminous imaging reports to identify the best responses and the timing of disease progression. Here, we employed natural language processing, specifically deep bidirectional transformers, to automate the extraction of treatment response data. Methods: Data were sourced from the Yonsei Cancer Data Library database, focusing on patients with stage II-IV colorectal cancer at the Yonsei Cancer Center from Jan 1, 2010, to Dec 31, 2020. Imaging reports from 6,574 patients were gathered, amounting to 97,119 CT readings. Among these, 9,000 CT reports corresponding to 2,859 patients were randomly subjected to multilabel manual labeling by four radiology experts, based on the RECIST version 1.1 classification (CR/NED, PR, SD, PD). The pretrained BERT-base-uncased model was employed and fine-tuned for the downstream tasks of multilabel classification. 6,765 reports were used for training, while the remaining 1,000 reports were divided equally between the validation and test sets. Additionally, an algorithm for integrating and extracting treatment response data was also implemented. Clinical data were meticulously collected for 47 patients with stage IV early-onset colorectal cancer (EOCRC) receiving palliative first-line chemotherapy. The primary objective was to evaluate the model’s accuracy in predicting the timing of disease progression events within a ±30-day window. Secondary objectives focused on the model’s ability to identify the best response and its timing within a ±45-day window. Results: The evaluation of the classification accuracy across 1,000 individual CT reports, categorized as CR/NED (319), PR (86), SD (272), and PD (298), revealed accuracy with an AUROC of 0.956 and an F1 score of 0.823. All EOCRC patients were initially diagnosed with stage IV disease, and 45 out of 47 (95.7%) underwent metastasectomy either before initiating chemotherapy or during the first-line chemotherapy treatment. In clinical evaluation, the model demonstrated 72.3% (95% Confidence Interval [CI], 59.5-85.1) accuracy in predicting the day of disease progression within a ±30-day window. It achieved 55.3% (95% CI, 41.1-69.5) accuracy in predicting the best response category and its timing within ±45-days. Notably, the model was more accurate in predicting CR/NED at 72% compared to SD and PR, which had accuracy of 27.3% and 15.4%, respectively. Conclusions: Our model demonstrated high performance in classifying CT reports, which is expected to provide rapid insights into patient progress and improve clinical decision-making. However, the complexity involved in integrating and extracting data result in slight constraints in performance. This emphasizes the need for further research into multimodal large language models that can integrate a wider variety of clinical data.

The autologous serum skin test (ASST) predicts the response to anti-IgE treatment in Chronic Spontaneous Urticaria patients: a prospective study.

Background. Chronic spontaneous urticaria (CSU), characterized by recurrent itchy wheals and angioedema for > 6 weeks, is a quite common disease that may heavily impair the quality of life. Omalizumab, an anti-IgE mAb, has much improved the management of CSU but patients' response to the drug may vary and predictive markers are still largely missing. We investigated the predictive value of the autologous serum skin test (ASST) on omalizumab response. Methods. 15 patients with severe CSU eligible for omalizumab treatment were prospectively studied submitting them to ASST and to complete blood count, D-dimer, anti-thyroid peroxidase antibodies, and total IgE measurement before the start of the treatment. Results. 14/15 (93%) responded brilliantly to omalizumab at 3 months assessment. 7 responded in less than 1 month ("early responders") and 7 only after multiple administrations ("late responders"). Of 9 patients scoring positive on ASST, 7 (78%) were late, and 2 (22%) early responders to omalizumab (p = 0.021). Of 6 patients scoring negative on ASST, 5 were early omalizumab responders and 1 did not respond. The PPV and NPV of the ASST for a "late" response to omalizumab were 78% and 100%, respectively. Total IgE were significantly higher in early responders. Conclusions. Although larger prospective studies are needed to confirm these results, this study confirms previous retrospective investigations that the positive ASST appears to predict a slow response to omalizumab in CSU patients.

Prevalence of fibrinolytic alveolitis following extraction of impacted mandibular third molars: A systematic review and meta-analysis

Our research aims to assess the prevalence of alveolar osteitis (AO) following impacted mandibular third molar extractions and investigate the impact of potential moderating factors on this occurrence. Two independent reviewers conducted a comprehensive systematic literature search across Medline, Scopus, and Google Scholar databases. The pooled prevalence, accompanied by 95 % confidence intervals (CI), was calculated. Quality assessments, outlier and influential analyses were performed. Subgroup and meta-regression analysis were conducted in order the effect of categorical and continuous variables on the estimated prevalence to be investigated. Our meta-analysis included twenty-eight eligible studies, encompassing a total of 41,859 impacted mandibular third molar extractions. The overall prevalence of dry socket (DS) following impacted mandibular third molar extractions was estimated at 6.7 % (95 % CI 4.6–9.1 %), indicating considerable heterogeneity among the studies. No study was identified as critically influential, and meta-regression analysis did not pinpoint any potential sources of heterogeneity. This study highlights the imperative for future well-constructed prospective and retrospective investigations to deepen our understanding of the etiological nuances and refine management approaches for this prevalent postoperative complication.

Diagnostic Utility of EWSR1 in Clear Cell Odontogenic Carcinoma: A Systematic Review.

In the 2022, World Health Organisation classification of odontogenic tumours, the clear cell odontogenic carcinoma is designated as a malignant odontogenic tumour with high recurrence and aggressive behaviour. Deceptive behaviour in the context of a wide range of differentials presents a significant diagnostic problem. It is the fifth most commom type of malignant odontogenic tumor. A systematic assessment of published cases, case series, and retrospective investigations of diagnostic significance of EWSR1 gene in clear cell odontogenic carcinoma is presented to determine trends in presentation, diagnostic characteristics, treatment, and patient outcome. To locate papers reporting clear cell odontogenic carcinoma and EWSR1, extensive database searches were carried out. Demographics, tumour location, immunohistochemical and molecular tests, treatment, follow-up, and recurrence were the variables. 34 cases were detected; 52.9% (n = 18) of the cases were females. The average age was 62.5years, with a range of 43-82years. The average size ranged from 3.4 to 8cm. The mandibular body was the most common location, followed by the maxilla. Maximum immunohistochemistry positivity revealed by CK 19, CKAE1/3, EMA and p63. Most common gene fusion detected was EWSR1-ATF1 in 62.4% of cases contributing to its diagnostic attributes. Surgical treatment was used in 97% of cases. The average follow-up period was 30.3months, and recurrence was reported in 52.4% of the cases. CCOC can metastasize, and the prognosis is fair. This is first systematic review, where we have attempted to consolidate the mutational expression of EWSR1 in Clear cell odontogenic carcinoma. It is difficult to identify from other clear cell tumours of the head and neck region. It is crucial to distinguish it from other clear cell lesions because of its aggressiveness.

Why do people get burned? Qualitative analysis of the causes of burns in a large survey of burn survivors

BackgroundUnderstanding the national epidemiology of burns is necessary for effective planning of prevention and treatment services. However, epidemiological studies of burns have often focused on short-term and retrospective investigations of a specific group of burned patients in Iran. Therefore, we conduct a comprehensive study from August 2016 to October 2017, in the Burn Research Center of Iran University of Medical Sciences on approximately 1700 hospitalized burn patients at Motahari Hospital to identify the underlying causes of burns. In this study, an open-ended question was asked about how the burn occurred in the patients. The current study was designed and conducted for the qualitatively analyzing of the responses to this question, using the content analysis method, in order to maximize its use in policymaking and prevention. MethodsContent analysis of written responses to open-ended questions was done as a part of a large questionnaire survey. This survey was conducted by face-to-face interview at a national referral center for burn injuries. ResultsAnswers from 1595 patients were coded and the underlying causes of injury were categorized into three themes and 43 subthemes. These underlying causes were lack of knowledge and awareness, inappropriate equipment, and inevitable accidents. The underlying cause of lack of knowledge and awareness had the highest proportion in causing burns in both men and women. The most common subthemes in descending order included lack of skills, dangerous actions, improper location of hot liquids, individual mistakes, and improper use of flammable materials. The top five subthemes with the highest average percentage of burn in patients in descending order were deficiency of residential equipment, self-immolation, accidents, inappropriate location of flammable materials, and unsafe kitchen appliances. ConclusionThe focus of prevention programs on educating and increasing awareness of individuals, preferably women, is suggested. Educational programs, tailored to occupational standards and workplace and household equipment, are recommended for men in work environments.

Revolutionizing Medical Practice: The Impact of Artificial Intelligence (AI) on Healthcare

The twenty-first century has witnessed significant advancements in informatics, reshaping our understanding of data processing and accessibility. Artificial intelligence (AI), encompassing techniques such as machine learning (ML), deep learning (DP), and neural networks (NN), is poised to revolutionize medicine. AI holds the capability of analyzing vast amounts of data, extracting meaningful insights, and making accurate predictions, thereby empowering industries to make informed decisions, drive innovation, and enhance efficiency. The landscape of medical AI has evolved significantly, demonstrating expert-level disease detection from medical images and promising breakthroughs across various industries. AI revolutionizes medical practice by leveraging advanced algorithms and machine learning capabilities to improve diagnostics, treatment planning, and overall patient care. However, the deployment of medical AI systems in regular clinical practice still needs to be tapped, presenting complex ethical, technical, and human-centered challenges that must be addressed for successful implementation. While AI algorithms have shown efficacy in retrospective medical investigations, their translation into practical medical settings has been limited, raising concerns about their usability and interaction with healthcare professionals. Moreover, the representativeness of retrospective datasets in real-world medical practice is subject to filtering and cleaning biases. Integrating AI into clinical medicine holds great promise for transforming healthcare delivery, improving patient care, and revolutionizing aspects such as diagnosis, treatment planning, drug discovery, personalized treatment, and medical imaging. With advanced algorithms and machine learning capabilities, AI and robotics in Healthcare can analyze large volumes of medical data, extract meaningful insights, and provide accurate predictions, empowering healthcare professionals to make informed decisions and optimize resource allocation. The availability of extensive clinical, genomics, and digital imaging data, coupled with investments from healthcare institutions and technology giants, underscores the potential of AI in healthcare. This review article explores AI's powerful potential to revolutionize healthcare delivery across multiple domains, emphasizing the need to overcome challenges and harness its transformative capabilities in clinical practice.

A Dual Pharmacological Strategy against COVID-19: The Therapeutic Potential of Metformin and Atorvastatin.

Metformin (MET) and atorvastatin (ATO) are promising treatments for COVID-19. This review explores the potential of MET and ATO, commonly prescribed for diabetes and dyslipidemia, respectively, as versatile medicines against SARS-CoV-2. Due to their immunomodulatory and antiviral capabilities, as well as their cost-effectiveness and ubiquitous availability, they are highly suitable options for treating the virus. MET's effect extends beyond managing blood sugar, impacting pathways that can potentially decrease the severity and fatality rates linked with COVID-19. It can partially block mitochondrial complex I and stimulate AMPK, which indicates that it can be used more widely in managing viral infections. ATO, however, impacts cholesterol metabolism, a crucial element of the viral replicative cycle, and demonstrates anti-inflammatory characteristics that could modulate intense immune reactions in individuals with COVID-19. Retrospective investigations and clinical trials show decreased hospitalizations, severity, and mortality rates in patients receiving these medications. Nevertheless, the journey from observing something to applying it in a therapeutic setting is intricate, and the inherent diversity of the data necessitates carefully executed, forward-looking clinical trials. This review highlights the requirement for efficacious, easily obtainable, and secure COVID-19 therapeutics and identifies MET and ATO as promising treatments in this worldwide health emergency.

Effect of Surface Topography on the Primary Stability of Miniscrew Implants in Orthodontics—A Systematic Review and Meta-Analysis

ABSTRACT This present study has the purpose of determining how surface topography of implants affects the initial stability of miniscrew implants (MSIs). Electronic databases like PubMed Central, Scopus, Web of Science, Embase, and Cochrane Library, as well as reference lists, were thoroughly searched up until September 2022. Clinical trials involving individuals who got anchorage through mini-implants, along with information on categories of mini-implants dimension, shape, thread design, and insertion site, were required as part of the eligibility criteria. Primary and secondary stability were also assessed. We carried out selection process for the study, extraction of data, quality assessment, and a meta-analysis. The qualitative synthesis included 10 papers: three randomized, four prospective, and four retrospective clinical investigations. The results of this meta-analysis demonstrate that the clinical state of MIs is controlled by their geometrical surface qualities, which are also influenced by their shape and thread design. According to the evidence this meta-analysis produced, this circumstance exists. The duration of the follow-up period and MI success rates did not correlate with one another.

Establishing a trigger tool based on global trigger tools to identify adverse drug events in obstetric inpatients in China

BackgroundPregnant women belong to the special population of drug therapy, and their physiological state, pharmacokinetics and pharmacodynamics are significantly different from the general population. Drug safety during pregnancy involves two generations, which is a hot issue widely concerned in the whole society. Global Trigger Tool (GTT) of the Institute for Healthcare Improvement (IHI) has been wildly used as a patient safety measurement strategy by several institutions and national programs, and the effectiveness had been demonstrated. But only one study reports the use of GTT in obstetric delivery until now. The aim of the study is to establish triggers detecting adverse drug events (ADEs) suitable for obstetric inpatients on the basis of the GTT, to examine the performance of the obstetric triggers in detecting ADEs experienced by obstetric units compared with the spontaneous reporting system and GTT, and to assess the utility and value of the obstetric trigger tool in identifying ADEs of obstetric inpatients.MethodsBased on a literature review searched in PubMed and CNKI from January of 1997 to October of 2023, retrospective local obstetric ADEs investigations, relevant obstetric guidelines and the common adverse reactions of obstetric therapeutic drugs were involved to establish the initial obstetric triggers. According to the Delphi method, two rounds of expert questionnaire survey were conducted among 16 obstetric and neonatological physicians and pharmacists until an agreement was reached. A retrospective study was conducted to identity ADEs in 300 obstetric inpatient records at the Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital from June 1 to September 30, 2018. Two trained junior pharmacists analyzed the first eligible records independently, and the included records reviewed by trained pharmacist and physician to identify ADEs. Sensitivity and specificity of the established obstetric triggers were assessed by the number of ADEs/100 patients and positive predictive value with the spontaneous reporting system (SRS) and GTT. Excel 2010 and SPSS22 were used for data analysis.ResultsThrough two rounds of expert investigation, 39 preliminary triggers were established that comprised four modules (12 laboratory tests, 9 medications, 14 symptoms, and 4 outcomes). A total of 300 medical records were reviewed through the obstetric triggers, of which 48 cases of ADEs were detected, with an incidence of ADEs of 16%. Among the 39 obstetric triggers, 22 (56.41%) were positive and 11 of them detected ADEs. The positive predictive value (PPV) was 36.36%, and the number of ADEs/100 patients was 16.33 (95% CI, 4.19–17.81). The ADE detection rate, positive trigger rate, and PPV for the obstetric triggers were significantly augmented, confirming that the obstetric triggers were more specific and sensitive than SRS and GTT.ConclusionThe obstetric triggers were proven to be sensitive and specific in the active monitoring of ADE for obstetric inpatients, which might serve as a reference for ADE detection of obstetric inpatients at medical institutions.

Effects of Health Records Management on Health Service Delivery: A case study of the Prestea Government Hospital. (PGH)

Background: The most crucial instrument when discussing patient healthcare are medical records. Both their management and their utilization are crucial for patient care management. Ghana has used many medical records management systems to aid in healthcare development. Retrospective and epidemiological investigations are slowed down by poor data quality, which inhibits research. As expectations have grown, more initiatives to capture and save patient records electronically are planned. Aim: The purpose of the study is to investigate the perception of health worker about the EHRs use and impact on service delivery. Materials and methods: The study's focus is on the health workers at Prestea Government Hospital (PGH), which include nurses, physicians, biotechnologists, Health Information Manager, pharmacists, midwives, etc. A sample size of 100 people from the intended audience was used. Standardized questionnaires were self-completed by respondent. The Completed questionnaires were given numbers to protect participants anonymity. Participants received sufficient information regarding their right to decline study participation and to withdraw at any time without repercussions. Data was entered into Excel and exported to SPSS for analysis. Descriptive and inferential analysis was performed and the outcomes were shown as tables, graphs, and figures. Results: In all, out of 100 respondents, 35% of them were males and 65% were women. There were a lot of female replies since many of the respondents were nurses. Medical laboratory technicians comprised the smallest proportion of the workforce (5%) of all occupational groups. Prestea Government Hospital survey respondents overwhelmingly concur that electronic health records (EHRs) aid in the delivery of treatment. According to a survey, medical practitioners think the facility's EHR has all of the forms that are utilized there. The idea that the facility's EHRs help with data collection is accepted by few people. Medical professionals believe that the use of EHRs makes it simple to obtain historical patient data. This is so that all information may be easily accessed while undergoing medical treatment and kept securely saved. The system features alarms that play when erroneous data is entered. Although the system features pre-programmed commands that allow for uninterrupted navigation, there are frequently disruptions due to power fluctuations. Conclusion: Access to patients' medical records via an electronic health information system platform is crucial for making medical decisions that will result in effective care delivery in healthcare facilities, lower the risk of treatment errors, decrease patient waiting times, and lower the number of medical errors, a study has found.

Addressing researcher fraud: retrospective, real-time, and preventive strategies-including legal points and data management that prevents fraud.

Researcher fraud is often easy and enticing in academic research, with little risk of detection. Cases of extensive fraud continue to occur. The amount of fraud that goes undetected is unknown and may be substantial. Three strategies for addressing researcher fraud are (a) retrospective investigations after allegations of fraud have been made, (b) sting operations that provide conclusive evidence of fraud as it occurs, and (c) data management practices that prevent the occurrence of fraud. Institutional and regulatory efforts to address researcher fraud have focused almost exclusively on the retrospective strategy. The retrospective approach is subject to controversy due to the limitations of post-hoc evidence in science, the difficulty in establishing who actually committed the fraud in some cases, the application of a legal standard of evidence that is much lower than the usual standards of evidence in science, and the lack of legal expertise by scientists investigating fraud. The retrospective strategy may be reliably effective primarily in cases of extensive, careless fraud. Sting operations can overcome these limitations and controversies, but are not feasible in many situations. Data management practices that are effective at preventing researcher fraud and unintentional errors are well-established in clinical trials regulated by government agencies, but appear to be largely unknown or unimplemented in most academic research. Established data management practices include: archiving secure copies of the raw data, audit trails, restricted access to the data and data collection processes, software validation, quality control checks, blinding, preregistration of data processing and analysis programs, and research audits that directly address fraud. Current discussions about data management in academic research focus on sharing data with little attention to practices that prevent intentional and unintentional errors. A designation or badge such as error-controlled data management could be established to indicate research that was conducted with data management practices that effectively address intentional and unintentional errors.

Intra-Cranial Hematoma as a First Manifestation of Brain Tumours, a Meta-Analysis

Introduction: Intracerebral Hematoma (ICH), conventionally associated with vascular causes, is increasingly recognized as the initial presentation of underlying brain tumors. This Narrative review aims to synthesize current literature on the incidence, clinical features, diagnostic challenges, and outcomes associated with ICH as the primary manifestation of brain tumors. Methods: A systematic search across PubMed, Embase, and Cochrane Library databases yielded studies meeting inclusion criteria. These encompassed prospective and retrospective observational studies, case-control investigations, and case series reporting instances where ICH was the initial sign of an underlying brain tumor. Results: Analysis of the selected studies revealed variable incidences of ICH as the first manifestation of brain tumors, with differences across tumor types and patient demographics. Clinical presentations mimicked primary vascular causes, posing diagnostic challenges. Common tumor types included with varying intracranial locations. Treatment strategies ranged from surgery to adjuvant therapies, and outcomes were heterogeneous, influenced by tumor histology, location, and patient characteristics. Discussion: This review highlights the significance of recognizing ICH as an initial sign of brain tumors, emphasizing the need for refined diagnostic approaches and enhanced imaging modalities. Challenges in timely identification underscore the importance of heightened clinical suspicion. The variable outcomes suggest the necessity of tailoring treatment strategies based on tumor characteristics and patient factors, paving the way for future research to optimize interventions in ICH associated with brain tumors.

Comparing the survival rates of patients with stage IIIC endometrial cancer undergoing sandwich therapy to those undergoing sequential chemotherapy and radiotherapy: a meta-analysis.

The use of additional treatment after surgery for stage IIIC endometrial cancer (EC) according to the Federation of Gynecology and Obstetrics (FIGO) is still a topic of discussion. This meta-analysis examined the effects of sandwich treatment and sequential treatment on the survival of individuals diagnosed with stage IIIC EC. We examined the literature from various databases regarding the overall survival (OS) and adverse effects of the two additional therapies following surgery in individuals diagnosed with stage IIIC EC. Revman 5.4.1 was utilized to combine hazard ratios (HR) and their corresponding 95% confidence intervals (95% CI) for OS and toxicities. The findings comprised of five retrospective investigations involving a combined total of 800 individuals. The patients who underwent sandwich treatment did not demonstrate a notable improvement in survival rates over a period of 3years. Upon eliminating the impact of extensive samples, it was discovered that sandwich therapy exhibited a superior 5-year overall survival compared to patients receiving sequential therapy. The effectiveness of sandwich therapy was superior to sequential therapy in terms of a 3-year OS for non-endometrioid histology, although the outcome did not reach statistical significance. The toxicities of both treatments were similar. In terms of long-term survival, sandwich therapy was found to be more advantageous than sequential therapy for patients with stage IIIC EC, with no significant disparity observed in the 3-year OS and toxicities between the two treatments. Sandwich therapy exhibited a tendency towards improved effectiveness in patients with histology other than endometrioid.

Profiling a Low Emissivity Glass Coating with ToF‐SIMS and Machine Learning

AbstractCharacterization of multilayer coatings in 3D presents many challenges, as composition can change by area and by depth. Compositional characteristics of the interior of multilayer coatings emerge during analysis, so are frequently discovered only through exacting retrospective investigations. Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) can be used to elucidate such complex systems; however, data analysis is a challenge. In this work a detail presentation is done of 3D chemical characterization of a low emissivity (low‐E) double silver coating on glass using ToF‐SIMS and machine learning. An unsupervised machine learning technique, the self‐organizing map with relational perspective mapping, is used to visualize the chemical similarity between different layers of the low‐E film. Repeating layers are easily identified at the single‐voxel level, based on their entire mass spectra, and are classified as chemically indistinguishable. All major film components are identified, including the use of SnO2 as a dielectric, ZnO seeding layers, TiOx blocking layers, a Zn base layer, and a TiOx topcoat. The thin optically active silver layers are examined in detail, demonstrating subtle chemical changes with depth. This technique provides excellent insight into manufacturing processes and production challenges and has excellent potential in forensic applications.