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Frontiers in Psychiatry 2024Factors such as coronavirus neurotropism, which is associated with a massive increase in pro-inflammatory molecules and neuroglial reactivity, along with experiences of...
INTRODUCTION
Factors such as coronavirus neurotropism, which is associated with a massive increase in pro-inflammatory molecules and neuroglial reactivity, along with experiences of intensive therapy wards, fears of pandemic, and social restrictions, are pointed out to contribute to the occurrence of neuropsychiatric conditions.
AIM
The aim of this study is to evaluate the role of COVID-19 inflammation-related indices as potential markers predicting psychiatric complications in COVID-19.
METHODS
A total of 177 individuals were examined, with 117 patients from a temporary infectious disease ward hospitalized due to COVID-19 forming the experimental group and 60 patients from the outpatient department showing signs of acute respiratory viral infection comprising the validation group. The PLR index (platelet-to-lymphocyte ratio) and the CALC index (comorbidity + age + lymphocyte + C-reactive protein) were calculated. Present State Examination 10, Hospital Anxiety and Depression Scale, and Montreal Cognitive Assessment were used to assess psychopathology in the sample. Regression and Receiver operating characteristic (ROC) analysis, establishment of cutoff values for the COVID-19 prognosis indices, contingency tables, and comparison of means were used.
RESULTS
The presence of multiple concurrent groups of psychopathological symptoms in the experimental group was associated (R² = 0.28, F = 5.63, p < 0.001) with a decrease in the PLR index and a simultaneous increase in CALC. The Area Under Curve (AUC) for the cutoff value of PLR was 0.384 (unsatisfactory). For CALC, the cutoff value associated with an increased risk of more psychopathological domains was seven points (sensitivity = 79.0%, specificity = 69.4%, AUC = 0.719). Those with CALC > 7 were more likely to have disturbances in orientation (χ² = 13.6; p < 0.001), thinking (χ² = 7.07; p = 0.008), planning ability (χ² = 3.91; p = 0.048). In the validation group, an association (R² = 0.0775; p = 0.041) between CALC values exceeding seven points and the concurrent presence of pronounced anxiety, depression, and cognitive impairments was demonstrated (OR = 1.52; p = 0.038; AUC = 0.66).
DISCUSSION
In patients with COVID-19, the CALC index may be used for the risk assessment of primary developed mental disturbances in the context of the underlying disease with a diagnostic threshold of seven points.
PubMed: 38426006
DOI: 10.3389/fpsyt.2024.1341666 -
American Journal of Veterinary Research May 2024Use a referral dental clinic model to study how to calculate accurate 95% upper confidence limits for probabilities of workloads (total case duration, including turnover...
OBJECTIVE
Use a referral dental clinic model to study how to calculate accurate 95% upper confidence limits for probabilities of workloads (total case duration, including turnover time) exceeding allocated times.
ANIMALS
Dogs and cats undergoing dental treatments.
METHODS
Managerial data (procedure date and duration) collected over 44 consecutive operative workdays were used to calculate the daily anesthetist workload. Workloads were compared with a normal distribution using the Shapiro-Wilk test, serial correlation was examined by runs test, and comparisons among weekdays were made using the Kruskal-Wallis test. The 95% confidence limits for normally distributed workloads exceeding allocated times were estimated with a generalized pivotal quantity. The impact of a number of procedures was assessed with scatterplots, Pearson linear correlation coefficients, and multivariable linear regression.
RESULTS
Mean anesthetist's workload was normally distributed (Shapiro-Wilk P = .25), without serial correlation (P = .45), and without significant differences among weekdays (P = .52). Daily workload, mean 9.39 hours and SD 3.06 hours, had 95% upper confidence limit of 4.47% for the probability that exceeding 16 hours (ie, 8 hours per each of 2 tables). There was a strong positive correlation between daily workload and the end of the workday (r = .85), significantly larger than the correlation between the end of the workday and the number of procedures (r = .64, P < .0001).
CLINICAL RELEVANCE
There are multiple managerial applications in veterinary anesthesia wherein the problem is to estimate risks of exceeding thresholds of workload, including the costs of hiring a locum, scheduling unplanned add-on cases, planning for late discharge of surgical patients to owners, and coordinating anesthetist breaks.
Topics: Animals; Workload; Cats; Dogs; Veterinary Medicine; Anesthetists; Probability; Time Factors; Veterinarians
PubMed: 38408432
DOI: 10.2460/ajvr.23.09.0196 -
Global Health, Science and Practice Feb 2024Global and local health organizations track surgical system efficiency to improve surgical system performance using various efficiency metrics, such as operating room...
BACKGROUND
Global and local health organizations track surgical system efficiency to improve surgical system performance using various efficiency metrics, such as operating room (OR) output, surgical incision start time (SIST), turnover time (TOT), cancellation rate among elective surgeries, and in-hospital surgery wait time. We evaluated the surgical system efficiency and factors affecting the efficiency in health facilities across Ethiopia.
METHODS
A cross-sectional study design with retrospective record review was used to evaluate the surgical system efficiency in 163 public and private health facilities in Ethiopia from December 2020 to June 2021. Experienced, trained surgical clinicians abstracted efficiency data from service registers and patient charts using a pretested tool. A bivariable and multivariable regression analysis was conducted.
RESULTS
In the study facilities, 84.11% of the operating tables were functional, and 68,596 major surgeries were performed. The aggregate OR output in both public and private health facilities was 2 surgeries per day per OR table. Operating productivity was shown to be affected by first-case SIST (=.004). However, of the total 881 surgery incision times audited, 19.86% of the first-of-the-day elective surgeries started after 10:01 am. The SIST was strongly associated with an in-hospital wait time for surgery (=.016). The elective surgery cancellation rate was 5.2%, and aggregate mean TOT was 50.25 minutes. The mean in-hospital surgery wait time was 45.40 hours, longer than the national cutoff for wait time. In a bivariable analysis, the independent variables that demonstrated association operating room productivity were then inputted into a multivariable regression analysis model. However, none of the predictor/independent variables showed significance in the multivariable regression analysis model.
CONCLUSION
The volume of surgery and overall OR productivity in Ethiopia is low. This calls for concerted action to optimize OR efficiency and improve access to timely and safe surgical care in Ethiopia and other LMICs.
PubMed: 38336477
DOI: 10.9745/GHSP-D-22-00277 -
BioData Mining Jan 2024Nowadays, the chance of discovering the best antibody candidates for predicting clinical malaria has notably increased due to the availability of multi-sera data. The...
BACKGROUND
Nowadays, the chance of discovering the best antibody candidates for predicting clinical malaria has notably increased due to the availability of multi-sera data. The analysis of these data is typically divided into a feature selection phase followed by a predictive one where several models are constructed for predicting the outcome of interest. A key question in the analysis is to determine which antibodies should be included in the predictive stage and whether they should be included in the original or a transformed scale (i.e. binary/dichotomized).
METHODS
To answer this question, we developed three approaches for antibody selection in the context of predicting clinical malaria: (i) a basic and simple approach based on selecting antibodies via the nonparametric Mann-Whitney-Wilcoxon test; (ii) an optimal dychotomizationdichotomization approach where each antibody was selected according to the optimal cut-off via maximization of the chi-squared (χ) statistic for two-way tables; (iii) a hybrid parametric/non-parametric approach that integrates Box-Cox transformation followed by a t-test, together with the use of finite mixture models and the Mann-Whitney-Wilcoxon test as a last resort. We illustrated the application of these three approaches with published serological data of 36 Plasmodium falciparum antigens for predicting clinical malaria in 121 Kenyan children. The predictive analysis was based on a Super Learner where predictions from multiple classifiers including the Random Forest were pooled together.
RESULTS
Our results led to almost similar areas under the Receiver Operating Characteristic curves of 0.72 (95% CI = [0.62, 0.82]), 0.80 (95% CI = [0.71, 0.89]), 0.79 (95% CI = [0.7, 0.88]) for the simple, dichotomization and hybrid approaches, respectively. These approaches were based on 6, 20, and 16 antibodies, respectively.
CONCLUSIONS
The three feature selection strategies provided a better predictive performance of the outcome when compared to the previous results relying on Random Forest including all the 36 antibodies (AUC = 0.68, 95% CI = [0.57;0.79]). Given the similar predictive performance, we recommended that the three strategies should be used in conjunction in the same data set and selected according to their complexity.
PubMed: 38273386
DOI: 10.1186/s13040-024-00354-4 -
Wetlands (Wilmington, N.C.) 2024Understanding hydrological processes operating on relatively intact blanket bogs provides a scientific basis for establishing achievable restoration targets for damaged...
UNLABELLED
Understanding hydrological processes operating on relatively intact blanket bogs provides a scientific basis for establishing achievable restoration targets for damaged sites. A GIS-based hydrological model, developed to assess restoration potential of Irish raised bogs, was adapted and applied to four relatively intact blanket bogs in Ireland. The Modified Flow Accumulation Capacity (MFAC) model utilised high-resolution topographic data to predict surface wetness, based on climatic conditions, contributing catchment and local surface slope. Modifications to MFAC parameters aimed to account for differences in hydrological processes between raised bogs and blanket bogs. Application of a climatic correction factor accounted for variations in effective rainfall between the four study sites, while monitoring of water table levels indicated a log-linear relationship between MFAC values and summer water table levels and range of water table fluctuations. Deviations from the observed relationship between MFAC and water table levels were associated with hydrological pressures, such as artificial drainage or the occurrence of subsurface macropores (peat pipes), which further lowered summer water tables. Despite being effective as a predictor of relative surface wetness, the relationship between MFAC and ecological variables such as cover proved poor, pointing to the impact of past activities and damage caused by anthropogenic pressures. Findings demonstrated MFAC as an effective tool in predicting surface wetness within blanket bog-covered landscapes, thus proving useful to peatland practitioners in planning and prioritising areas for restoration.
SUPPLEMENTARY INFORMATION
The online version contains supplementary material available at 10.1007/s13157-023-01765-5.
PubMed: 38188226
DOI: 10.1007/s13157-023-01765-5 -
Scientific Reports Dec 2023This study focuses on the issue of lots resubmission in inspection processes, which often arises when the initial inspection of a lot is suspected, marked as held, or...
This study focuses on the issue of lots resubmission in inspection processes, which often arises when the initial inspection of a lot is suspected, marked as held, or not accepted. To address this problem, a novel variables sampling plan based on the coefficient of variation is proposed. The objective is to determine the sampling plan parameters that minimize the average sample number while satisfying the two-points of operating characteristic curve. Practical considerations are taken into account by providing tabulated values for the inspection sample size and acceptance criteria of the proposed plan. These tables incorporate various combinations of quality levels, considering commonly used producer's risk and consumer's risk. Furthermore, a comparative analysis between the proposed plan and a single sampling plan is conducted to highlight the advantages of the new approach. To illustrate the practical implementation of the proposed plan, an example is presented.
PubMed: 38151512
DOI: 10.1038/s41598-023-50498-2 -
Journal of the American Heart... Dec 2023The Diamond-Forrester model was used extensively to predict obstructive coronary artery disease (CAD) but overestimates probability in current populations. Coronary...
BACKGROUND
The Diamond-Forrester model was used extensively to predict obstructive coronary artery disease (CAD) but overestimates probability in current populations. Coronary artery calcium (CAC) is a useful marker of CAD, which is not routinely integrated with other features. We derived simple likelihood tables, integrating CAC with age, sex, and cardiac chest pain to predict obstructive CAD.
METHODS AND RESULTS
The training population included patients from 3 multinational sites (n=2055), with 2 sites for external testing (n=3321). We determined associations between age, sex, cardiac chest pain, and CAC with the presence of obstructive CAD, defined as any stenosis ≥50% on coronary computed tomography angiography. Prediction performance was assessed using area under the receiver-operating characteristic curves (AUCs) and compared with the CAD Consortium models with and without CAC, which require detailed calculations, and the updated Diamond-Forrester model. In external testing, the proposed likelihood tables had higher AUC (0.875 [95% CI, 0.862-0.889]) than the CAD Consortium clinical+CAC score (AUC, 0.868 [95% CI, 0.855-0.881]; =0.030) and the updated Diamond-Forrester model (AUC, 0.679 [95% CI, 0.658-0.699]; <0.001). The calibration for the likelihood tables was better than the CAD Consortium model (Brier score, 0.116 versus 0.121; =0.005).
CONCLUSIONS
We have developed and externally validated simple likelihood tables to integrate CAC with age, sex, and cardiac chest pain, demonstrating improved prediction performance compared with other risk models. Our tool affords physicians with the opportunity to rapidly and easily integrate a small number of important features to estimate a patient's likelihood of obstructive CAD as an aid to clinical management.
Topics: Humans; Coronary Artery Disease; Calcium; Coronary Angiography; Risk Assessment; Calcium, Dietary; Chest Pain; Predictive Value of Tests; Risk Factors
PubMed: 38108259
DOI: 10.1161/JAHA.123.031601 -
Gynecologic Oncology Jan 2024The International Federation of Gynecology and Obstetrics (FIGO) scoring system uses the sum of eight risk-factors to predict single-agent chemotherapy resistance in...
OBJECTIVE
The International Federation of Gynecology and Obstetrics (FIGO) scoring system uses the sum of eight risk-factors to predict single-agent chemotherapy resistance in Gestational Trophoblastic Neoplasia (GTN). To improve ease of use, this study aimed to generate: (i) streamlined models that match FIGO performance and; (ii) visual-decision aids (nomograms) for guiding management.
METHODS
Using training (n = 4191) and validation datasets (n = 144) of GTN patients from two UK specialist centres, logistic regression analysis generated two-factor models for cross-validation and exploration. Performance was assessed using true and false positive rate, positive and negative predictive values, Bland-Altman calibration plots, receiver operating characteristic (ROC) curves, decision-curve analysis (DCA) and contingency tables. Nomograms were developed from estimated model parameters and performance cross-checked upon the training and validation dataset.
RESULTS
Three streamlined, two-factor models were selected for analysis: (i) M1, pre-treatment hCG + history of failed chemotherapy; (ii) M2, pre-treatment hCG + site of metastases and; (iii) M3, pre-treatment hCG + number of metastases. Using both training and validation datasets, these models showed no evidence of significant discordance from FIGO (McNemar's test p > 0.78) or across a range of performance parameters. This behaviour was maintained when applying algorithms simulating the logic of the nomograms.
CONCLUSIONS
Our streamlined models could be used to assess GTN patients and replace FIGO, statistically matching performance. Given the importance of imaging parameters in guiding treatment, M2 and M3 are favoured for ongoing validation. In resource-poor countries, where access to specialist centres is problematic, M1 could be pragmatically implemented. Further prospective validation on a larger cohort is recommended.
Topics: Pregnancy; Female; Humans; Retrospective Studies; Gestational Trophoblastic Disease; Nomograms; Risk Factors
PubMed: 38091775
DOI: 10.1016/j.ygyno.2023.11.017 -
Therapeutics and Clinical Risk... 2023For the diagnosis of pediatric osteomyelitis, the sensitivity, specificity, and predictive value of erythrocyte sedimentation rate (ESR) were evaluated in this study. (Review)
Review
OBJECTIVE
For the diagnosis of pediatric osteomyelitis, the sensitivity, specificity, and predictive value of erythrocyte sedimentation rate (ESR) were evaluated in this study.
METHODS
A systematic computer-based search was performed for relevant articles focusing on the ESR diagnosis of pediatric osteomyelitis in PubMed, Embase, and the Cochrane Library with an inclusion criteria: 1) the diagnostic utility of ESR for diagnosing osteomyelitis patients under the age of 18;2) two-by-two contingency tables can be obtained. Case reports, review papers, and animal experiments were excluded.
RESULTS
The diagnostic meta-analysis included 8 studies involving 348 children with osteomyelitis, all of whom were tested for ESR. Diagnostic meta-analysis revealed a sensitivity and specificity of 0.90, 95% confidence interval (CI) (0.86-0.93), and 0.50 (95% CI,0.47-0.54) for ESR in pediatric osteomyelitis diagnosis, respectively. The positive likelihood ratio (LR), negative LR, and diagnostic odds ratio were 1.38,(95% CI,1.08-1.78), 0.46, (95% CI,0.26-0.73), and 3.20, (95% CI,1.33-7.69), respectively. The area under the curve (AUC) was determined to be 0.80 based on the summary receiver operating characteristic curve (SROC).
CONCLUSION
The literature on the use of ESR in pediatric osteomyelitis diagnosis was thoroughly reviewed in this study. It was also found that ESR may be useful as a biomarker for pediatric osteomyelitis diagnosis. Due to its low specificity, it should be used in combination with other markers such as C-reactive protein, neutrophil percentage, and white blood cell count.
PubMed: 38089965
DOI: 10.2147/TCRM.S440996 -
Biomedicines Nov 2023To investigate the performance of the END-PAC model in predicting pancreatic cancer risk in individuals with new-onset diabetes (NOD). (Review)
Review
OBJECTIVES
To investigate the performance of the END-PAC model in predicting pancreatic cancer risk in individuals with new-onset diabetes (NOD).
METHODS
The PRISMA statement standards were followed to conduct a systematic review. All studies investigating the performance of the END-PAC model in predicting pancreatic cancer risk in individuals with NOD were included. Two-by-two tables, coupled forest plots and summary receiver operating characteristic plots were constructed using the number of true positives, false negatives, true negatives and false positives. Diagnostic random effects models were used to estimate summary sensitivity and specificity points.
RESULTS
A total of 26,752 individuals from four studies were included. The median follow-up was 3 years and the pooled risk of pancreatic cancer was 0.8% (95% CI 0.6-1.0%). END-PAC score ≥ 3, which classifies the patients as high risk, was associated with better predictive performance (sensitivity: 55.8% (43.9-67%); specificity: 82.0% (76.4-86.5%)) in comparison with END-PAC score 1-2 (sensitivity: 22.2% (16.6-29.2%); specificity: 69.9% (67.3-72.4%)) and END-PAC score < 1 (sensitivity: 18.0% (12.8-24.6%); specificity: 50.9% (48.6-53.2%)) which classify the patients as intermediate and low risk, respectively. The evidence quality was judged to be moderate to high.
CONCLUSIONS
END-PAC is a promising model for predicting pancreatic cancer risk in individuals with NOD. The score ≥3 should be considered as optimum cut-off value. More studies are needed to assess whether it could improve early pancreatic cancer detection rate, pancreatic cancer re-section rate, and pancreatic cancer treatment outcomes.
PubMed: 38002040
DOI: 10.3390/biomedicines11113040