Complexity Score Research Articles

Hyperlactataemia Following Crystalloid Cardiopulmonary Bypass Priming in Paediatric Cardiac Surgery—Benign or Malignant? A Retrospective Study

Background: Various mechanisms leading to early hyperlactataemia post-cardiac surgery have been postulated. Specifically, in the paediatric population, benign early hyperlactataemia may be associated with crystalloid priming in the cardiopulmonary bypass circuit. The aim of this study was to review paediatric patients who had crystalloid prime and assess their outcomes. Methods: A retrospective review of paediatric patients who underwent cardiac surgery with crystalloid prime at our institution between November 2014 and May 2018 was performed. Data were collected from medical and laboratory records. Results: Among 569 patients, 237 (42%) received a crystalloid prime; 51 (22%) were excluded due to intraoperative hyperlactataemia. Of the remaining 186 patients, 98 (53%) developed hyperlactataemia postoperatively. Patients with hyperlactataemia had longer cardiopulmonary bypass and aortic cross-clamp times but similar Aristotle complexity scores. Patients with postoperative hyperlactataemia had higher peak VIS [median 8 (IQR 0–8) vs. 5 (IQR 0–8)] within the first 24 h (p = 0.002). However, there was no difference in the duration of ventilation between the two groups (p = 0.14). Yet only 58% of patients with hyperlactataemia were discharged from the ICU within 24 h, compared to 78% without hyperlactataemia. Conclusions: In this study population, transient postoperative hyperlactataemia in paediatric patients with crystalloid prime may not necessarily indicate tissue hypoxaemia. Despite a similar duration of ventilation in patients with and without hyperlactataemia, patients with hyperlactataemia had a longer duration of inotropes and ICU stay. Consideration should be given to discontinuing inotropes in patients with crystalloid prime and postoperative early hyperlactataemia once they are extubated.

Interleukin-1 Blockade in Patients With ST-Segment Elevation Myocardial Infarction Across the Spectrum of Coronary Artery Disease Complexity.

Patients with ST-segment elevation myocardial infarction (STEMI) and complex coronary artery disease (CAD) face a poor prognosis, including increased heart failure (HF) risk. Phase 2 clinical trials of anakinra have shown inhibition of the acute inflammatory response and prevention of HF after STEMI, but data on its effects based on CAD complexity are lacking. We performed a pooled secondary analysis of 139 patients with STEMI. The SYNTAX (Synergy Between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery), SYNTAX II and Gensini scores were calculated, and patients were divided into two groups below and above the median. We evaluated the effect of anakinra on the area-under-the-curve of high-sensitivity C-reactive protein (hsCRP-AUC) at 14 days, and the composite endpoint of new-onset HF, HF hospitalization, or all-cause death at 1-year follow-up using Kaplan-Meier survival curves, Cox regression analysis for Hazard Ratios (HR), and tested interactions between subgroups. All three CAD complexity scores (SYNTAX, SYNTAX II and Gensini) were associated with an increased risk of adverse events (HR 1.02 to 1.06, all p-values ≤0.025). We found no statistically significant interactions between CAD extent, measured as single-vessel or multi-vessel CAD, SYNTAX score ≤9 or >9, SYNTAX II score ≤24 or >24, Gensini score ≤32 or >32, and treatment effect of anakinra on hsCRP-AUC or the composite clinical endpoint (all p-values for interaction >0.05). In conclusion, among patients with STEMI, IL-1 blockade with anakinra significantly attenuated the acute inflammatory response and reduced the risk of HF-related events regardless of the spectrum of CAD complexity.

Quantitative Evaluation of a Fully Automated Planning Solution for Prostate-Only and Whole-Pelvic Radiotherapy

Background/Objectives: To evaluate an end-to-end pipeline for normo-fractionated prostate-only and whole-pelvic cancer treatments that requires minimal human input and generates a machine-deliverable plan as an output. Methods: In collaboration with TheraPanacea, a treatment planning pipeline was developed that takes as its input a planning CT with organs-at-risk (OARs) and planning target volume (PTV) contours, the targeted linac machine, and the prescription dose. The primary components are (i) dose prediction by a single deep learning model for both localizations and (ii) a direct aperture VMAT plan optimization that seeks to mimic the predicted dose. The deep learning model was trained on 238 cases, and a held-out set of 86 cases was used for model validation. An end-to-end clinical evaluation study was performed on another 40 cases (20 prostate-only, 20 whole-pelvic). First, a quantitative evaluation was performed based on dose–volume histogram (DVH) points and plan parameter metrics. Then, the plan deliverability was assessed via portal dosimetry using the global gamma index. Additionally, the reference clinical manual plans were compared with the automated plans in terms of monitor unit (MU) numbers and modulation complexity scores (MCSv). Results: The automated plans provided adequate treatment plans (or minor deviations) with respect to the dose constraints, and the quality of the plans was similar to the manual plans for both localizations. Moreover, the automated plans showed successful deliverability and passed the portal dose verification. Despite higher median total MUs, no statistically significant correlation was observed between any of the gamma criteria tested and the number of MUs or MCSv. Conclusions: This study shows the feasibility of a deep learning-based fully automated treatment planning pipeline that generates high-quality plans that are competitive with manually made plans and are clinically approved in terms of dosimetry and machine deliverability.

Patient Photograph Association with Radiologist Recommendations for Additional Imaging

ObjectiveAssess whether display of a patient photograph in the electronic health record (EHR) alongside head and neck CT or MRI radiology examinations is associated with recommendations for additional imaging (RAI) and whether self-reported race modifies that association. MethodsThis multi-institution healthcare system retrospective observational study from 6/1/2021-5/31/2022 included all patients with a head/neck CT or MRI report. We investigated association of photograph with RAI using mixed effects models adjusting for age, sex, complexity score, race, and area deprivation index while conditioning on patient and radiologist. Race was subsequently included as an interaction term. Multiple imputation was used as sensitivity analysis to address missing race data. Results60,543 reports were included from 48,143 patients (55.6% female; median age 58 years, IQR 40-70). The EHR included a photograph at the time 18.2% (11,048/60,543) of reports were signed. 7.5% (4,522/60,543) of reports contained RAI. Reports signed when a photograph was displayed had lower estimated odds of containing RAI (OR: 0.85, 95%CI: 0.77-0.93, p<0.001), consistent in sensitivity analysis, with no clear interaction between race and photograph (OR: 0.99, 95% CI: 0.69-1.46, p=0.97). DiscussionPatients with a photograph in the EHR had a lower probability of receiving RAI and this difference did not appear to be the result of implicit racial bias but may be due to personalization of the encounter. This effect may influence radiology reporting for millions of patients per year. Further research is needed to determine if the association has a positive or negative impact on care quality and outcomes.

Machine learning prediction models for individualized technical success of chronic total occlusion revascularization using anatomical input

Abstract Introduction Chronic total occlusion revascularization (CTO PCI) remains a challenging procedure in the realm of percutaneous coronary interventions. Efforts such as implementing the hybrid algorithm for CTO crossing have been made. Interventional techniques are evolving, and complexity scores such as the J-CTO score might get outdated. Machine learning models can be used to overcome this limitation by constantly providing new data and improving the models by continuous data feeding. In this study, we introduced machine learning models to predict individualized technical success of CTO PCI using anatomical coronary information and baseline information. Methods Consecutive patients undergoing percutaneous coronary intervention of chronic total occlusions were enrolled in this study. Angiographic data and lesion characteristics from coronary angiography were extracted. Machine learning models were applied to predict technical success. A total of 271 patients were used to validate and train the models and 50 separate patients for testing. Data was normalized and fed to several classifying machine learning models including decision trees (DT), random forest (RF), extreme gradient boosting (XGB), CatBoost (CB) classifiers, and light gradient boosting (LGB). Finally, accuracy, precision, recall and F1-score of the selected hyperparameters and cross-validation was performed. Results CB was the best performing model with an accuracy of 0.81, precision of 0.83 and recall of 0.98. The F1 score was 0.90. RF was the second-best performing model with accuracy of 0.77, precision of 0.82, recall of 0.92 and F1 score 0.87. The tuned models performed modestly with RF having a low F1 score of 0.44, due to small sample size. In the tuned models. LGB had a higher F1 score and a relatively high accuracy (0.782) and precision (0.508). The feature importance matrix found age, CTO length, reference diameter to have the highest value among the lesion complexity parameters. Discussion: Overall, the normal-run CB was the best model for predicting the technical success after a CTO PCI with a high accuracy. The fine-tuned and cross-validated models performed modestly because of the relatively small, unbalanced dataset and overfitting. However, data showed promising first results in implementing machine learning into predicting interventional outcomes. Further studies like data augmentation and providing a weighted dataset would increase the model performance and provide a very precise statement whether a patient would have increased chances to have a successful PCI based on baseline anatomic information. Conclusion This is one of the first studies to predict technical success of CTO PCI using angiographic baseline parameters using machine learning. Future studies with larger patient cohorts are needed to involve deploying the selected model in larger patient cohorts including external validation and assessing its performance with new, unseen data.Figure 1.Machine learning modelsFigure 2.Feature importance matrix

Improved protein interaction models predict differences in complexes between human cell lines.

The interactions of proteins to form complexes play a crucial role in cell function. Data on protein-protein or pairwise interactions (PPI) typically come from a combination of sample separation and mass spectrometry. Since 2010, several extensive, high-throughput mass spectrometry-based experimental studies have dramatically expanded public repositories for PPI data and, by extension, our knowledge of protein complexes. Unfortunately, challenges of limited overlap between experiments, modality-oriented biases, and prohibitive costs of experimental reproducibility continue to limit coverage of the human protein assembly map, both underscoring the need for and spurring the development of relevant computational approaches. Here, we present a new method for predicting the strength of protein interactions. It addresses two important issues that have limited past PPI prediction approaches: incomplete feature sets and incomplete proteome coverage. For a given collection of protein pairs, we fused data from heterogeneous sources into a feature matrix and identified the minimal set of feature partitions for which a non-empty set of protein pairs had complete values. For each such feature partition, we trained a classifier to predict PPI probabilities. We then calculated an overall prediction for a given protein pair by weighting the probabilities from all models that applied to that pair. Our approach accurately identified known and highly probable PPI, far exceeding the performance of current approaches and providing more complete proteome coverage. We then used the predicted probabilities to assemble complexes using previously-described graph-based tools and clustering algorithms and again obtained improved results. Lastly, we used features for three human cell lines to predict PPI and complex scores and identified complexes predicted to differ between those cell lines.

Subsegmentation of the hippocampus in subgroups of migraine with aura patients: advanced structural neuroimaging study

BackgroundThis study investigated for a possible contributing role of hippocampus in the different clinical phenotypic manifestations of migraine aura.MethodsHerein, patients were categorized as those with pure visual aura (MwAv), those who reported additional somatosensory and dysphasic symptoms (MwAvsd), and healthy controls (HCs). Neuroimaging data obtained using FreeSurfer-based segmentation of hippocampal subfields were compared between HCs and patients with migraine with aura, as well as between HCs and those with MwAv and MwAvsd. The average migraine aura complexity score (MACS) was calculated for each patient to investigate the correlation between hippocampal subfield volume and migraine aura complexity.ResultsHerein, 46 patients with migraine with aura (28 MwAvsd and 18 MwAv) and 31 HCs were included. There were no significant differences in the hippocampal subfields between HCs and patients with migraine with aura. The average MACS negatively correlated with the volumes of the left and right hippocampi, Cornu Ammonis (CA) 1, CA3, CA4, molecular layer, left granule cell layer of the dentate gyrus, hippocampal fissure, and hippocampus-amygdala transition area. The MwAvsd subgroup had significantly smaller whole hippocampal volumes in both hemispheres, as well as in both subicula, compared with the MwAv subgroup and HCs. In addition, the left molecular layer, right CA1, and hippocampal fissures were significantly smaller in the MwAvsd group than in the MwAv subgroup and HCs.ConclusionsSmaller left and right hippocampal volumes, particularly of the subiculum/CA1 area, may play an important role in the pathophysiology of somatosensory and dysphasic symptoms in migraine with aura.

Online Plain Language Tool and Health Information Quality

Complex and ineffective health communication is a critical source of health inequity and occurs despite repeated policy directives to provide health information that is easy to understand and applies health literacy principles. To evaluate the effectiveness of the Sydney Health Literacy Lab Health Literacy Editor, an easy-to-use online plain language tool that supports health information providers to apply health literacy guidelines to written health information. This randomized clinical trial, conducted online in Australia from May 2023 to February 2024, included a convenience sample of health information providers with no previous experience using the Health Literacy Editor. Analysts were blinded to study group. Participants were randomized 1:1 to the intervention or control group. Participants in the intervention group were provided access to the Health Literacy Editor and a 30-minute online training program prior to editing 3 prespecified health texts. The Health Literacy Editor gives objective, real-time feedback on words and sentences. Control participants revised the texts using their own standard health information development processes. The preregistered primary outcome was the text school grade reading score (using a validated instrument, the Simple Measure of Gobbledygook). Secondary outcomes were text complexity (percentage of text using complex language), use of passive voice (number of instances), and subjective expert ratings (5-point Likert scale corresponding to items on the Patient Education Materials Assessment Tool). A total of 211 participants were randomized, with 105 in the intervention group and 106 in the control group. Of 181 participants in the intention-to-treat analysis (mean [SD] age, 41.0 [11.6] years; 154 women [85.1%]), 86 were in the intervention group and 95 in the control group. Texts revised in the intervention group had significantly improved grade reading scores (mean difference [MD], 2.48 grades; 95% CI, 1.84-3.12 grades; P < .001; Cohen d, 0.99), lower text complexity scores (MD, 6.86; 95% CI, 4.99-8.74; P < .001; Cohen d, 0.95), and less use of passive voice (MD, 0.95 instances; 95% CI, 0.44-1.47 instances; P < .001; Cohen d, 0.53) compared with texts revised in the control group in intention-to-treat analyses. Experts rated texts in the intervention group more favorably for word choice and style than those in the control group (MD, 0.44; 95% CI, 0.25-0.63; P < .001; Cohen d, 0.63), with no loss of meaning or content. In this randomized clinical trial, the Health Literacy Editor helped users simplify health information and apply health literacy guidelines to written text. The findings suggest the tool has high potential to improve development of health information for people who have low health literacy. As an online tool, the Health Literacy Editor is also easy to access and implement at scale. ANZCTR Identifier: ACTRN12623000386639.

Assessment of the frequency and risk factors of gastrointestinal bleeding after cardiopulmonary bypass in paediatric cases.

Gastrointestinal bleeding is a potential complication in paediatric patients undergoing cardiopulmonary bypass, as it develops secondary to low gastrointestinal perfusion. This study aimed to examine the incidence of gastrointestinal bleeding and identify its risk factors in these patients. This retrospective study was undertaken to examine the demographic features, clinical findings, and operative data of paediatric patients under years old who had undergone congenital heart surgery with cardiopulmonary bypass between November 1, 2021, and November 1, 2023. The study aimed to investigate the incidence of gastrointestinal bleeding associated with cardiopulmonary bypass and to identify potential risk factors for gastrointestinal bleeding. The obtained results were statistically evaluated. The study period included 1100 patients who underwent congenital heart surgery with cardiopulmonary bypass. Fifty-two percent of the total participants were male. The median weight of the patients was 4.4 kg, with an interquartile range of 3.5-5.8 kg. The patients were categorised by age, revealing that 62% were newborns, 24% were infants, and 14% were children. Forty-four (4.2%) of the total number of patients experienced gastrointestinal bleeding. Newborns had a significantly higher incidence of bleeding (6% or 34 patients) compared to infants (3% or 8 patients) and children (1.5% or 2 patients) (p < 0.05). Patients who experienced gastrointestinal bleeding had a longer median hospital stay of 24 days compared to those who did not, with a median hospital stay of 14 days. Moreover, patients who suffered from bleeding had a significantly higher mortality rate (30%) in comparison to those who did not (9.9%) (p < 0.05). The incidence of gastrointestinal bleeding was found to be associated with several risk factors, such as low operative age and weight, high surgical score, presence of low cardiac output syndrome, extracorporeal membrane oxygenation (ECMO) usage, high lactate levels, and low platelet count. Gastrointestinal bleeding is a potential complication for patients who undergo cardiopulmonary bypass. It is particularly relevant for newborns who have undergone prolonged surgery, have a high surgical complexity score, exhibit high lactate levels, display low cardiac output, utilise ECMO, and possess low platelet counts. In such cases, there may be a heightened incidence of gastrointestinal bleeding. It is important to consider this possibility in order to ensure the best possible patient outcomes.

An Evaluation of Patient Profiles and Outcomes in an Off-Site Rehabilitation Unit in 2023 Compared to 2019

Abstract Background Our off-site inpatient rehabilitation unit accepts patients from many different referral centres. Demographic shifts have occurred in the last 4 years with the Covid-19 pandemic resulting in several practice changes and frailty admissions increasing at our primary referral centre by 11%. We compared the number of patients, their demographics and dependency in 2023 in comparison with 2019 and hypothesised a longer length of stay could be explained by increased dependency as defined by Barthel score on admission. Methods Data regarding patients’ age, admission and discharge dates, referral source and discharge destination were extracted from the rehabilitation unit's database. Weekly MDT records were examined to identify the patients’ presentation and dependency level. Presentations were categorised as stroke, hip fracture, other fracture, acute medical and surgical presentations, and elective surgical procedures. Results Discharges decreased to 89 in 2023 compared to 125 in 2019. Mean length of stay increased to 35.1 from 29.5. Mean age reduced from 85 to 83. Mean Barthel on admission was unchanged at 10. 21 Patients were admitted following elective orthopaedic surgery in 2019 compared to 2 in 2023 with a mean length of stay of 16 days. Length of stay for stroke patients increased from 33 to 50. Excluding both led to a length of stay of 32 in both years. Conclusion The reduction of bed days could be explained by increased frequency of outbreaks and more robust isolation strategies reducing total bed availability. A significant reduction in patients admitted following elective orthopaedic surgery impacted the average length of stay as did an increase in length of stay for stroke patients. Patient dependency defined by Barthel score was not increased and did not explain the increased length of stay. A more comprehensive score such as the Rehabilitation Complexity Score may be more predictive of complexity and thus length of stay.

"Like an umbrella, protecting me from the rain until I get to my destination": Evaluating the implementation of a tailored primary care model for urban marginalized populations.

Improving health equity and access to the highest possible standard of health care is a key issue of social accountability. Centretown Community Health Centre in Ottawa, Canada has iteratively developed a program to target and serve marginalized and complex populations since 1999. The program implementation was evaluated using a validated implementation framework. Quantitative and qualitative data were collected through a health records extraction (n = 570), a client complexity assessment tool (n = 74), semi-structured interviews with clients and key stakeholders (n = 41), and a structured client satisfaction survey (n = 30). Data were analyzed using descriptive statistics and inductive thematic analysis. Five hundred and seventy unique clients were seen between November 1-30, 2021. A third of clients (34%) did not have a provincial health card for access to universal health care services, and most (68%) were homeless or a resident of rooming houses. Most clients who reported their income (92%) were at or below Canada's official poverty line. The total mean complexity score for clients seen over a one-month period (n = 74) was 16.68 (SD 6.75) where a total score of at least 13 of 33 is perceived to be a threshold for client biopsychosocial complexity. Clients gained the majority of their total score from the Social support assessment component of the tool. Clients (n = 31) and key informants (n = 10) highlighted the importance of building relationships with this population, providing wrap-around care, and providing low-barrier care as major strength to the Urban Health program (UH). Key areas for improvement included the need to: i) increase staff diversity, ii) expand program hours and availability, and iii) improve access to harm reduction services. Clients appeared to be highly satisfied with the program, rating the program an average total score of 18.50 out of 20. The program appears to serve marginalized and complex clients and seems well-received by the community. Our findings have relevance for other health care organizations seeking to better serve marginalized and medically and socially complex individuals and families in their communities.

The correlation of the modulation complexity score (MCS) with the number of segments and local gamma passing rate for the Intensity Modulated Radiation Therapy (IMRT) treatment planning delivery.

To compare the modulation complexity scores across treatment sites, and to examine their connection with monitor unit, segment number and global and local gamma passing percentage. The cross-sectional study was conducted at the Baghdad Centre for Radiation Therapy and Nuclear Medicine, Baghdad Medical City, Baghdad, Iraq, from May 2021 to February 2022. Included were 34 patients, with the age range between 20 - 50 years, subjected to intensity-modulated radiation therapy for head and neck tumours in group A or pelvic tumours in group B. Treatment planning was done using Monaco 5.1, and radiotherapy was done using Synergy linear accelerator. Modulation complexity scores were calculated using MATLAB 2019a. Data was analysed using SPSS 24. Of the 34 patients, 22(64.7%) were in group A; 12(54.5%) males and 10(45.5%) females. There were 12(35.3%) patients in group B; 8(66.7%) females and 4(33.3%) males. The number of segments was greater in group B than group A. A modest positive linear association was seen in group A, demonstrating that an increase in segment numbers resulted in a rise in modulation complexity score (R2=0.0244). Group B tumours had inverse negative linear correlation (R2=0.0189). As the complexity of plans increased in group A, local gamma passing percentage decreased (R2=0.0452). Group B showed a slight negative connection with modulation complexity score (R2=0.0622). The modulation complexity score may be used to provide a simple prediction for pre-treatment verification, and it may also serve as a simple quality assurance tool for intensity-modulated radiation therapy plans.

AI-Powered Telemedicine for Automatic Scoring of Neuromuscular Examinations.

Telemedicine is now being used more frequently to evaluate patients with myasthenia gravis (MG). Assessing this condition involves clinical outcome measures, such as the standardized MG-ADL scale or the more complex MG-CE score obtained during clinical exams. However, human subjectivity limits the reliability of these examinations. We propose a set of AI-powered digital tools to improve scoring efficiency and quality using computer vision, deep learning, and natural language processing. This paper focuses on automating a standard telemedicine video by segmenting it into clips corresponding to the MG-CE assessment. This AI-powered solution offers a quantitative assessment of neurological deficits, improving upon subjective evaluations prone to examiner variability. It has the potential to enhance efficiency, patient participation in MG clinical trials, and broader applicability to various neurological diseases.

Comparison of Scoring Systems in Predicting Stone-Free Rate in Flourless Retrograde Intrarenal Surgery

Abstract: Thus far, there is no standardised method for predicting outcomes from fluoro-less retrograde intrarenal surgery (RIRS) procedure. This study aimed to compare scoring systems in predicting stone-free rate (SFR) in RIRS patients This was an observational and analytical study with a retrospective cohort design. Samples were obtained from medical records of Dr. J. H. Awaloei Hospital from March 2022 to October 2023. This study only analyzed three scoring systems: Guy's Stone Score (GSS), Resorlu-Unsal Stone Score (RUSS), and Seoul National University Renal Stone Complexity Score (S-ReSC). The results obtained 219 patients with an average age of 55 years, GSS grade I in 108 patients, and grade II in 50 patients. Related to RUSS score, 43 patients got a score of 1, 108 got a score of 2, and 60 got a score of 60. Meanwhile, S-ReSC score was at a high level with a percentage of 65.3%, 20.4% at the medium level, and 14.4% at the low level. Moreover, GSS sensitivity 76%, specificity 75%, PPV 93.2%, NPV 41.1%, AUC 75%; RUSS score sensitivity 75.4%, specificity 62.2%, PPV 90%, NPV 36.2%, AUC 70%; S-ReSC score sensitivity 71%, specificity 77.5%, PPV 93.4%, NPV 37.3%, AUC 72%. In conclusion, Guy's Stone Score, Resorlu-Unsal Stone Score, and Seoul National University Renal Stone Complexity Score have similar abilities in predicting stone-free rate. Further research is needed with a larger sample size or population to confirm the findings of this study. Keywords: nephrolithiasis; stone-free rate; scoring system; retrograde intrarenal surgery

Complexity in palliative care inpatients: Prevalence and relationship with the provision of care—a retrospective study

Context End-of-life palliative care aims to provide comprehensive care and can be marked by somatic, psychosocial, and spiritual distresses, requiring interdisciplinary care. However, interdisciplinary care is costly, and palliative care services, similar to all other medical services, are pressurized to be as cost-effective as possible. Objectives To describe the case complexity of palliative care inpatients, we evaluated possible correlations between complexity and the provision of care and identified complexity subgroups. Methods Patients (N = 222) hospitalized in a specialist palliative care unit in Switzerland were assessed for biopsychosocial complexity using INTERMED. Based on a chart review, INTERMED scores were determined at admission and at the end of hospitalization or at death. Descriptive statistics and Pearson’s correlation coefficients were used to estimate the association between biopsychosocial complexity and the amount and type of care provided. Principal component analysis (PCA) was conducted to explain variance and identify patient subgroups. Results Almost all patients (98.7%) qualified as complex, as indicated by INTERMED. Provision of care was positively correlated (r = 0.23, p = 0.0008) with INTERMED scores upon admission. The change in the INTERMED score during the stay correlated negatively with the provision of care (r = −0.27, p = 0.0001). PCA performed with two factors explained 49% of the total variance and identified two subgroups that differed in the INTERMED psychosocial-item scores. Conclusion Inpatients receiving specialist palliative care showed the highest complexity score of all populations assessed to date using INTERMED. Correlations between biopsychosocial complexity and care provided, and between care and decrease in complexity scores can be considered indicators of care efficiency. Patient subgroups with specific requirements (psychosocial burden) suggested that palliative care teams require specialist palliative care collaborators. Key message Palliative care provision correlates with case complexity and is effective.

Pre-implant surgery complexity for achieving implant-supported prosthetic rehabilitation in oligodontia patients: a retrospective study

IntroductionOligodontia is a rare dental developmental pathology that requires prolonged, complex and multidisciplinary treatment. Although bone augmentation is frequently required during a complete implant treatment of oligodontia. Therefore, we evaluated the ability to predict pre-implant surgery complexity based on age, number of missing teeth, and number of implants required to achieve implant-supported prosthetic rehabilitation.Material and methodsThis retrospectively registered study included all patients who underwent surgical treatment for oligodontia in our Oral and Maxillofacial Surgery Department between January 2012 and May 2023. Demographic data, number and location of missing teeth, pre- and per-implant surgical procedures, and the number of planned implants were recorded. A quantitative variable called “complexity score of pre-implant surgery” was created. This 10-point score was calculated by adding one point for each preimplant surgical procedure registered. A simple linear regression was calculated to explain the number of targeted implants based on number of missing teeth. A multiple linear regression model was used to explain the complexity score of pre-implant surgery and age, number of missing teeth and number of targeted implants.Results119 oligodontia patients were included in the study. The median number of tooth agenesis was 10. A total of 825 implants were placed, 14 (1.7%) of which failed. A significant regression equation was used (F(1,118) = 1098,338; p < 0.0001) to explain the number of targeted implants based on number of missing teeth, with a R2 of 0.903. A significant regression equation was found (F(3,116) = 107,229; p < 0.0001) to explain the complexity score of pre-implant surgery and age, number of missing teeth and number of targeted implants, with a R2 of 0.735.DiscussionThese results based on patient data indicate that age, number of missing teeth and number of targeted implants could reliably explain the complexity of pre-implant surgery.

"How well do we know our patients?": Further validation of a complexity rating scale for HIV.

Despite advances in the management and treatment of HIV, identifying risks for disengagement are essential to maximize positive outcomes. The current study investigated the validity of the Clinical Complexity Rating Scale for HIV (CCRS-HIV), a risk-prediction tool, by assessing agreement between patient and clinician scores of patient complexity. 207 patients completed the patient version of the CCRS-HIV (CCRS-HIVP), and six Attending Medical Officers (AMOs) caring for those individuals completed the original clinician version (CCRS-HIVC). Kappa statistics, sensitivity and specificity were used to assess patient-clinician agreement. Patient-clinician agreement was highest for problematic crystal methamphetamine use (86%), polypharmacy (84%) and other physical health concerns (67%). Cut-offs of 40 and 45 for the total CCRS-HIV score were identified as most appropriate, with high sensitivity (79.31% and 76.0% respectively). Overall agreement between the clinician and patient complexity scores was high. These findings provide further evidence of the validity of the scale. The study demonstrates that the unique role of AMOs at the center contributes to them knowing their patients well, allowing them to manage and refer when required for interdisciplinary care which likely contributes to their ongoing engagement in care and may account for the high level of agreement.

Scalability and performance of decision tree for cardiovascular disease prediction

&lt;span lang="EN-US"&gt;As one of the most common types of disease, cardiovascular disease is a serious health concern worldwide. Early detection is crucial for successful treatment and improved survival rates. The decision tree is a robust classifier for predicting the risk of cardiovascular disease and getting insights that would assist in making clinical decisions. However, selecting a better model for cardiovascular disease could be challenging due to scalability issues. Hence, this study examines the scalability and performance of decision trees for cardiovascular disease prediction. The study evaluated the performance of a decision tree for predicting cardiovascular disease. The performance evaluation was carried out by employing a confusion matrix, cross-validation score, model complexity, and training score for varying sizes of training samples. The experiment depicted that, the decision tree model was 88.8% accurate in predicting the presence or absence of cardiovascular disease. Therefore, the implementation of the decision tree is beneficial for the prediction and early detection of heart disease events in patients.&lt;/span&gt;

Assessing robotic-assisted surgery versus open approach in penetrating Crohn's disease: advantages and outcomes in ileocolic resection.

Penetrating Crohn's disease (CD) often necessitates surgical intervention, with the open approach traditionally favored. Robotic-assisted surgery offers potential benefits but remains understudied in this complex patient population. Additionally, the lack of standardized surgical complexity scoring in CD hinders research and comparisons. We retrospectively analyzed adult patients with penetrating CD who underwent either robotic-assisted ileocolic resection (RICR) or open ileocolic resection (OICR) at our institution from January 2007 to December 2021. We assessed endpoints, including length of stay, complications, readmissions, reoperations, and other perioperative outcomes. RICR demonstrated safety outcomes comparable to OICR. Importantly, RICR patients experienced significantly reduced estimated blood loss (p < 0.0001), shorter hospital stays (median 4.5days versus 6.9days; p = 0.01), lower surgical site infection rates (0% versus 15.4%; p = 0.01), and decreased 30-day readmission rates (0% versus 15.4%; p = 0.01). Linear regression analysis revealed the need for additional strictureplasties (coefficient: 84.8; p = 0.008), colonic resections (coefficient: 41.7; p = 0.008), and estimated blood loss (coefficient: 0.07; p = 0.002) independently correlated with longer operative times). Robotic-assisted surgery appears to be a safe and potentially beneficial alternative for the surgical management of penetrating CD, offering advantages in perioperative outcomes reducing length of stay, blood loss, surgical site infection rates, and readmission rates. Further validation with larger cohorts is warranted.

Resource management and capacity planning for clinical trial sites

Background: Since 2020, the number of registered clinical trials has surged by over 30%, significantly increasing the demand for skilled coordinators. Despite this growth, a national shortage of qualified coordinators remains, driven by escalating responsibilities and workloads. Effective resource management is crucial for retention. While the Ontario Protocol Assessment Level (OPAL) helps quantify trial complexity, it overlooks key factors such as organizational structure and budget constraints that impact coordinator productivity. This project aims to refine the OPAL score by integrating it with longitudinal coordinator effort data, improving resource allocation, operational efficiency, and job satisfaction, thereby reducing burnout and turnover. Aim: The aim of this study was to reduce burnout and turnover, ultimately contributing to the overall success of clinical trials.Methods: Actively enrolling interventional studies with corresponding coordinator effort tracking from June 1, 2022, to December 1, 2022, were included in the database. Protocols were graded using an adapted protocol assessment tool. Descriptive statistics compared protocol characteristics to the adapted assessment score and tracked coordinator hours, while Student’s t-test and univariate analysis evaluated differences in continuous variables. Linear regression analysis assessed the association between the adapted score and the coordinator effort. Results: Seven protocols were analyzed: five (71%) were federally funded, two (29%) were industry-sponsored; four (57%) were behavioral interventions, and three (43%) were drug studies. Significant differences were observed between industry-sponsored and federally funded studies (7.25 ± 1.77 vs. 6.45 ± 1.65; P &lt; 0.0001) and between behavioral interventions and drug studies (6.88 ± 1.56 vs. 6.42 ± 1.91; P &lt; 0.0001). Linear regression revealed the adapted OPAL score significantly predicted coordinator hours (β = 77.22; P = 0.01; R2 = 0.78). Conclusion: The adapted protocol complexity scores predict coordinator effort, aiding in capacity assessment and objective project distribution. Relevance for Patients: The findings from this project can inform more precise resource allocation, potentially leading to higher-quality studies and enhanced participant safety.