Tag: pubmed

Otolaryngol Head Neck Surg. 2023 Aug 2. doi: 10.1002/ohn.465. Online ahead of print.

ABSTRACT

OBJECTIVE: Chat Generative Pretrained Transformer (ChatGPT) is the newest iteration of OpenAI’s generative artificial intelligence (AI) with the potential to influence many facets of life, including health care. This study sought to assess ChatGPT’s capabilities as a source of medical knowledge, using Google Search as a comparison.

STUDY DESIGN: Cross-sectional analysis.

SETTING: Online using ChatGPT, Google Seach, and Clinical Practice Guidelines (CPG).

METHODS: CPG Plain Language Summaries for 6 conditions were obtained. Questions relevant to specific conditions were developed and input into ChatGPT and Google Search. All questions were written from the patient perspective and sought (1) general medical knowledge or (2) medical recommendations, with varying levels of acuity (urgent or emergent vs routine clinical scenarios). Two blinded reviewers scored all passages and compared results from ChatGPT and Google Search, using the Patient Education Material Assessment Tool (PEMAT-P) as the primary outcome. Additional customized questions were developed that assessed the medical content of the passages.

RESULTS: The overall average PEMAT-P score for medical advice was 68.2% (standard deviation [SD]: 4.4) for ChatGPT and 89.4% (SD: 5.9) for Google Search (p < .001). There was a statistically significant difference in the PEMAT-P score by source (p < .001) but not by urgency of the clinical situation (p = .613). ChatGPT scored significantly higher than Google Search (87% vs 78%, p = .012) for patient education questions.

CONCLUSION: ChatGPT fared better than Google Search when offering general medical knowledge, but it scored worse when providing medical recommendations. Health care providers should strive to understand the potential benefits and ramifications of generative AI to guide patients appropriately.

PMID:37529853 | DOI:10.1002/ohn.465

Neuroradiol J. 2023 Aug 2:19714009231193158. doi: 10.1177/19714009231193158. Online ahead of print.

ABSTRACT

The simplest approach to convey the results of scientific analysis, which can include complex comparisons, is typically through the use of visual items, including figures and plots. These statistical plots play a critical role in scientific studies, making data more accessible, engaging, and informative. A growing number of visual representations have been utilized recently to graphically display the results of oncologic imaging, including radiomic and radiogenomic studies. Here, we review the applications, distinct properties, benefits, and drawbacks of various statistical plots. Furthermore, we provide neuroradiologists with a comprehensive understanding of how to use these plots to effectively communicate analytical results based on imaging data.

PMID:37529843 | DOI:10.1177/19714009231193158

Cureus. 2023 Jul 1;15(7):e41254. doi: 10.7759/cureus.41254. eCollection 2023 Jul.

ABSTRACT

Background Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease characterized by various clinical manifestations. Despite efforts to improve outcomes, mortality rates remain high, and certain disparities, including gender, may influence prognosis and mortality rates in SLE. This study aims to examine the gender disparities in outcomes of SLE hospitalizations in the US. Methods We conducted a retrospective analysis of the Nationwide Inpatient Sample (NIS) database between 2016 and 2020. The NIS database is the largest publicly available all-payer database for inpatient care in the United States, representing approximately 20% of all hospitalizations nationwide. We selected every other year during the study period and included hospitalizations of adult patients (≥18 years old) with a primary or secondary diagnosis of SLE using International Classification of Diseases, Tenth Revision (ICD-10) codes. The control population consisted of all adult hospitalizations. Multivariate logistic regression was used to estimate the strength of the association between gender and primary and secondary outcomes. The regression models were adjusted for various factors, including age, race, median household income based on patients’ zip codes, Charlson comorbidity index score, insurance status, hospital location, region, bed size, and teaching status. To ensure comparability across the years, revised trend weights were applied as the healthcare cost and use project website recommends. Stata version 17 (StataCorp LLC, TX, USA) was used for the statistical analyses, and a two-sided P-value of less than 0.05 was considered statistically significant. Results Among the 42,875 SLE hospitalizations analyzed, women accounted for a significantly higher proportion (86.4%) compared to men (13.6%). The age distribution varied, with the majority of female admissions falling within the 30- to 60-year age range, while most male admissions fell within the 15- to 30-year age category. Racial composition showed a slightly higher percentage of White Americans in the male cohort compared to the female cohort. Notably, more Black females were admitted for SLE compared to Black males. Male SLE patients had a higher burden of comorbidities and were more likely to have Medicare and private insurance, while a higher percentage of women were uninsured. The mortality rate during the index hospitalization was slightly higher for men (1.3%) compared to women (1.1%), but after adjusting for various factors, there was no statistically significant gender disparity in the likelihood of mortality (adjusted odds ratio (aOR): 1.027; 95% confidence interval (CI): 0.570-1.852; P=0.929). Men had longer hospital stays and incurred higher average hospital costs compared to women (mean length of stay (LOS): seven days vs. six days; $79,751 ± $5,954 vs. $70,405 ± $1,618 respectively). Female SLE hospitalizations were associated with a higher likelihood of delirium, psychosis, and seizures while showing lower odds of hematological and renal diseases compared to men. Conclusion While women constitute the majority of SLE hospitalizations, men with SLE tend to have a higher burden of comorbidities and are more likely to have Medicare and private insurance. Additionally, men had longer hospital stays and incurred higher average hospital costs. However, there was no significant gender disparity in the likelihood of mortality after accounting for various factors.

PMID:37529818 | PMC:PMC10389681 | DOI:10.7759/cureus.41254

Cureus. 2023 Jul 1;15(7):e41260. doi: 10.7759/cureus.41260. eCollection 2023 Jul.

ABSTRACT

This study evaluated the feasibility of using artificial intelligence (AI) segmentation software for volume-modulated arc therapy (VMAT) prostate planning in conjunction with knowledge-based planning to facilitate a fully automated workflow. Two commercially available AI software programs, Radformation AutoContour (Radformation, New York, NY) and Siemens AI-Rad Companion (Siemens Healthineers, Malvern, PA) were used to auto-segment the rectum, bladder, femoral heads, and bowel bag on 30 retrospective clinical cases (10 intact prostate, 10 prostate bed, and 10 prostate and lymph node). Physician-segmented target volumes were transferred to AI structure sets. In-house RapidPlan models were used to generate plans using the original, physician-segmented structure sets as well as Radformation and Siemens AI-generated structure sets. Thus, there were three plans for each of the 30 cases, totaling 90 plans. Following RapidPlan optimization, planning target volume (PTV) coverage was set to 95%. Then, the plans optimized using AI structures were recalculated on the physician structure set with fixed monitor units. In this way, physician contours were used as the gold standard for identifying any clinically relevant differences in dose distributions. One-way analysis of variation (ANOVA) was used for statistical analysis. No statistically significant differences were observed across the three sets of plans for intact prostate, prostate bed, or prostate and lymph nodes. The results indicate that an automated volumetric modulated arc therapy (VMAT) prostate planning workflow can consistently achieve high plan quality. However, our results also show that small but consistent differences in contouring preferences may lead to subtle differences in planning results. Therefore, the clinical implementation of auto-contouring should be carefully validated.

PMID:37529805 | PMC:PMC10389787 | DOI:10.7759/cureus.41260

Turk J Emerg Med. 2023 Jun 26;23(3):162-168. doi: 10.4103/tjem.tjem_8_23. eCollection 2023 Jul-Sep.

ABSTRACT

OBJECTIVE: The aim was to determine the effects of digital game play on children’s pain, fear, and anxiety levels during suturing.

METHODS: Data were obtained from 84 children between the ages of 8 and 17 years at the pediatric emergency department between January 16 and March 19, 2020, using the Socio-Demographic and Clinical Characteristics Form, the Wong-Baker Faces Pain Rating Scale (WBFPS), the Visual Analogue Scale (VAS), the Fear of Medical Procedures Scale (FMPS), and the State-Trait Anxiety Inventory for Children (STAI-CH). A four-block randomization system was used. The study group (n = 42) played digital games during the suturing procedure, unlike the control group (n = 42). Ethical permissions were obtained from the ethical committee, hospital, and families.

RESULTS: Before the suturing procedure, there was no statistically significant difference between the groups’ mean scores. The intervention group was found to have statistically significantly lower WBFPS and VAS pain scores than the control group during the suturing procedure, and after the procedure, statistically significantly lower WBFPS, VAS, FMPS, and STAI-CH mean scores than the control group.

CONCLUSIONS: The digital game-playing approach applied before and during the suture procedure was found to be effective in reducing children’s pain, fear, and anxiety levels.

PMID:37529788 | PMC:PMC10389094 | DOI:10.4103/tjem.tjem_8_23

Front Genet. 2023 Jul 17;14:1198821. doi: 10.3389/fgene.2023.1198821. eCollection 2023.

ABSTRACT

The amount of Insulin Growth Factor 2 (IGF2) controls the rate of embryonal and postnatal growth. The IGF2 and adjacent H19 are the imprinted genes of the telomeric cluster in the 11p15 chromosomal region regulated by differentially methylated regions (DMRs) or imprinting centers (ICs): H19/IGF2:IG-DMR (IC1). Dysregulation due to IC1 Loss-of-Methylation (LoM) or Gain-of-Methyaltion (GoM) causes Silver-Russell syndrome (SRS) or Beckwith-Wiedemann syndrome (BWS) disorders associated with growth retardation or overgrowth, respectively. Specific features define each of the two syndromes, but isolated asymmetry is a common cardinal feature, which is considered sufficient for a diagnosis in the BWS spectrum. Here, we report the case of a girl with right body asymmetry, which suggested BWS spectrum. Later, BWS/SRS molecular analysis identified IC1_LoM revealing the discrepant diagnosis of SRS. A clinical re-evaluation identified a relative macrocephaly and previously unidentified growth rate at lower limits of normal at birth, feeding difficulties, and asymmetry. Interestingly, and never previously described in IC1_LoM SRS patients, since the age of 16, she has developed hand-writer’s cramps, depression, and bipolar disorder. Trio-WES identified a VPS16 heterozygous variant [NM_022575.4:c.2185C>G:p.Leu729Val] inherited from her healthy mother. VPS16 is involved in the endolysosomal system, and its dysregulation is linked to autosomal dominant dystonia with incomplete penetrance and variable expressivity. IGF2 involvement in the lysosomal pathway led us to speculate that the neurological phenotype of the proband might be triggered by the concurrent IGF2 deficit and VPS16 alteration.

PMID:37529781 | PMC:PMC10387531 | DOI:10.3389/fgene.2023.1198821

Front Genet. 2023 Jul 17;14:1161047. doi: 10.3389/fgene.2023.1161047. eCollection 2023.

ABSTRACT

Drug-induced liver injury (DILI) is an adverse hepatic drug reaction that can potentially lead to life-threatening liver failure. Previously published work in the scientific literature on DILI has provided valuable insights for the understanding of hepatotoxicity as well as drug development. However, the manual search of scientific literature in PubMed is laborious and time-consuming. Natural language processing (NLP) techniques along with artificial intelligence/machine learning approaches may allow for automatic processing in identifying DILI-related literature, but useful methods are yet to be demonstrated. To address this issue, we have developed an integrated NLP/machine learning classification model to identify DILI-related literature using only paper titles and abstracts. For prediction modeling, we used 14,203 publications provided by the Critical Assessment of Massive Data Analysis (CAMDA) challenge, employing word vectorization techniques in NLP in conjunction with machine learning methods. Classification modeling was performed using 2/3 of the data for training and the remainder for test in internal validation. The best performance was achieved using a linear support vector machine (SVM) model on the combined vectors derived from term frequency-inverse document frequency (TF-IDF) and Word2Vec, resulting in an accuracy of 95.0% and an F1-score of 95.0%. The final SVM model constructed from all 14,203 publications was tested on independent datasets, resulting in accuracies of 92.5%, 96.3%, and 98.3%, and F1-scores of 93.5%, 86.1%, and 75.6% for three test sets (T1-T3). Furthermore, the SVM model was tested on four external validation sets (V1-V4), resulting in accuracies of 92.0%, 96.2%, 98.3%, and 93.1%, and F1-scores of 92.4%, 82.9%, 75.0%, and 93.3%.

PMID:37529777 | PMC:PMC10390074 | DOI:10.3389/fgene.2023.1161047

Ther Adv Drug Saf. 2023 Jul 29;14:20420986231188842. doi: 10.1177/20420986231188842. eCollection 2023.

ABSTRACT

BACKGROUND: Adverse drug reactions (ADRs) contribute to the burden of disease globally and of particular concern are ADR-related hospital admissions.

OBJECTIVES: This study sought to determine the burden, characteristics, contributing factors and patient outcomes of ADRs that were the primary diagnosis linked to hospital admission among inpatients in Uganda.

DESIGN: We conducted a cross-sectional secondary analysis of data from a prospective cohort study of adult inpatients aged 18 years and older at Uganda’s Mulago National Referral Hospital from November 2013 to April 2014.

METHODS: We reviewed clinical charts to identify inpatients with an ADR as one of the admitting diagnoses and, if so, whether or not the hospital admission was primarily attributed to the ADR. Logistic regression was used to determine factors associated with hospital admissions primarily attributed to ADRs.

RESULTS: Among 762 inpatients, 14% had ADRs at hospital admission and 7% were primarily hospitalized due to ADRs. A total of 235 ADRs occurred among all inpatients and 57% of the ADRs were the primary diagnosis linked to hospital admission. The majority of ADRs occurred in people living with HIV and were attributed to antiretroviral drugs. HIV infection [aOR (adjusted odds ratio) = 2.97, 95% confidence interval (CI): 1.30-6.77], use of antiretroviral therapy (aOR = 5.46, 95% CI: 2.56-11.68), self-medication (aOR = 2.27, 95% CI: 1.14-4.55) and higher number of drugs used (aOR = 1.13, 95% CI: 1.01-1.26) were independently associated with hospital admissions attributed to ADRs.

CONCLUSION: Antiretroviral drugs were often implicated in ADR-related hospital admissions. HIV infection (whether managed by antiretroviral therapy or not), self-medication and high pill burden were associated with hospital admissions attributable to ADRs. The high HIV burden in Sub-Saharan Africa increases the risk of ADR-related hospitalization implying the need for emphasis on early detection, monitoring and appropriate management of ADRs associated with hospital admission in people living with HIV.

PMID:37529762 | PMC:PMC10387768 | DOI:10.1177/20420986231188842

Womens Health Rep (New Rochelle). 2023 Jul 28;4(1):387-399. doi: 10.1089/whr.2023.0022. eCollection 2023.

ABSTRACT

BACKGROUND: Lower urinary tract symptoms (LUTS) are prevalent across women’s life course. Evidence shows toileting behaviors (TBs) and urinary urge cues are related to LUTS. It is unknown when women start using these behaviors and responding to urinary cues.

METHODS: An online survey was administered to 338 women, 65 years of age and older, to assess the age of onset for 20 TBs from the Toileting Behaviors-Women’s Elimination Behavior (TB-WEB) questionnaire, 10 urinary urge cues from the Urinary Cues Questionnaire, and urinary urgency and leakage items from the International Consultation on Incontinence Questionnaire-Overactive Bladder (ICIQ-OAB) Short Form. Descriptive statistics were reported for each TB and urinary cue. A timeline was generated with the average earliest age of onsets for each type of TB, urinary cues, and urinary urgency and leakage symptoms.

RESULTS: Place preference, delayed voiding, and hovering over toilets away from home were reported to have the earliest ages of onset. Urinary urge cues, premature voiding, and straining to void tended to start after 45 years of age, as did the symptoms of urinary urgency and leakage. The timeline indicated that the earliest place preference and position preference TBs started before 20 years of age.

CONCLUSION: Some TBs begin early in life and persist into old age, while other TBs and urinary cues begin later. Bladder health promotion may depend on intervening at specific times in the life course to alter TBs and responses, and potentially making environmental changes.

PMID:37529759 | PMC:PMC10389249 | DOI:10.1089/whr.2023.0022

Front Sociol. 2023 Jul 17;8:1141616. doi: 10.3389/fsoc.2023.1141616. eCollection 2023.

ABSTRACT

Promoting technology transfer is an important strategic measure for China to promote industrial innovation. However, there is little research exploring the influence of technology transfer on the green innovation efficiency (GIE) of China’s high-tech industry (HTI). From the perspective of process, green innovation in HTI is a continuous three-stage system including research and development (R&D), commercialization, and diffusion. Therefore, we measure the GIE of China’s HTI by using a three-stage network data envelopment analysis (NDEA) model considering environmental pollution and establish a series of regression models to investigate the role of the two main ways of technology transfer, domestic technology acquisition (DTA) and foreign technology introduction (FTI), in improving the GIE of HTI. The results show that the average GIE of China’s HTI is 0.7727 from 2011 to 2020. Except for Jiangsu, Guangdong, Qinghai, and Xinjiang, green innovation in HTI in other provinces in China is inefficient. DTA has significantly promoted GIE in HTI. FTI has a positive impact on the GIE of HTI but is not statistically significant. The robustness test confirmed these results. This study is helpful to understand the differences between the effects of DTA and FTI on the GIE of China’s HTI, to provide a basis for adjusting technology transfer policies.

PMID:37529708 | PMC:PMC10388581 | DOI:10.3389/fsoc.2023.1141616