Psychological well-being and needs of parents and carers of children and young people with mental health difficulties: a quantitative systematic review with meta-analyses.

QUESTION: For parents of children and young people (CYP) with diagnosed mental health difficulties, what are the levels of parents' well-being and psychological need? STUDY SELECTION AND ANALYSIS: Medline, PsycINFO, EMBASE, AMED, CINAHL, Web of Science and Cochrane Library of Registered Trials were searched from inception to June 2023. INCLUSION CRITERIA: parents of CYP aged 5-18 years with formal mental health diagnosis. Data were extracted from validated measures of well-being or psychological needs with established cut-off points or from a controlled study. FINDINGS: 32 of the 73 310 records screened were included. Pooled means showed clinical range scores for one measure of depression, and all included measures of anxiety, parenting stress and general stress. Meta-analyses showed greater depression (g=0.24, 95% CI 0.11 to 0.38) and parenting stress (g=0.34, 95% CI 0.20 to 0.49) in parents of CYP with mental health difficulties versus those without. Mothers reported greater depression (g=0.42, 95% CI 0.18 to 0.66) and anxiety (g=0.73, 95% CI 0.27 to 1.18) than fathers. Narrative synthesis found no clear patterns in relation to CYP condition. Rates of parents with clinically relevant levels of distress varied. Typically, anxiety, parenting stress and general stress scored above clinical threshold. Quality appraisal revealed few studies with a clearly defined control group, or attempts to control for important variables such as parent gender. CONCLUSIONS: The somewhat mixed results suggest clinical anxiety, parenting and general stress may be common, with sometimes high depression. Assessment and support for parents of CYP with mental health problems is required. Further controlled studies, with consideration of pre-existing parental mental health difficulties are required. PROSPERO REGISTRATION NUMBER: CRD42022344453.

Chronotype and emotion processing: a pilot study testing timing of online cognitive bias modification training.

BACKGROUND: Circadian rhythms influence cognitive performance which peaks in the morning for early chronotypes and evening for late chronotypes. It is unknown whether cognitive interventions are susceptible to such synchrony effects and could be optimised at certain times-of-day. OBJECTIVE: A pilot study testing whether the effectiveness of cognitive bias modification (CBM) for facial emotion processing was improved when delivered at a time-of-day that was synchronised to chronotype. METHODS: 173 healthy young adults (aged 18-25) with an early or late chronotype completed one online session of CBM training in either the morning (06:00 hours to 10:00 hours) or evening (18:00 hours to 22:00 hours). FINDINGS: Moderate evidence that participants learnt better (higher post-training balance point) when they completed CBM training in the synchronous (evening for late chronotypes, morning for early chronotypes) compared with asynchronous (morning for late chronotypes, evening for early chronotypes) condition, controlling for pre-training balance point, sleep quality and negative affect. There was also a group×condition interaction where late chronotypes learnt faster and more effectively in synchronous versus asynchronous conditions. CONCLUSIONS: Preliminary evidence that synchrony effects apply to this psychological intervention. Tailoring the delivery timing of CBM training to chronotype may optimise its effectiveness. This may be particularly important for late chronotypes who were less able to adapt to non-optimal times-of-day, possibly because they experience more social jetlag. CLINICAL IMPLICATIONS: To consider delivery timing of CBM training when administering to early and late chronotypes. This may generalise to other psychological interventions and be relevant for online interventions where the timing can be flexible.

Changes in the prevalence of mental health problems during the first year of the pandemic: a systematic review and dose-response meta-analysis.

AIM: To describe the pattern of the prevalence of mental health problems during the first year of the COVID-19 pandemic and examine the impact of containment measures on these trends. METHODS: We identified articles published until 30 August 2021 that reported the prevalence of mental health problems in the general population at two or more time points. A crowd of 114 reviewers extracted data on prevalence, study and participant characteristics. We collected information on the number of days since the first SARS-CoV-2 infection in the study country, the stringency of containment measures and the number of cases and deaths. We synthesised changes in prevalence during the pandemic using a random-effects model. We used dose-response meta-analysis to evaluate the trajectory of the changes in mental health problems. RESULTS: We included 41 studies for 7 mental health conditions. The average odds of symptoms increased during the pandemic (mean OR ranging from 1.23 to 2.08). Heterogeneity was very large and could not be explained by differences in participants or study characteristics. Average odds of psychological distress, depression and anxiety increased during the first 2 months of the pandemic, with increased stringency of the measures, reported infections and deaths. The confidence in the evidence was low to very low. CONCLUSIONS: We observed an initial increase in the average risk of psychological distress, depression-related and anxiety-related problems during the first 2 months of the pandemic. However, large heterogeneity suggests that different populations had different responses to the challenges imposed by the pandemic.

Severe psychiatric disorders are associated with increased risk of dementia.

BACKGROUND: Individuals with psychiatric disorders have an increased risk of developing dementia. Most cross-sectional studies suffer from selection bias, underdiagnosis and poor population representation, while there is only limited evidence from longitudinal studies on the role of anxiety, bipolar and psychotic disorders. Electronic health records (EHRs) permit large cohorts to be followed across the lifespan and include a wide range of diagnostic information. OBJECTIVE: To assess the association between four groups of psychiatric disorders (schizophrenia, bipolar disorder/mania, depression and anxiety) with dementia in two large population-based samples with EHR. METHODS: Using EHR on nearly 1 million adult individuals in Wales, and from 228 937 UK Biobank participants, we studied the relationships between schizophrenia, mania/bipolar disorder, depression, anxiety and subsequent risk of dementia. FINDINGS: In Secure Anonymised Information Linkage, there was a steep increase in the incidence of a first diagnosis of psychiatric disorder in the years prior to the diagnosis of dementia, reaching a peak in the year prior to dementia diagnosis for all psychiatric diagnoses. Psychiatric disorders, except anxiety, were highly significantly associated with a subsequent diagnosis of dementia: HRs=2.87, 2.80, 1.63 for schizophrenia, mania/bipolar disorder and depression, respectively. A similar pattern was found in the UK Biobank (HRs=4.46, 3.65, 2.39, respectively) and anxiety was also associated with dementia (HR=1.34). Increased risk of dementia was observed for all ages at onset of psychiatric diagnoses when these were divided into 10-year bins. CONCLUSIONS: Psychiatric disorders are associated with an increased risk of subsequent dementia, with a greater risk of more severe disorders. CLINICAL IMPLICATIONS: A late onset of psychiatric disorders should alert clinicians of possible incipient dementia.

Missing data in emergency care: a pitfall in the interpretation of analysis and research based on electronic patient records.

Electronic patient records (EPRs) are potentially valuable sources of data for service development or research but often contain large amounts of missing data. Using complete case analysis or imputation of missing data seem like simple solutions, and are increasingly easy to perform in software packages, but can easily distort data and give misleading results if used without an understanding of missingness. So, knowing about patterns of missingness, and when to get expert data science (data engineering and analytics) help, will be a fundamental future skill for emergency physicians. This will maximise the good and minimise the harm of the easy availability of large patient datasets created by the introduction of EPRs.

Comorbid physical health burden of serious mental health disorders in 32 European countries.

BACKGROUND: Mental health disorders (MHDs) are associated with physical health disparities, but underlying excess risk and health burden have not yet been comprehensively assessed. OBJECTIVE: To assess the burden of comorbid physical health conditions (PHCs) across serious MHDs in Europe. METHODS: We estimated the relative prevalence risk of PHCs associated with alcohol use disorders (AUD), bipolar disorder (BD), depressive disorders (DD) and schizophrenia (SZ) across working-age populations of 32 European countries in 2019 based on a targeted literature review. Excess physical health burden was modelled using population-attributable fractions and country-level prevalence data. FINDINGS: We screened 10 960 studies, of which 41 were deemed eligible, with a total sample size of over 18 million persons. Relative prevalence of PHCs was reported in 54%, 20%, 15%, 5% and 7% of studies, respectively, for SZ, DD, BD, AUD or mixed. Significant relative risk estimates ranged from 1.44 to 3.66 for BD, from 1.43 to 2.21 for DD, from 0.81 to 1.97 for SZ and 3.31 for AUD. Excess physical health burden ranged between 27% and 67% of the total, corresponding to 84 million (AUD), 67 million (BD), 66 million (DD) and 5 million (SZ) PHC diagnoses in Europe. A 1% reduction in excess risk assuming causal inference could result in two million fewer PHCs across investigated MHDs. CONCLUSIONS: This is the first comprehensive study of the physical health burden of serious MHDs in Europe. The methods allow for updates, refinement and extension to other MHDs or geographical areas. CLINICAL IMPLICATIONS: The results indicate potential population health benefits achievable through more integrated mental and physical healthcare and prevention approaches.

Effectiveness of an online recovery training for employees exposed to blurred boundaries between work and non-work: Bayesian analysis of a randomised controlled trial.

BACKGROUND: Blurred work-non-work boundaries can have negative effects on mental health, including sleep. OBJECTIVES: In a randomised control trial, we aimed to assess the effectiveness of an online recovery training programme designed to improve symptoms of insomnia in a working population exposed to blurred boundaries. METHODS: 128 participants with severe insomnia symptoms (Insomnia Severity Index ≥15) and working under blurred work and non-work conditions (segmentation supplies <2.25) were randomly assigned to either the recovery intervention or a waitlist control group (WLC). The primary outcome was insomnia severity, assessed at baseline, after 2 months (T2) and 6 months (T3). FINDINGS: A greater reduction in insomnia was observed in the intervention compared with the WLC group at both T2 (d=1.51; 95% CI=1.12 o 1.91) and T3 (d=1.63; 95% CI=1.23 to 2.03]. This was shown by Bayesian analysis of covariance (ANCOVA), whereby the ANCOVA model yielded the highest Bayes factor (BF 10=3.23×e60] and a 99.99% probability. Likewise, frequentist analysis revealed significantly reduced insomnia at both T2 and T3. Beneficial effects were found for secondary outcomes including depression, work-related rumination, and mental detachment from work. Study attrition was 16% at T2 and 44% at T3. CONCLUSIONS: The recovery training was effective in reducing insomnia symptoms, work related and general indicators of mental health in employees exposed to blurred boundaries, both at T2 and T3. CLINICAL IMPLICATIONS: In addition to demonstrating the intervention's effectiveness, this study exemplifies the utilisation of the Bayesian approach in a clinical context and shows its potential to empower recipients of interventional research by offering insights into result probabilities, enabling them to draw informed conclusions. TRIAL REGISTRATION NUMBER: German Clinical Trial Registration (DRKS): DRKS00006223, https://drks.de/search/de/trial/DRKS00006223.

Suicide risk assessment tools and prediction models: new evidence, methodological innovations, outdated criticisms.

The number of prediction models for suicide-related outcomes has grown substantially in recent years. These models aim to assist in stratifying risk, improve clinical decision-making, and facilitate a personalised medicine approach to the prevention of suicidal behaviour. However, there are contrasting views as to whether prediction models have potential to inform and improve assessment of suicide risk. In this perspective, we discuss common misconceptions that characterise criticisms of suicide risk prediction research. First, we discuss the limitations of a classification approach to risk assessment (eg, categorising individuals as low-risk vs high-risk), and highlight the benefits of probability estimation. Second, we argue that the preoccupation with classification measures (such as positive predictive value) when assessing a model's predictive performance is inappropriate, and discuss the importance of clinical context in determining the most appropriate risk threshold for a given model. Third, we highlight that adequate discriminative ability for a prediction model depends on the clinical area, and emphasise the importance of calibration, which is almost entirely overlooked in the suicide risk prediction literature. Finally, we point out that conclusions about the clinical utility and health-economic value of suicide prediction models should be based on appropriate measures (such as net benefit and decision-analytic modelling), and highlight the role of impact assessment studies. We conclude that the discussion around using suicide prediction models and risk assessment tools requires more nuance and statistical expertise, and that guidelines and suicide prevention strategies should be informed by the new and higher quality evidence in the field.

Understanding effect size: an international online survey among psychiatrists, psychologists, physicians from other medical specialities, dentists and other health professionals.

BACKGROUND AND OBJECTIVE: Various ways exist to display the effectiveness of medical treatment options. This study examined various psychiatric, medical and allied professionals' understanding and perceived usefulness of eight effect size indices for presenting both dichotomous and continuous outcome data. METHODS: We surveyed 1316 participants from 13 countries using an online questionnaire. We presented hypothetical treatment effects of interventions versus placebo concerning chronic pain using eight different effect size measures. For each index, the participants had to judge the magnitude of the shown effect, to indicate how certain they felt about their own answer and how useful they found the given effect size index. FINDINGS: Overall, 762 (57.9%) participants fully completed the questionnaire. In terms of understanding, the best results emerged when both the control event rate (CER) and the experimental event rate (EER) were presented. The difference in minimal importance difference units (MID unit) was understood worst. Respondents also found CER and EER to be the most useful presentation approach while they rated MID unit as the least useful. Confidence in the risk ratio ranked high, even though it was rather poorly understood. CONCLUSIONS AND CLINICAL IMPLICATIONS: For dichotomous outcomes, presenting the effects in terms of the CER and EER could lead to the most correct interpretation. Relative measures including the risk ratio must be supplemented with absolute measures such as the CER and EER. Effects on continuous outcomes were better understood through standardised mean differences than mean differences. These can also be supplemented by dichotomised CER and EER.

Prescriptions of antidepressants and anxiolytics in France 2012-2022 and changes with the COVID-19 pandemic: interrupted time series analysis.

BACKGROUND: Depression and anxiety have increased in prevalence since the start of the COVID-19 pandemic. OBJECTIVE: To evaluate the consumption of antidepressants and anxiolytics from 2012 to 2022 and the pandemic's potential impact in France. METHODS: We conducted an interrupted time series analysis of routine drug sales data (Medic'AM) from all French outpatient pharmacies from 2012 to 2022. We investigated trends in defined daily doses of antidepressants and anxiolytics sold per 1000 inhabitants (DDD/TID) and related expenditures before and after pandemic onset and in relation with stringency of pandemic mitigation measures. Analyses were performed descriptively and using segmented linear regression, autoregressive and autoregressive integrated moving average models. FINDINGS: From 2012 to 2019, overall monthly antidepressant sales increased (+0.02 DDD/TID) while monthly anxiolytic sales decreased (-0.07 DDD/TID). With pandemic onset, there was a relevant and persisting trend increase (+0.20 DDD/TID per month) for antidepressant sales overall, with an estimated excess of 112.6 DDD/TID sold from May 2020 until December 2022. Anxiolytic sales were elevated from February 2020 throughout the pandemic but returned to expected levels by December 2022, with an estimated excess of 33.8 DDD/TID. There was no evident association between stringency and antidepressant or anxiolytic sales. CONCLUSIONS: This study showed a protracted trend increase in the consumption of antidepressants since pandemic onset, while increases in anxiolytic consumption were temporary. CLINICAL IMPLICATIONS: We provide evidence that the COVID-19 pandemic may have had long-lasting consequences on the prevalence and treatment of depression and anxiety disorders, requiring further actions by researchers and policy-makers to address this potential public mental health crisis.

Influence of study characteristics, methodological rigour and publication bias on efficacy of pharmacotherapy in obsessive-compulsive disorder: a systematic review and meta-analysis of randomised, placebo-controlled trials.

QUESTION: We examined the effect of study characteristics, risk of bias and publication bias on the efficacy of pharmacotherapy in randomised controlled trials (RCTs) for obsessive-compulsive disorder (OCD). STUDY SELECTION AND ANALYSIS: We conducted a systematic search of double-blinded, placebo-controlled, short-term RCTs with selective serotonergic reuptake inhibitors (SSRIs) or clomipramine. We performed a random-effect meta-analysis using change in the Yale-Brown Obsessive-Compulsive Scale (YBOCS) as the primary outcome. We performed meta-regression for risk of bias, intervention, sponsor status, number of trial arms, use of placebo run-in, dosing, publication year, age, severity, illness duration and gender distribution. Furthermore, we analysed publication bias using a Bayesian selection model. FINDINGS: We screened 3729 articles and included 21 studies, with 4102 participants. Meta-analysis showed an effect size of -0.59 (Hedges' G, 95% CI -0.73 to -0.46), equalling a 4.2-point reduction in the YBOCS compared with placebo. The most recent trial was performed in 2007 and most trials were at risk of bias. We found an indication for publication bias, and subsequent correction for this bias resulted in a depleted effect size. In our meta-regression, we found that high risk of bias was associated with a larger effect size. Clomipramine was more effective than SSRIs, even after correcting for risk of bias. After correction for multiple testing, other selected predictors were non-significant. CONCLUSIONS: Our findings reveal superiority of clomipramine over SSRIs, even after adjusting for risk of bias. Effect sizes may be attenuated when considering publication bias and methodological rigour, emphasising the importance of robust studies to guide clinical utility of OCD pharmacotherapy. PROSPERO REGISTRATION NUMBER: CRD42023394924.

On the use of receiver operating characteristic curve analysis to determine the most appropriate p value significance threshold.

BACKGROUND: p value is the most common statistic reported in scientific research articles. Choosing the conventional threshold of 0.05 commonly used for the p value in research articles, is unfounded. Many researchers have tried to provide a reasonable threshold for the p value; some proposed a lower threshold, eg, 0.005. However, none of the proposals has gained universal acceptance. Using the analogy between the diagnostic tests with continuous results and statistical inference tests of hypothesis, I wish to present a method to calculate the most appropriate p value significance threshold using the receiver operating characteristic curve (ROC) analysis. RESULTS: As with diagnostic tests where the most appropriate cut-off values are different depending on the situation, there is no unique cut-off for the p significance threshold. Unlike the previous proposals, which mostly suggest lowering the threshold to a fixed value (eg, from 0.05 to 0.005), the most appropriate p significance threshold proposed here, in most instances, is much less than the conventional cut-off of 0.05 and varies from study to study and from statistical test to test, even within a single study. The proposed method provides the minimum weighted sum of type I and type II errors. CONCLUSIONS: Given the perplexity involved in using the frequentist statistics in a correct way (dealing with different p significance thresholds, even in a single study), it seems that the p value is no longer a proper statistic to be used in our research; it should be replaced by alternative methods, eg, Bayesian methods.

Estimating the smallest worthwhile difference of antidepressants: a cross-sectional survey.

BACKGROUND: Approximately 30% of patients experience substantial improvement in depression after 2 months without treatment, and 45% with antidepressants. The smallest worthwhile difference (SWD) refers to an intervention's smallest beneficial effect over a comparison patients deem worthwhile given treatment burdens (harms, expenses and inconveniences), but is undetermined for antidepressants. OBJECTIVE: Estimating the SWD of commonly prescribed antidepressants for depression compared to no treatment. METHODS: The SWD was estimated as a patient-required difference in response rates between antidepressants and no treatment after 2 months. An online cross-sectional survey using Prolific, MQ Mental Health and Amazon Mechanical Turk crowdsourcing services in the UK and USA between October 2022 and January 2023 garnered participants (N=935) that were a mean age of 44.1 (SD=13.9) and 66% women (n=617). FINDINGS: Of 935 participants, 124 reported moderate-to-severe depressive symptoms but were not in treatment, 390 were in treatment and 495 reported absent-to-mild symptoms with or without treatment experiences. The median SWD was a 20% (IQR=10-30%) difference in response rates for people with moderate-to-severe depressive symptoms, not in treatment, and willing to consider antidepressants, and 25% (IQR=10-35%) for the full sample. CONCLUSIONS: Our observed SWDs mean that the current 15% antidepressant benefit over no treatment was sufficient for one in three people to accept antidepressants given the burdens, but two in three expected greater treatment benefits. IMPLICATIONS: While a minority may be satisfied with the best currently available antidepressants, more effective and/or less burdensome medications are needed, with more attention given to patient perspectives.

Rapidly scalable and low-cost public health surveillance reporting system for COVID-19.

OBJECTIVE: Data-driven innovations are essential in strengthening disease control. We developed a low-cost, open-source system for robust epidemiological intelligence in response to the COVID-19 crisis, prioritising scalability, reproducibility and dynamic reporting. METHODS: A five-tiered workflow of data acquisition; processing; databasing, sharing, version control; visualisation; and monitoring was used. COVID-19 data were initially collated from press releases and then transitioned to official sources. RESULTS: Key COVID-19 indicators were tabulated and visualised, deployed using open-source hosting in October 2022. The system demonstrated high performance, handling extensive data volumes, with a 92.5% user conversion rate, evidencing its value and adaptability. CONCLUSION: This cost-effective, scalable solution aids health specialists and authorities in tracking disease burden, particularly in low-resource settings. Such innovations are critical in health crises like COVID-19 and adaptable to diverse health scenarios.

Is the Bland-Altman plot method useful without inferences for accuracy, precision, and agreement?

ABSTRACT OBJECTIVE This study aims to propose a comprehensive alternative to the Bland-Altman plot method, addressing its limitations and providing a statistical framework for evaluating the equivalences of measurement techniques. This involves introducing an innovative three-step approach for assessing accuracy, precision, and agreement between techniques, which enhances objectivity in equivalence assessment. Additionally, the development of an R package that is easy to use enables researchers to efficiently analyze and interpret technique equivalences. METHODS Inferential statistics support for equivalence between measurement techniques was proposed in three nested tests. These were based on structural regressions with the goal to assess the equivalence of structural means (accuracy), the equivalence of structural variances (precision), and concordance with the structural bisector line (agreement in measurements obtained from the same subject), using analytical methods and robust approach by bootstrapping. To promote better understanding, graphical outputs following Bland and Altman's principles were also implemented. RESULTS The performance of this method was shown and confronted by five data sets from previously published articles that used Bland and Altman's method. One case demonstrated strict equivalence, three cases showed partial equivalence, and one showed poor equivalence. The developed R package containing open codes and data are available for free and with installation instructions at Harvard Dataverse at https://doi.org/10.7910/DVN/AGJPZH. CONCLUSION Although easy to communicate, the widely cited and applied Bland and Altman plot method is often misinterpreted, since it lacks suitable inferential statistical support. Common alternatives, such as Pearson's correlation or ordinal least-square linear regression, also fail to locate the weakness of each measurement technique. It may be possible to test whether two techniques have full equivalence by preserving graphical communication, in accordance with Bland and Altman's principles, but also adding robust and suitable inferential statistics. Decomposing equivalence into three features (accuracy, precision, and agreement) helps to locate the sources of the problem when fixing a new technique.

Validez de apariencia y racionalidad de una metodología para estudiar la causalidad en salud / Appearance and rational validity of a methodology to study causality in health

Introducción: Es objetivo fundamental de la medicina, determinar las causas que producen las enfermedades; para llevar a cabo este estudio, a finales del siglo XX se emplearon técnicas estadísticas multivariadas confiables en el análisis simultáneo de diferentes variables independientes sobre un desenlace. Objetivo: Determinar la aplicación de la validez racional y de apariencia en la metodología empleada para el estudio de la causalidad en salud. Métodos: Para evaluar si la metodología se correspondía con los requerimientos de la investigación, se aplicó la validez de apariencia para valorar los resultados obtenidos en su aplicación, específicamente, si las reglas reflejan verazmente, lo que ocurre en la práctica médica, mediante el empleo de la validez racional. Resultados: Los usuarios potenciales de la metodología la consideraron aceptable en los aspectos medidos sobre la regresión logística binaria. El mayor porcentaje de las reglas analizadas está en correspondencia con lo planteado en la literatura, pocas plantean aspectos que no se dan necesariamente en la práctica médica, pero tampoco se contradicen con la literatura. Los resultados de la validez de apariencia no fueron favorables, pues la metodología no había sido empleada antes en el contexto. En cuanto a la validez racional, se verificó un alto porcentaje de correspondencia entre lo planteado por las reglas y la literatura. Es importante tener en cuenta, que el hallazgo de algo conocido reafirma la validez de esa regla. Conclusiones: Las reglas obtenidas de la aplicación de la metodología reflejan, en general, lo que ocurre en la práctica médica.

Introduction: the fundamental objective of medicine is to determine the causes that produce diseases. At the end of the 20th century, multivariate statistical techniques were used as reliable in the simultaneous analysis of different independent variables on an outcome. Objective: to determine the application of appearance and rational validity of a methodology to study causality in health. Methods: to evaluate whether the methodology corresponded to the research requirements, appearance validity was applied to assess the results obtained in its application, specifically, if the rules accurately reflect what happens in medical practice, through the use of rational validity. Results: the potential users of the methodology considered it acceptable in the measured aspects of the binary logistic regression. The highest percentage of the rules analyzed is in correspondence with what is stated in the literature; few raise aspects that do not necessarily occur in medical practice, but they do not contradict the literature either. The results of face validity were not favourable, since the methodology had not been used before in the context. A high percentage of correspondence regarding rational validity was verified between what was stated by the rules and the literature. It is important to note that finding something known reaffirms the validity of that rule. Conclusions: the rules obtained from the application of the methodology reflect, in general, what happens in medical practice.

Accuracy of a tool to prioritise patients awaiting elective surgery: an implementation report.

STUDY OBJECTIVE: The objective of this study was to evaluate the accuracy of a new elective surgery clinical decision support system, the 'Patient Tacking List' (PTL) tool (C2-Ai(c)) through receiver operating characteristic (ROC) analysis. METHODS: We constructed ROC curves based on risk predictions produced by the tool and compared these with actual patient outcomes on a retrospective cohort of patients awaiting elective surgery. RESULTS: A total of 11 837 patients were included across three National Health Service (NHS) hospitals in England. ROC analysis revealed an area under the curve of 0.95 (95% CI 0.92 to 0.98) for mortality and 0.8 (95% CI 0.78 to 0.82) for complications. DISCUSSION: The PTL tool was successfully integrated into existing data infrastructures, allowing real-time clinical decision support and a low barrier to implementation. ROC analysis demonstrated a high level of accuracy to predict the risk of mortality and complications after elective surgery. As such, it may be a valuable adjunct in prioritising patients on surgical waiting lists.Health systems, such as the NHS in England, must look at innovative methods to prioritise patients awaiting surgery in order to best use limited resources. Clinical decision support tools, such as the PTL tool, can improve prioritisation and thus positively impact clinical care and patient outcomes. CONCLUSIONS: The high level of accuracy for predicating mortality and complications after elective surgery using the PTL tool indicates the potential for clinical decision support tools to help tackle rising waiting lists and improve surgical planning.

One-point versus two-point fixation in the management of zygoma complex fractures.

BACKGROUND: The treatment of zygoma complex fractures is of crucial importance in the field of plastic surgery. However, surgical methods to correct zygoma complex fractures, including the number of fixation sites, differ among operators. Although several studies have compared two-point and three-point fixation, no comparative research has yet been conducted on one-point versus two-point fixation using computed tomography scans of surgical results. Therefore, the present study aimed to address this gap in the literature by comparing surgical results between one-point and two-point fixation procedures. METHODS: In this study, we randomly selected patients to undergo surgery using one of two surgical methods. We analyzed patients with unilateral zygoma complex fractures unaccompanied by other fractures according to whether they underwent one-point fixation of the zygomaticomaxillary buttress or two-point fixation of the zygomaticomaxillary buttress and the zygomaticofrontal suture. We then made measurements at three points-the zygomaticofrontal suture, inferior orbital wall, and malar height-using 3-month postoperative computed tomography images and performed statistical analyses to compare the results of the two methods. RESULTS: All three measurements (zygomaticofrontal suture, inferior orbital wall, and malar height) showed significant differences (p < 0.05) between one-point and two-point fixation. Highly significant differences were found for the zygomaticofrontal suture and malar height parameters. The difference in the inferior wall measurements was less meaningful, even though it also reached statistical significance. CONCLUSION: Using three parameters in a statistical analysis of imaging findings, this study demonstrated significant differences in treatment outcomes according to the number of fixations. The results indicate that bone alignment and continuity can be achieved to a greater extent by two-point fixation instead of one-point fixation.