Identification Of Risk Factors Research Articles

AI-powered fertility assessment tool

The integration of artificial intelligence (AI) into fertility assessment and treatment presents a promising solution to the pervasive issue of infertility, offering individuals and couples personalized insights and recommendations on their reproductive health journey. By harnessing machine learning algorithms, an AI-powered fertility assessment tool analyzes diverse datasets encompassing demographic and clinical variables to generate comprehensive fertility profiles. These profiles provide predictions of fertility potential, identification of risk factors for infertility, and tailored recommendations for lifestyle modifications or medical interventions. The tool's adaptability and capacity for continuous improvement through user feedback and updated research ensure the relevance and effectiveness of its recommendations, while stringent privacy measures safeguard sensitive information. Preliminary testing demonstrates high accuracy and user satisfaction, highlighting the tool's potential to transform reproductive healthcare by streamlining assessments, reducing diagnostic uncertainties, and facilitating early interventions. However, the responsible implementation of AI-powered tools requires careful consideration of ethical, regulatory, and societal implications to ensure equitable access and mitigate algorithmic biases. Overall, AI-powered fertility assessment tools signify a significant advancement in reproductive medicine, offering hope and empowerment to individuals and couples navigating the complexities of fertility challenges.

The association between HLA-B variants and amoxicillin-induced severe cutaneous adverse reactions in Chinese han population

BackgroundAmoxicillin (AMX) is among the most prescribed and the best tolerated antimicrobials worldwide. However, it can occasionally trigger severe cutaneous adverse reactions (SCAR) with a significant morbidity and mortality. The genetic factors that may be relevant to AMX-induced SCAR (AMX-SCAR) remain unclear. Identification of the genetic risk factor may prevent patients from the risk of AMX exposure and resume therapy with other falsely implicated drugs.MethodologyFour patients with AMX-SCAR, 1,000 population control and 100 AMX-tolerant individuals were enrolled in this study. Both exome-wide and HLA-based association studies were conducted. Molecular docking analysis was employed to simulate the interactions between AMX and risk HLA proteins.ResultsCompared with AMX-tolerant controls, a significant association of HLA-B*15:01 with AMX-SCAR was validated [odds ratio (OR) = 22.9, 95% confidence interval (CI): 1.68–1275.67; p = 7.34 × 10−3]. Moreover, 75% carriers of HLA-B*15:01 in four patients with AMX-SCAR, and the carrier frequency of 10.7% in 1,000 control individuals and 11.0% in 100 AMX-tolerant controls, respectively. Within HLA-B protein, the S140 present in all cases and demonstrated the strongest association with AMX-SCAR [OR = 53.5, p = 5.18 × 10−4]. Molecular docking results also confirmed the interaction between AMX and S140 of the HLA-B protein, thus eliminating the false-positive results during in association analysis.ConclusionOur findings suggest that genetic susceptibility may be involved in the development of AMX-SCAR in Han Chinese. However, whether the HLA-B variants observed in this study can be used as an effective genetic marker of AMX-induced SCAR still needs to be further explored in larger cohort studies and other ethnic populations.

Current concepts in the management of non-cirrhotic non-malignant portal vein thrombosis

Non-cirrhotic non-malignant portal vein thrombosis (NCPVT) is an uncommon condition characterised by thrombosis of the portal vein, with or without extension into other mesenteric veins, in the absence of cirrhosis or intra-abdominal malignancy. Complications can include intestinal infarction, variceal bleeding and portal biliopathy. In this article, we address current concepts in the management of NCPVT including identification of risk factors, classification and treatment, and review the latest evidence on medical and interventional management options.

Development and validation of a machine learning-based prediction model for sudden cardiac death in the general population: insights from the community cardiovascular cohort

Abstract Background/Introduction Accurately predicting and managing the risk of sudden cardiac death (SCD) in the general population is a formidable challenge. Purpose This study aimed to develop and validate a machine learning (ML)-based prediction model for SCD using data from the Community Cardiovascular Cohort (CCCC) in Taiwan. Methods A community-based cohort study was used for model construction . Four ML algorithms, including extreme gradient boosting (XGBoost), random forests (RF), logistic regression, and deep neural network (DNN), underwent meticulous evaluation. Performance assessment encompassed receiver operating characteristic (ROC) curves, area under the curves (AUC), and accuracy metrics. Significant risk factors were identified through feature importance analysis. Results We employed a random partitioning strategy, allocating 1744 participants (55%) to the training dataset, 952 participants (30%) to the test dataset, and 476 participants (15%) to the validation dataset. In the data training stage, the XGBoost algorithm demonstrated outstanding prediction performance for SCD (AUC: 1.000); In the validation stage, the XGBoost algorithm demonstrated good prediction performance for SCD prediction (AUC: 0.791, 95%CI: 0.617-0.964; Accuracy: 0.971). Using XGBoost-generated predicted probabilities (P(XGB)), we identified individuals with P(XGB) ≥ 0.5 (Group 1) who displayed significantly higher SCD risk (HR 32.0; 95% CI: 9.29-109.9) compared to those with P(XGB) < 0.5 (Group 0). Conclusions Our study demonstrates the effectiveness of ML algorithms, particularly XGBoost, in predicting event of SCD in the general population. The identification of these pivotal risk factors holds profound implications, empowering the identification of high-risk individuals and facilitating the implementation of precisely tailored preventive strategies.Figure 1:KM sruvival curveFigure 2:Feature importance analysis

An integrated model combining BERT and tree-augmented naive Bayes for analyzing risk factors of construction accident

PurposeLearning from past construction accident reports is critical to reducing their occurrence. Digital technology provides feasibility for extracting risk factors from unstructured reports, but there are few related studies, and there is a limitation that textual contextual information cannot be considered during extraction, which tends to miss some important factors. Meanwhile, further analysis, assessment and control for the extracted factors are lacking. This paper aims to explore an integrated model that combines the advantages of multiple digital technologies to effectively solve the above problems.Design/methodology/approachA total of 1000 construction accident reports from Chinese government websites were used as the dataset of this paper. After text pre-processing, the risk factors related to accident causes were extracted using KeyBERT, and the accident texts were encoded into structured data. Tree-augmented naive (TAN) Bayes was used to learn the data and construct a visualized risk analysis network for construction accidents.Findings The use of KeyBERT successfully considered the textual contextual information, prompting the extracted risk factors to be more complete. The integrated TAN successfully further explored construction risk factors from multiple perspectives, including the identification of key risk factors, the coupling analysis of risk factors and the troubleshooting method of accident risk source. The area under curve (AUC) value of the model reaches up to 0.938 after 10-fold cross-validation, indicating good performance.Originality/value This paper presents a new machine-assisted integrated model for accident report mining and risk factor analysis, and the research findings can provide theoretical and practical support for accident safety management.

Keratoplasty - an Overview of the Methods and their Perioperative Management

Corneal transplantation can be divided into two groups: penetrating and lamellar keratoplasty. Newer minimally invasive procedures have emerged over the years, to improve the visual outcome and reduce complications. This article summarizes the different procedures, their indications and complications, and outlines the pre-, peri- and postoperative management in a clinical setting.Corneal transplantation is the most commonly performed transplantation of donor tissue in modern medicine. In the last years a shift away from penetrating keratoplasty (PK) towards minimally invasive lamellar operative techniques, associated with less complications, can be observed. The Descemet membrane endothelial keratoplasty (DMEK) is used to treat endothelial corneal pathologies and has overtaken the PK to become the most commonly performed form of keratoplasty. Preparation and identification of possible risk-factors are essential preoperative steps to reduce peri- and postoperative complications of keratoplasties. If corneal graft rejection occurs, early and maximum therapy is crucial for graft survival. Laser-assisted techniques offer different advantages in lamellar and penetrating keratoplasty but are not very cost-efficient.

#1665 Mechanisms underlying long-term weight changes and their impact on all-cause mortality among chronic hemodialysis patients

Abstract Background and Aims Observational studies have demonstrated a significant association between long-term weight loss and weight gain and an increased risk of mortality among chronic hemodialysis patients. However, underlying mechanisms of these associations remain insufficiently explored. To address this knowledge gap, we conducted an in-depth analysis using a cohort of hemodialysis patients, benefiting from comprehensive baseline data, regular six-month evaluations, and an extended follow-up period. We employed advanced statistical techniques, including Lasso regression, to construct predictive models for long-term weight loss and gain. Furthermore, we conducted mediation analyses to elucidate whether weight change mediates the impact of major risk factors on all-cause mortality. Method This post-hoc analysis utilized data from participants in a previous randomized controlled trial conducted between 2006 and 2011, named as the Olmesartan clinical trial in Okinawan patients under the OKIDS (OCTOPUS) study. Subsequently, we tracked participants' mortality outcomes until July 2018. At the time of enrollment, we collected comprehensive baseline information, encompassing demographics, medical history, and laboratory data. Throughout the trial, participants' body weights were meticulously recorded every six months. Our analysis was restricted to patients who survived for at least two years post-enrollment, ensuring a minimum of five body weight measurements during the trial. Lasso regression was employed in training datasets (comprising 60% of participants) to identify crucial risk factors associated with long-term weight gain (>1 kg per year) or weight loss (<−1 kg per year) among chronic hemodialysis patients. These selected models were subsequently applied to paired validation datasets (comprising 40% of participants), and receiver operating characteristic (ROC) curves were used to calculate the area under the curve (AUC), aiding in the identification of key risk factors for long-term weight changes. Subsequently, we conducted mediation analyses to investigate whether weight change mediated the relationship between risk factors and all-cause mortality. Results Our analysis included 404 out of 461 OCTOPUS participants, with 60.9% being male, a mean age of 59.2 years (±11.7), and a mortality rate of 41.6%. The median follow-up period extended to 10.3 years. In the training datasets, Lasso models identified critical predictors for weight increase, including a history of diabetes, younger age, normal cardio-thoracic ratio (CTR) (<50% for males and <53% for females), and BMI <20. Conversely, predictors for weight decrease included BMI ≥20, serum sodium <135 mEq/L, serum albumin <3.5 g/dL, and older age. Weight increase demonstrated higher predictability (mean AUC of 0.59) compared to weight decrease (mean AUC of 0.55) in the validation datasets. Mediation analyses revealed that weight loss mediated 30% of the impact of older age (≥70 years old) on all-cause mortality (P = 0.068). Conclusion Our findings suggest that, among chronic hemodialysis patients, long-term weight increase is associated with a history of diabetes and younger age, while long-term weight loss is linked to BMI (≥20), hyponatremia, hypoalbuminemia, and older age. Notably, long-term weight loss appears to explain 30% of the increased risk of all-cause mortality associated with older age (≥70 years old).

#1129 Systematic reporting of extracorporeal blood losses in a large dialysis provider organization

Abstract Background and Aims The assessment of adverse safety events is important for the risk assessment of major blood loss from the extracorporeal blood circuit during hemodialysis (HD). Such blood loss has been proven to result in a low double-digit number of fatal events per year in the USA. The frequency in Europe is not mandatorily recorded. The mechanisms of blood loss in the venous leg of the system, undetected by the alarm system of the dialysis machines, are not generally known and further patient and structure-related risks are not yet systematically recorded, evaluated and improved. Method We set up a web-based intranet database (“Event Management”) to record serious adverse events affecting patients during or around dialysis treatments in all 174 kidney centers of the Kuratorium für Dialyse und Nierentranspantation in Germany (KfH). This system is accessed via intranet within the KfH organization. Nursing and medical staff are regularly trained and informed about this system. The entry of event data that have endangered or harmed patients is mandatory. Results 141 reports of blood loss were identified for a total of approximately 3 million hemodialysis treatments performed in 174 renal centers in between 2020 and 2022, including venous needle loss due to complications in the extracorporeal blood circuit, 15 of which required inpatient treatment. The breakdown of the causes and consequences of blood losses is shown in the Figure. Conclusion Venous disconnection must be reduced by earlier detection with appropriate technical and patient-adapted measures. Patients should be educated about their individual risk and about individual measures to manage risk. Identification of patient-specific and shunt-specific risk factors is necessary. Patient-related risk factors include cognitive impairment, frailty, and dialysis in special areas (ICU, isolation area, nocturnal dialysis). Monitoring systems (blood sensors) currently on the market have good technical blood detection sensitivity. Such systems should be investigated with regard to their clinical benefit according to the rules of evidence-based medicine before their broad introduction into routine care.

#246 Understanding the impact of antiangiogenic drug-induced proteinuria on kidney function in cancer patients

Abstract Background and Aims Proteinuria is a common adverse event associated with the use of vascular endothelial growth factor (VEGF) inhibitor drugs, which are widely employed in oncology for treating various tumors. The incidence of proteinuria of all degrees ranges from 10% to 90%, with proteinuria in the nephrotic range occurring in 1-5% of cases. VEGF plays a crucial role in maintaining the integrity of the glomerular capillary wall. Podocytes, constitutively express VEGF, and VEGF receptors are present on both the surface of glomerular capillary endothelial cells and podocytes. Any disruption in the podocyte-endothelial VEGF axis can lead to the loss of endothelial fenestrations in glomerular capillaries, proliferation of glomerular endothelial cells, loss of podocytes, and subsequent proteinuria. The most common pathological findings include focal segmental glomerulosclerosis and minimal change nephropathy, typically associated with tyrosine kinase inhibitors (TKIs), as well as thrombotic microangiopathy (TMA), more frequently observed in pts treated with anti VEGF. Proteinuria is a recognized risk factor for progressive renal damage and end-stage renal disease. However, it's worth noting that the average treatment duration for patients on anti-angiogenic therapy is considerably shorter than the time indicated by clinical studies as necessary to induce renal damage from proteinuria in healthy individuals. However, the long-term impact of drug-induced proteinuria on renal function remains uncertain. The aim of the study is to investigate the association between proteinuria induced by anti-VEGF/VEGFR drugs and its long-term effects on renal function in cancer patients. Method A retrospective study was conducted on 124 patients undergoing anti-VEGF/VEGFR therapy for ≥6 months. 45% of the patients enrolled in the study were on TKI monotherapy, 36% received TKI plus immune checkpoint inhibitors (ICIs), 10% received anti- VEGF treatment, 7% received TKI + chemotherapy (CT), and 2% received anti-VEGF + ICIs. Among patients, 51% were undergoing treatment for kidney cancer, 25% for thyroid cancer, 14% for colon cancer, 7% for liver cancer, and 5% for lung cancer. The study assessed the time course of estimated glomerular filtration rate (eGFR), the influence of baseline eGFR on subsequent variations, the association between proteinuria and renal function, and the identification of risk factors for proteinuria or renal failure. Proteinuria was quantified as proteinuria/24 h. Results Among the 124 patients, 53 developed proteinuria <1 g/24 h, 41 between 1-3 g/24 h, and 30 >3 g/24 h. Specific data are outlined in Table 1. A trend toward a reduction in eGFR of −5 ml/min/1.73 m2 was observed in all patients after 2 years of treatment. The high proteinuria group exhibited a greater percentage change in eGFR compared to the other groups (−1.5% vs −8.5% vs −12.3%) as depicted in Fig. 1A, along with a time-dependent decrease in eGFR. There was no significant difference in the development of eGFR <30 ml/min/1.73 m2 between groups, and no patients permanently discontinued treatment due to nephrotoxicity. No differences in eGFR reduction were noted among the three groups categorized by baseline eGFR (Fig. 1B). Importantly, renal function after the end of therapy was found to be reversible. Conclusion The study did not find a correlation between the degree of proteinuria secondary to anti-VEGF/VEGFR and significant reductions in renal function. Therefore, treatment can be continued irrespective of the degree of proteinuria. Clinical decisions regarding the continuation of therapy with these drugs should weigh the benefits in terms of survival against the potential risks of toxicity, including a modest reduction in renal glomerular filtration rate.

Identification of crucial inflammaging related risk factors in multiple sclerosis

BackgroundMultiple sclerosis (MS) is an immune-mediated disease characterized by inflammatory demyelinating lesions in the central nervous system. Studies have shown that the inflammation is vital to both the onset and progression of MS, where aging plays a key role in it. However, the potential mechanisms on how aging-related inflammation (inflammaging) promotes MS have not been fully understood. Therefore, there is an urgent need to integrate the underlying mechanisms between inflammaging and MS, where meaningful prediction models are needed.MethodsFirst, both aging and disease models were developed using machine learning methods, respectively. Then, an integrated inflammaging model was used to identify relative risk factors, by identifying essential “aging-inflammation-disease” triples. Finally, a series of bioinformatics analyses (including network analysis, enrichment analysis, sensitivity analysis, and pan-cancer analysis) were further used to explore the potential mechanisms between inflammaging and MS.ResultsA series of risk factors were identified, such as the protein homeostasis, cellular homeostasis, neurodevelopment and energy metabolism. The inflammaging indices were further validated in different cancer types. Therefore, various risk factors were integrated, and even both the theories of inflammaging and immunosenescence were further confirmed.ConclusionIn conclusion, our study systematically investigated the potential relationships between inflammaging and MS through a series of computational approaches, and could present a novel thought for other aging-related diseases.

Complications after Heller myotomy in children: a national multicenter study on the impact of prior endoscopic dilatation and identification of risk factors.

Although esophageal achalasia has been historically treated by Heller myotomy, endoscopic esophageal dilatations are nowadays often the first-line treatment in children. The aim was to assess whether performing an endoscopic dilatation before a Heller myotomy is associated with higher risks of esophageal perforation in children. A retrospective multicentric study was performed, including children that underwent a Heller myotomy (2000-2022, 10 centers). Two groups were compared based on the history of previous dilatation before myotomy. Outcomes esophageal perforation (intra-operative or secondary) and post-operative complications requiring surgery (Clavien-Dindo III). Statistics Comparisons using contingency tables or Kruskal-Wallis when appropriate. Statistical significance: p-value < 0.05. A Heller myotomy was performed in 77 children (median age: 11.8 years), with prior endoscopic dilatation in 53% (n = 41). A laparoscopic approach was used in 90%, with associated fundoplication in 95%. Esophageal perforation occurred in 19% of children (n = 15), including 12 patients with intra-operative mucosal tear and 3 with post-operative complications related to an unnoticed esophageal perforation. Previous endoscopic dilatation did not increase the risk of esophageal perforation (22% vs 17%, OR: 1.4, 95%CI: 0.43-4.69). Post-operative complications occurred in 8% (n = 6), with similar rates regardless of prior endoscopic dilatation. Intra-operative mucosal tear was the only risk factor for post-operative complications, increasing the risk of complications from 5 to 25% (OR: 6.89, 95%CI: 1.38-31.87). Prior endoscopic dilatations did not increase the risk of esophageal perforation or postoperative complications of Heller myotomy in this cohort of children with achalasia. Mucosal tear was identified as a risk factor for post-operative complications.

Predictive modelling and identification of key risk factors for stroke using machine learning

Strokes are a leading global cause of mortality, underscoring the need for early detection and prevention strategies. However, addressing hidden risk factors and achieving accurate prediction become particularly challenging in the presence of imbalanced and missing data. This study encompasses three imputation techniques to deal with missing data. To tackle data imbalance, it employs the synthetic minority oversampling technique (SMOTE). The study initiates with a baseline model and subsequently employs an extensive range of advanced models. This study thoroughly evaluates the performance of these models by employing k-fold cross-validation on various imbalanced and balanced datasets. The findings reveal that age, body mass index (BMI), average glucose level, heart disease, hypertension, and marital status are the most influential features in predicting strokes. Furthermore, a Dense Stacking Ensemble (DSE) model is built upon previous advanced models after fine-tuning, with the best-performing model as a meta-classifier. The DSE model demonstrated over 96% accuracy across diverse datasets, with an AUC score of 83.94% on imbalanced imputed dataset and 98.92% on balanced one. This research underscores the remarkable performance of the DSE model, compared to the previous research on the same dataset. It highlights the model's potential for early stroke detection to improve patient outcomes.

The role of donor hypertension and angiotensin II in the occurrence of early pancreas allograft thrombosis

BackgroundAbout 10–20% of pancreas allografts are still lost in the early postoperative period despite the identification of numerous detrimental risk factors that correlate with graft thrombosis.MethodsWe conducted a multicenter study including 899 pancreas transplant recipients between 2000 and 2018. Early pancreas failure due to complete thrombosis, long-term pancreas, kidney and patient survivals were analyzed and adjusted to donor, recipient and perioperative variables using a multivariate cause-specific Cox model stratified to transplant centers.ResultsPancreas from donors with history of hypertension (6.7%), as well as with high body mass index (BMI), were independently associated with an increased risk of pancreas failure within the first 30 post-operative days (respectively, HR= 2.57, 95% CI from 1.35 to 4.89 and HR= 1.11, 95% CI from 1.04 to 1.19). Interaction term between hypertension and BMI was negative. Donor hypertension also impacted long-term pancreas survival (HR= 1.88, 95% CI from 1.13 to 3.12). However, when pancreas survival was calculated after the postoperative day 30, donor hypertension was no longer a significant risk factor (HR= 1.22, 95% CI from 0.47 to 3.15). A lower pancreas survival was observed in patients receiving a pancreas from a hypertensive donor without RAAS (Renin Angiotensin Aldosterone System) blockers compared to others (50% vs 14%, p &amp;lt; 0.001). Pancreas survival was similar among non-hypertensive donors and hypertensive ones under RAAS blockers.ConclusionDonor hypertension was a significant and independent risk factor of pancreas failure. The well-known pathogenic role of renin-angiotensin-aldosterone system seems to be involved in the genesis of this immediate graft failure.

From hazard to risk prioritization: a case study to predict drug-induced cholestasis using physiologically based kinetic modeling.

Cholestasis is characterized by hepatic accumulation of bile acids. Clinical manifestation of cholestasis only occurs in a small proportion of exposed individuals. The present study aims to develop a new approach methodology (NAM) to predict drug-induced cholestasis as a result of drug-induced hepatic bile acid efflux inhibition and the resulting bile acid accumulation. To this end, hepatic concentrations of a panel of drugs were predicted by a generic physiologically based kinetic (PBK) drug model. Their effects on hepatic bile acid efflux were incorporated in a PBK model for bile acids. The predicted bile acid accumulation was used as a measure for a drug's cholestatic potency. The selected drugs were known to inhibit hepatic bile acid efflux in an assay with primary suspension-cultured hepatocytes and classified as common, rare, or no for cholestasis incidence. Common cholestasis drugs included were atorvastatin, chlorpromazine, cyclosporine, glimepiride, ketoconazole, and ritonavir. The cholestasis incidence of the drugs appeared not to be adequately predicted by their Ki for inhibition of hepatic bile acid efflux, but rather by the AUC of the PBK model predicted internal hepatic drug concentration at therapeutic dose level above this Ki. People with slower drug clearance, a larger bile acid pool, reduced bile salt export pump (BSEP) abundance, or given higher than therapeutic dose levels were predicted to be at higher risk to develop drug-induced cholestasis. The results provide a proof-of-principle of using a PBK-based NAM for cholestasis risk prioritization as a result of transporter inhibition and identification of individual risk factors.

Characterization of Colon Anastomosis Healing in Obese Mice

Abstract Background Colon anastomosis leak is the most feared complication in colorectal surgery, with high morbidity and mortality. Despite the identification of correctible risk factors, its incidence has remained stable for the past 50 years. One of the risk factors is obesity, a systemic disease whose prevalence is continuously increasing worldwide. To understand the implicated mechanisms, and to develop therapeutic strategies, characterization of colon anastomosis healing in obese subjects is mandatory. Aims We aimed to describe the colon anastomotic healing process in obese mice, with a secondary aim to identify potential targets to decrease post-operative leaks. Methods Three groups of mice were fed different diets for 16 weeks: normal diet only (ND), high-fat diet reverted to normal diet on day of surgery (HF-ND), or high-fat diet only (HF-HF). Surgery consisted of left colon hemi-transection on the anti-mesenteric wall, and subsequent anastomosis with separate stitches. N=5 mice from each group were sacrificed at days 3, 5, 7, 10 and 14 after surgery. Results HF-HF mice had diarrhea and lost weight up to day 10 after surgery, compared to day 1 for ND mice. Overall, abscess rate was 4% in ND and HF-ND, and 8% in HF-HF mice. Free leak rate was 0% in ND and HF-ND, and 16% in HF-HF mice (p=0.03). Angiogenesis was decreased in HF-HF mice at day 5 compared to ND mice (p=0.02). Conclusion Obese mice undergoing continued high-fat diet (HF-HF) globally demonstrated worst outcomes after colon anastomosis with increased leak rates, and decreased angiogenesis. Despite having similarly low angiogenesis, these results seem to be mitigated in high-fat diet fed mice reverting to normal diet on day of surgery (HF-ND), hinting towards an involvement of gut microbiota. Further analysis of gut microbiota and angiogenesis pathways are warranted in order to determine therapeutic strategies.

New Models for Prediction of Post-Operative Pulmonary Complications in Lung Resection Candidates

IntroductionIn recent years, ventilatory efficiency (VE/VCO2slope) and partial pressure of end-tidal carbon dioxide (PETCO2) emerged as independent predictors of post-operative pulmonary complications (PPC). Single parameters may give only partial information regarding peri-procedural hazards. Accordingly, our aim was to create prediction models with improved ability to stratify PPC risk in patients scheduled for elective lung resection surgery.MethodsThispost-hocanalysis was comprised of consecutive lung resection candidates from two prior prospective trials. All individuals completed pulmonary function tests and cardiopulmonary exercise testing (CPET). Logistic regression analyses were used for identification of risk factors for PPC that were entered into the final risk prediction models. Two risk models were developed; the first used rest PETCO2(for patients with no available CPET data), the second used VE/VCO2slope (for patients with available CPET data). ROC analysis with the De-Long test and area under the curve (AUC) were used for comparison of models.ResultsThe dataset from 423 patients was randomly split into the derivation (n=310) and validation (n=113) cohorts. Two final models were developed, both including sex, thoracotomy, „atypical“ resection and FEV1/FVC ratio as risk factors. In addition, the first model also included rest PETCO2, while the second model used VE/VCO2slope from CPET. AUCs of risk scores were 0.795 (95% CI: 0.739–0.851) and 0.793 (95% CI: 0.737–0.849); both p&lt;0.001. No differences in AUCs were found between the derivation and validation cohorts.ConclusionsWe created two multicomponental models for PPC risk prediction, both having excellent predictive properties.

Iris Pigmented Lesions and Risk of Cutaneous Melanoma: Case-Control Study in Lithuania.

The global incidence of cutaneous melanoma (CM) is rising, necessitating early detection and identification of risk factors across different populations. A case-control study with 180 patients with primary diagnosed CM and 182 healthy controls was conducted. Participants underwent ophthalmic and skin examinations, where the identification and counting of common melanocytic nevi (CMN) and atypical melanocytic nevi (AMN) was performed. During ophthalmic examination, high-resolution slit lamp iris images were taken. Images were categorized according to iris periphery, collaret, and freckles. There was no difference in iris periphery and collaret color between groups. However, blue/grey iris periphery and blue collaret with or without freckles were the most common patterns. The presence of pigmented iris lesions and 2-5 mm and ≥5 mm in diameter CMNs was strongly associated with CM risk. The evidence from this study indicates that blue or grey periphery and blue collaret iris pattern with iris freckles are 2.74 times higher in the CM group than controls. Further research is needed to explore iris patterns' association with CM risk in diverse populations.

Definitions and surveillance methods of running‐related injuries: A scoping review

AbstractInconsistent and restricted definitions of injury have contributed to limitations in determining injury rates and identifying risk factors for running‐related injuries (RRIs). The aim of this scoping review was to investigate the definitions and surveillance methods of RRIs. A systematic electronic search was performed using PubMed, Scopus, SPORTDiscuss, MEDLINE, and Web of Science databases. Included studies were published in English between January 1980 and June 2023 which investigated RRIs in adult running populations, providing a definition for a general RRI. Results were extracted and collated. 204 articles were included. Three primary criteria were used to define RRIs: physical description, effect on training and medical intervention, while three secondary criteria are also associated with definitions: cause/onset of injury, location, and social consequences. Further descriptors and sub‐descriptors form these criteria. The use of Boolean operators resulted in nine variations in definitions. Inconsistency is evident among definitions of RRIs. Injury definitions seem to be important for two main reasons: firstly, determining accurate injury rates, and secondly, in research examining risk factors. For the latter, definitions seem to be very limited, only capturing severe injuries and failing to recognise the full development process of RRIs, precluding the identification of conclusive risk factors. A potential two‐approach solution is the initial use of a broad definition acting as a gatekeeper for identifying any potential injury, and follow‐up with an extensive surveillance tool to capture the specific consequences of the varying severity of RRIs.

More than clean teeth! Identifying factors that contribute to the development of early childhood caries.

This review aimed to identify established and updated evidence-based factors that could contribute to a child's development of Early Childhood Caries (ECC). Four online databases were used to source evidence including the Cochrane Library, EMBASE, MEDLINE, and Scopus. The data search selected studies published between 2017 and 2021. Three specific terms were used to search: Dental Caries, Children, and Risk Assessment. There were three teams involved in data collection, two teams then reviewed selected articles. Exclusion criteria included any duplicate studies, commentaries, and editorials. Inclusion criteria included only randomised control trials and cohort studies. Selected studies must include children younger than 72 months, define the demographics, their clinical characteristics, and have clear follow-up of the patients involved. Commonly identified factors that were mentioned in multiple studies were then collected and assigned strength depending on the evidence measured using ratios. These could then beutilised to form a draft Caries Risk Assessment tool. 512 abstracts and 52 articles were screened, having matched the criteria set. Extraction of the data was completed under four headings: the child's age at the time of study (in years/months), risk predictors, the outcome, and the quality of the evidence presented. The GRADE system was then employed to separate the studies into high, moderate, low, and very low categorisation. Eventually, 22 new studies were included that would build on the original 25 articles that were identified in the previous systematic review. The most defining factors across the most recent systematic reviews in 2021 highlighted behavioural factors such as toothbrushing quality - parental supervision, frequency, and fluoride exposure. Specifically, the presence of plaque was used as a marker for oral hygiene evaluation. Dietary history included snacking frequency and, controversially, baby-toddler breastfeeding patterns. However, this does not take into consideration the dental impact - mainly the frequency or timing of breastfeeding (e.g. overnight). The review emphasises the importance of consideration of socio-economic factors though this may be a difficult topic of discussion if families are struggling i.e. household income and education level of parents or guardians. There is also mention of factors that do not have a significant evidence base such as the child's gender, ethnicity, and parental smoking status. In conclusion, the factors found to be relevant in the development of ECC were the child's age, toothbrushing quality/plaque control, parental involvement in toothbrushing, fluoride exposure, pattern of dental attendance, dietary sugar exposure, and habits, clinically carious active lesion presence, the oral bacterial composition (Streptococcus mutanspresence) and the socio-economic status of the child and their family. Though the review encourages identification of the caries risk factors in the mentioned groups, separated by both dental and non-dental professionals, ideally the aim would be to create a holistic care approach for management and signposting.

Preoperative Risk Factors for Pain After Reverse Total Shoulder Arthroplasty: A Systematic Review.

Despite being a generally successful procedure, pain following reverse total shoulder arthroplasty (rTSA) is a known complication. The aim of this systematic review is to identify preoperative risk factors for pain following rTSA to encourage evidence-based interventions, inform clinicians, and aid in surgical planning. Studies that reported preoperative risk factors and pain after rTSA were included. Studies which reported outcome measures that incorporated pain scores yet did not display them independently, studies which only reported intraoperative risk factors, and studies involving participants under 18 were excluded. The search was conducted on May 31, 2023, across the following databases: PubMed, Web of Science, Embase, Scopus, and Cochrane Central Register of Controlled Trials. Four independent researchers conducted this systematic review, and a descriptive analysis was subsequently performed. Twenty-five studies were included following the evaluation of full-text articles, involving a total of 9,470 shoulders. Preoperative risk factors identified were categorised into the following groups: BMI, smoking, radiographic findings, age and sex, prior surgery, functional ability and pain, and psychosocial. The strongest associations identified were preoperative opioid use and smoking, which were both associated with worse pain outcomes following rTSA; other preoperative risk factors highlighted in this review showed either weak or no correlation. Preoperative opioid use and smoking are likely risk factors for the development of pain after rTSA. Although the studies included varying levels of quality, the identification of modifiable risk factors is useful in optimising management prior to surgery and guiding patient expectations. The lack of evidence regarding associations with non-modifiable risk factors further reinforces the potential benefits of the procedure on diverse population groups and is useful in itself for assessing the candidacy of patients for the procedure, particularly when postoperative pain is a factor being considered.