Predicting low cognitive ability at age 5 years using perinatal data and machine learning.

BACKGROUND: There are no early, accurate, scalable methods for identifying infants at high risk of poor cognitive outcomes in childhood. We aim to develop an explainable predictive model, using machine learning and population-based cohort data, for this purpose. METHODS: Data were from 8858 participants in the Growing Up in Ireland cohort, a nationally representative study of infants and their primary caregivers (PCGs). Maternal, infant, and socioeconomic characteristics were collected at 9-months and cognitive ability measured at age 5 years. Data preprocessing, synthetic minority oversampling, and feature selection were performed prior to training a variety of machine learning models using ten-fold cross validated grid search to tune hyperparameters. Final models were tested on an unseen test set. RESULTS: A random forest (RF) model containing 15 participant-reported features in the first year of infant life, achieved an area under the receiver operating characteristic curve (AUROC) of 0.77 for predicting low cognitive ability at age 5. This model could detect 72% of infants with low cognitive ability, with a specificity of 66%. CONCLUSIONS: Model performance would need to be improved before consideration as a population-level screening tool. However, this is a first step towards early, individual, risk stratification to allow targeted childhood screening. IMPACT: This study is among the first to investigate whether machine learning methods can be used at a population-level to predict which infants are at high risk of low cognitive ability in childhood. A random forest model using 15 features which could be easily collected in the perinatal period achieved an AUROC of 0.77 for predicting low cognitive ability. Improved predictive performance would be required to implement this model at a population level but this may be a first step towards early, individual, risk stratification.

Prediction of 2-Year Cognitive Outcomes in Very Preterm Infants Using Machine Learning Methods.

Importance: Early intervention can improve cognitive outcomes for very preterm infants but is resource intensive. Identifying those who need early intervention most is important. Objective: To evaluate a model for use in very preterm infants to predict cognitive delay at 2 years of age using routinely available clinical and sociodemographic data. Design, Setting, and Participants: This prognostic study was based on the Swedish Neonatal Quality Register. Nationwide coverage of neonatal data was reached in 2011, and registration of follow-up data opened on January 1, 2015, with inclusion ending on September 31, 2022. A variety of machine learning models were trained and tested to predict cognitive delay. Surviving infants from neonatal units in Sweden with a gestational age younger than 32 weeks and complete data for the Bayley Scales of Infant and Toddler Development, Third Edition cognitive index or cognitive scale scores at 2 years of corrected age were assessed. Infants with major congenital anomalies were excluded. Exposures: A total of 90 variables (containing sociodemographic and clinical information on conditions, investigations, and treatments initiated during pregnancy, delivery, and neonatal unit admission) were examined for predictability. Main Outcomes and Measures: The main outcome was cognitive function at 2 years, categorized as screening positive for cognitive delay (cognitive index score <90) or exhibiting typical cognitive development (score ≥90). Results: A total of 1062 children (median [IQR] birth weight, 880 [720-1100] g; 566 [53.3%] male) were included in the modeling process, of whom 231 (21.8%) had cognitive delay. A logistic regression model containing 26 predictive features achieved an area under the receiver operating curve of 0.77 (95% CI, 0.71-0.83). The 5 most important features for cognitive delay were non-Scandinavian family language, prolonged duration of hospitalization, low birth weight, discharge to other destination than home, and the infant not receiving breastmilk on discharge. At discharge from the neonatal unit, the full model could correctly identify 605 of 650 infants who would have cognitive delay at 24 months (sensitivity, 0.93) and 1081 of 2350 who would not (specificity, 0.46). Conclusions and Relevance: The findings of this study suggest that predictive modeling in neonatal care could enable early and targeted intervention for very preterm infants most at risk for developing cognitive impairment.

An audit of COVID-19 death reporting in counties Cork and Kerry, Ireland, winter 2021-2022.

BACKGROUND: In Ireland, a 'COVID-19 death' is defined as any death in which the decedent was COVID-19 positive and had no clear alternative cause of death unrelated to COVID-19, a definition based on World Health Organization guidance. AIMS: The objectives of this audit were to determine the proportion of COVID-19 deaths notified in the Cork/Kerry region of Ireland during winter 2021-2022 which adhered to this national definition, and to determine whether COVID-19 was deemed to be the primary cause of death, or a contributory or incidental factor. METHODS: A review of all deaths in individuals who were COVID-19 positive at the time of death notified to the Department of Public Health for Cork and Kerry between 22 November 2021 and 31 January 2022 was conducted to determine whether each death adhered to the national COVID-19 death definition. The clinical opinion on cause of death was obtained by contacting decedents' clinicians. RESULTS: Sixty deaths in individuals who were COVID-19 positive at the time of death were notified to the Department in the study period. Of deaths notified as being due to COVID-19, COVID-19 was deemed the primary cause of death, a contributory factor or an incidental factor in 72.7%, 21.8%, and 5.5% of cases, respectively. Most (93.3%) notified deaths adhered to the national COVID-19 death definition. CONCLUSIONS: The COVID-19 death definition in Ireland may require revision so it can distinguish between deaths caused by COVID-19 and those in which COVID-19 played a less direct role. The current COVID-19 mortality reporting system may also need updating to capture more clinical nuance.

Big data, machine learning, and population health: predicting cognitive outcomes in childhood.

The application of machine learning (ML) to address population health challenges has received much less attention than its application in the clinical setting. One such challenge is addressing disparities in early childhood cognitive development-a complex public health issue rooted in the social determinants of health, exacerbated by inequity, characterised by intergenerational transmission, and which will continue unabated without novel approaches to address it. Early life, the period of optimal neuroplasticity, presents a window of opportunity for early intervention to improve cognitive development. Unfortunately for many, this window will be missed, and intervention may never occur or occur only when overt signs of cognitive delay manifest. In this review, we explore the potential value of ML and big data analysis in the early identification of children at risk for poor cognitive outcome, an area where there is an apparent dearth of research. We compare and contrast traditional statistical methods with ML approaches, provide examples of how ML has been used to date in the field of neurodevelopmental disorders, and present a discussion of the opportunities and risks associated with its use at a population level. The review concludes by highlighting potential directions for future research in this area. IMPACT: To date, the application of machine learning to address population health challenges in paediatrics lags behind other clinical applications. This review provides an overview of the public health challenge we face in addressing disparities in childhood cognitive development and focuses on the cornerstone of early intervention. Recent advances in our ability to collect large volumes of data, and in analytic capabilities, provide a potential opportunity to improve current practices in this field. This review explores the potential role of machine learning and big data analysis in the early identification of children at risk for poor cognitive outcomes.

Predicting Low Cognitive Ability at Age 5-Feature Selection Using Machine Learning Methods and Birth Cohort Data.

Objectives: In this study, we applied the random forest (RF) algorithm to birth-cohort data to train a model to predict low cognitive ability at 5 years of age and to identify the important predictive features. Methods: Data was from 1,070 participants in the Irish population-based BASELINE cohort. A RF model was trained to predict an intelligence quotient (IQ) score ≤90 at age 5 years using maternal, infant, and sociodemographic features. Feature importance was examined and internal validation performed using 10-fold cross validation repeated 5 times. Results The five most important predictive features were the total years of maternal schooling, infant Apgar score at 1 min, socioeconomic index, maternal BMI, and alcohol consumption in the first trimester. On internal validation a parsimonious RF model based on 11 features showed excellent predictive ability, correctly classifying 95% of participants. This provides a foundation suitable for external validation in an unseen cohort. Conclusion: Machine learning approaches to large existing datasets can provide accurate feature selection to improve risk prediction. Further validation of this model is required in cohorts representative of the general population.

The predictive value of the ages and stages questionnaire in late infancy for low average cognitive ability at age 5.

AIM: This retrospective, longitudinal study examined the predictive value of the ages and stages questionnaire (ASQ) in late infancy for identifying children who progressed to have low cognitive ability at 5 years of age. METHODS: The ASQ was performed on 755 participants from the Irish BASELINE birth cohort at 24 or 27 months of age. Intelligence quotient was measured at age 5 with the Kaufmann Brief Intelligence Test, Second Edition, and low cognitive ability was defined as a score more than 1 standard deviation below the mean. The ASQ's predictive value was examined, together with other factors associated with low cognitive ability at 5 years. RESULTS: When the ASQ was performed at 24 or 27 months, the overall sensitivity for identifying low cognitive ability at 5 years was 20.8% and the specificity was 91.1%. Using a total score cut-off point increased the sensitivity to 46.6% and 71.4% at 24 and 27 months, but specificity fell to 74.1% and 67.2%, respectively. After adjusting for ASQ performance, maternal education and family income were strongly associated with cognitive outcomes at 5 years. CONCLUSION: The ASQ did not detect the majority of children with low cognitive ability at age 5. Alternative methods need investigation.

Below Average Cognitive Ability-An under Researched Risk Factor for Emotional-Behavioural Difficulties in Childhood.

Children with below average cognitive ability represent a substantial yet under-researched population for whom cognitive and social demands, which increase in complexity year by year, may pose significant challenges. This observational study examines the longitudinal relationship between early cognitive ability and emotional-behavioral difficulties (EBDs) between the age of three and nine. Participants include 7134 children from the population-based cohort study growing up in Ireland. Cognitive ability was measured at age three using the Picture Similarities Scale. A t-score one to two standard deviations below the mean was defined as below average cognitive ability (n = 767). EBDs were measured using the Strengths and Difficulties Questionnaire (SDQ) at three, five, and nine years of age. Generalized linear mixed models and logistic regression were used to examine the relationship. Below average cognitive ability was an independent predictor of higher longitudinal SDQ scores. After adjustment, children with below average cognitive ability were 1.39 times more likely (AOR 1.39, 95% CI 1.17-1.66, p < 0.001) to experience a clinically significant EBD between the ages of three to nine years. This study demonstrates the increased risk of EBDs for children with below average cognitive ability. A scalable method of early identification of at-risk children should be a research priority for public health, enabling early intervention for cognitive and adaptive outcomes.

An Evaluation of the Impact of a Multicomponent Stop Smoking Intervention in an Irish Prison.

The disproportionately high prevalence of tobacco use among prisoners remains an important public health issue. While Ireland has well-established legislative bans on smoking in public places, these do not apply in prisons. This study evaluates a multi-component tobacco control intervention in a medium security prison for adult males in Ireland. A stop-smoking intervention, targeting staff and prisoners, was designed, implemented, and evaluated with a before-and-after study. Analysis was conducted using McNemar's test for paired binary data, Wilcoxon signed rank test for ordinal data, and paired T-tests for continuous normal data. Pre-intervention, 44.3% (n = 58) of the study population were current smokers, consisting of 60.7% of prisoners (n = 51) and 15.9% of staff (n = 7). Post-intervention, 45.1% of prisoners (n = 23/51) and 100% of staff (n = 7/7) who identified as current smokers pre-intervention reported abstinence from smoking. Among non-smokers, the proportion reporting being exposed to someone else's cigarette smoke while being a resident or working in the unit decreased from 69.4% (n = 50/72) pre-intervention to 27.8% (n = 20/72) post-intervention (p < 0.001). This multicomponent intervention resulted in high abstinence rates, had high acceptability among both staff and prisoners, and was associated with wider health benefits across the prison setting.

E-Cigarette-Only and Dual Use among Adolescents in Ireland: Emerging Behaviours with Different Risk Profiles.

E-cigarette-only use and dual-use are emerging behaviours among adolescent nicotine product users which have not yet been sufficiently explored. This study examines the prevalence of, and the factors associated with, nicotine product use in adolescence. The study is a cross-sectional analysis of the 2018 Planet Youth survey completed by 15-16 year olds in the West of Ireland in 2018. The outcome of interest was current nicotine product use, defined as use at least once in the past 30 days. A main effects multinomial logistic regression model was used to examine the association between potential risk and protective factors and nicotine product use. Among 4422 adolescents 22.1% were current nicotine product users, consisting of 5.1% e-cigarette only users, 7.7% conventional cigarette only users, and 9.3% dual-users. For risk factors, the odds of association were weaker for e-cigarette only use compared to conventional cigarette and dual use. Participating in team sport four times/week or more significantly reduced the odds of conventional cigarette and dual use but had no association with e-cigarette only use (Cig: adjusted odds ratio (AOR) 0.63, 95% confidence interval (CI) 0.44-0.90; Dual-use: AOR 0.63, 95% CI 0.43-0.93). Similarly, having higher value for conventional social norms reduced the odds of conventional cigarette and dual use but not e-cigarette only use. This is the first study to show, among a generalisable sample, that dual-use is the most prevalent behaviour among adolescent nicotine product users in Ireland. Risk factor profiles differ across categories of use and prevention initiatives must be cognisant of this.

Physical activity and emotional-behavioural difficulties in young people: a longitudinal population-based cohort study.

BACKGROUND: There is growing concern around youth mental health. A population health approach to improve mental health must address, among other issues, economic insecurity, access to housing and education, harm reduction from substance use. As a universal public health intervention, increasing physical activity at a population level may have an important role in our approach. The aim of this study was to examine the longitudinal association between physical activity patterns between childhood and early adolescence and emotional-behavioural difficulties in later adolescence. METHODS: This study was based on data from the '98 Child cohort of the Growing Up in Ireland Study. Participants were categorized according to physical activity levels at ages 9 and 13. Emotional-behavioural difficulties at age 17 were measured using the parent-reported Strengths and Difficulties Questionnaire. Logistic regression was used to examine the association between physical activity and emotional-behavioural outcomes. RESULTS: Among 4618 participants included in the regression model, those categorized as Inactive (n=1607) or Reducer (n=1662) were more than twice as likely to have emotional-behavioural difficulties at age 17 compared with those who were Active [adjusted odds ratio (AOR) 2.1, 95% CI 1.46-3.01, P<0.001; AOR 1.93, 95% CI 1.34-2.76, P<0.001, respectively]. Among those with emotional-behavioural difficulties at baseline (n=525), those categorized as Active had 2.3-fold reduced odds for emotional-behavioural problems at age 17 compared with those who were Inactive (AOR 0.43, 95% CI 0.23-0.78, P=0.006). CONCLUSIONS: Increasing physical activity among adolescents is a safe and sustainable public health intervention associated with improved mental health.

Physical activity and mental health in an Irish population.

BACKGROUND: Physical activity represents a modifiable behaviour which may be associated with increased likelihood of experiencing positive mental health. AIMS: The aim of this study was to examine the association between self-rated physical activity and subjective indicators of both positive and negative mental health in an Irish adult population. METHODS: Based on data from a population-based, observational, cross-sectional study, participants were categorised using the International Physical Activity Questionnaire (IPAQ) into those who reported that they did and did not meet recommended physical activity requirements. Self-reported positive and negative mental health indicators were assessed using the Energy and Vitality Index (EVI) and the Mental Health Index-5 (MHI-5) from the SF-36 Health Survey Instrument, respectively. Binary logistic regression was used to identify variables independently associated with self-reported positive and negative mental health. RESULTS: A total of 7539 respondents were included in analysis. Overall, 32% reported that they met recommended minimal physical activity requirements. Self-reported positive and negative mental health were reported by 16 and 9% of respondents, respectively. Compared with those who reported meeting-recommended physical activity requirements, those performing no physical activity were three times less likely to report positive mental health (adjusted odds ratio (OR) 0.39, 95% confidence interval (CI) 0.28-0.55) and three times more likely to report negative mental health (OR 3.27, 95% CI 2.38-4.50). CONCLUSION: Compared with those who do not, those who report meeting-recommended physical activity requirements are more and less likely to report experiencing positive and negative mental health, respectively. Future policy development around physical activity should take cognisance of the impact of this activity on both physical and mental health outcomes.

Depolarized Hepatocytes Express the Stem/Progenitor Cell Marker Neighbor of Punc E11 After Bile Duct Ligation in Mice.

There is a medical need of biomarkers for disease stratification in cholestatic liver diseases that come along with changes in hepatocyte polarity. Neighbor of Punc E11 (Nope) is an oncofetal marker that is lost after final differentiation and polarization of hepatocytes. We analyzed the expression pattern of Nope and connexin (Cx) 26 as markers of hepatocyte polarization during murine liver development as well as in adult liver with or without bile duct ligation (BDL) by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR), western blotting (WB), and immunohistochemistry. Nope is highly expressed in fetal and postnatal liver but barely detectable thereafter. Cx26, however, is much higher expressed in adult than in fetal liver. Postnatally, Nope is directed to the sinusoidal membrane of early hepatocytes while Cx26 remains distributed over the whole membrane indicating limited polarization. In the adult liver, only Cx26 is detectable and restricted to the bile canalicular domain indicating fully polarized hepatocytes. After BDL, Nope is again >300-fold upregulated while Cx26 is reduced rapidly. By immunohistochemistry, Nope identifies a subset of hepatocytes with randomly distributed Cx26. In summary, Nope identifies depolarized adult hepatocytes after cholestatic liver injury resembling early postnatal hepatocytes. Therefore, Nope might be a valuable histochemical biomarker allowing stage-specific stratifications in cholestatic liver diseases.

Insufficient evidence of benefit regarding mortality due to albumin substitution in HCC-free cirrhotic patients undergoing large volume paracentesis.

BACKGROUND: Current guidelines for clinical practice recommend the infusion of human albumin after large volume paracentesis. After inspecting the current evidence behind this recommendation, we decided to conduct a systematic review and meta-analysis in order to address the effect of albumin on mortality and morbidity in the context of large volume paracentesis. METHODS: We performed a comprehensive search of large databases and abstract books of conference proceedings up to March 15th 2016 for randomized controlled trials, testing the infusion of human albumin against alternatives (vs no treatment, vs plasma expanders; vs vasoconstrictors) in HCC-free patients suffering from cirrhosis. We analyzed these trials with regard to mortality, changes in plasma renin activity (PRA), hyponatremia, renal impairment, recurrence of ascites with consequential re-admission into hospital and additional complications. We employed trial sequential analysis in order to calculate the number of patients required in controlled trials to be able to determine a statistically significant advantage of the administration of one agent over another with regard to mortality. RESULTS: We were able to include 21 trials totaling 1277 patients. While the administration of albumin prevents a rise in PRA as well as hyponatremia, no improvement in strong clinical endpoints such as mortality could be demonstrated. Trial sequential analysis showed that at least 1550 additional patients need to be recruited into RCTs and analyzed with regard to this question in order to detect or disprove a 25% mortality effect. CONCLUSIONS: There is insufficient evidence that the infusion of albumin after LVP significantly lowers mortality in HCC-free patients with advanced liver disease.

Elevated liver fibrosis index FIB-4 is not reliable for HCC risk stratification in predominantly non-Asian CHB patients.

We aimed to validate the liver fibrosis index FIB-4 as a model for risk stratification of hepatocellular carcinoma development in predominantly non-Asian patients with chronic hepatitis B infection seen at a tertiary referral center in Germany.We retrospectively analyzed 373 adult patients with chronic hepatitis B infection. Patient demographics, hepatitis B markers, antiviral treatment, laboratory parameters, results from liver imaging and histology were recorded. Patients were divided into 2 groups according to their FIB-4 levels and their hazard ratios for developing hepatocellular carcinoma were analyzed adjusted for age, sex, body mass index, alcohol consumption, and antiviral medication.Median follow-up was 8.7 years (range 1-21.3 years), 93% of patients were of non-Asian origin, and 64% were male. Compared with patients with a low FIB-4 (<1.25) patients with FIB-4 ≥1.25 showed a hazard ratio for incidence of hepatocellular carcinoma of 3.03 (95% confidence interval (CI): 1.24-7.41) and an adjusted hazard ratio of 1.75 (95% CI: 0.64-4.74). Notably, 68% of patients with liver cirrhosis and 68% of those who developed HCC during observation had a low FIB-4 (<1.25).We could not confirm that a FIB-4 value ≥1.25 is a reliable clinical indicator for incidence of hepatocellular carcinoma in predominantly non-Asian patients with chronic hepatitis B. Further studies in geographically and ethnically diverse populations are needed to prove its utility as a predictive tool.

Factors associated with reclassification of hyperplastic polyps after pathological reassessment from screening and surveillance colonoscopies.

INTRODUCTION: A substantial interobserver variation in the differential diagnosis of hyperplastic polyps (HPs) and sessile or traditional serrated adenomas (SSAs/TSAs) has been described. METHODS: The aim of this study is to determine the magnitude of reclassification of HPs and associated factors after pathological reassessment of specimens from screening and surveillance colonoscopies, and to estimate its consequences for follow-up recommendations. RESULTS: Among 1694 screening and surveillance colonoscopies, a total of 536 polyps were initially diagnosed as HPs and remained unchanged in 88.5% (n = 474), whereas 7.6 (n = 41) and 1.1% (n = 6) were reclassified as SSA and TSA, respectively. Compared to definite HPs, SSAs were found more frequently in men than in women (82.9 vs. 61.2%, p < 0.05), and in individuals ≥65.0 years (51.2 vs. 31.6%, p = 0.05). Also, more SSAs were >5 mm in size (36.6 vs. 6.3%, p < 0.05) and were localized in the proximal colon (31.7 vs. 11.8%, p < 0.05). In a mixed model analysis, age ≥65.0 years (OR 4.13, 95% CI 1.22-14.2), snare polypectomy (OR 23.6, 95% CI 4.86-115), and coincident advanced adenomas (OR 7.56, 95% CI 1.31-43.5) were significantly (p < 0.05) associated with reclassification to SSAs. Only 0.53% of patients had received false recommendations for follow-up visits based on the incorrect HP diagnosis. A c.1799T>A, p.V600E BRAF mutation was detected in 21.9 % (n = 9) of reclassified SSAs. CONCLUSION: Considering these factors may be helpful in serrated lesions that are difficult to allocate. Incorrect recommendations regarding control colonoscopy intervals due to misdiagnosed HPs can explain only a small fraction of interval colorectal cancers.

A Novel Easy-to-Use Prediction Scheme for Upper Gastrointestinal Bleeding: Cologne-WATCH (C-WATCH) Risk Score.

Acute upper gastrointestinal bleeding (UGIB) is the leading indication for emergency endoscopy. Scoring schemes have been developed for immediate risk stratification. However, most of these scores include endoscopic findings and are based on data from patients with nonvariceal bleeding. The aim of our study was to design a pre-endoscopic score for acute UGIB--including variceal bleeding--in order to identify high-risk patients requiring urgent clinical management. The scoring system was developed using a data set consisting of 586 patients with acute UGIB. These patients were identified from the emergency department as well as all inpatient services at the University Hospital of Cologne within a 2-year period (01/2007-12/2008). Further data from a cohort of 322 patients who presented to our endoscopy unit with acute UGIB in 2009 served for external/temporal validation.Clinical, laboratory, and endoscopic parameters, as well as further data on medical history and medication were retrospectively collected from the electronic clinical documentation system. A multivariable logistic regression was fitted to the development set to obtain a risk score using recurrent bleeding, need for intervention (angiography, surgery), or death within 30 days as a composite endpoint. Finally, the obtained risk score was evaluated on the validation set. Only C-reactive protein, white blood cells, alanine-aminotransferase, thrombocytes, creatinine, and hemoglobin were identified as significant predictors for the composite endpoint. Based on the regression coefficients of these variables, an easy-to-use point scoring scheme (C-WATCH) was derived to estimate the risk of complications from 3% to 86% with an area under the curve (AUC) of 0.723 in the development set and 0.704 in the validation set. In the validation set, no patient in the identified low-risk group (0-1 points), but 38.7% of patients in the high-risk group (≥ 2 points) reached the composite endpoint. Our easy-to-use scoring scheme is able to distinguish high-risk patients requiring urgent endoscopy, from low-risk cases who are suitable candidates for outpatient management or in whom endoscopy may be postponed. Based on our findings, a prospective validation of the C-WATCH score in different patient populations outside the university hospital setting seems warranted.

Circadian Variation in Arterial Blood Pressure and Glaucomatous Optic Neuropathy--A Systematic Review and Meta-Analysis.

BACKGROUND: Epidemiological studies have led to equivocal results concerning the role of arterial blood pressure as a risk factor for the development of glaucomatous damage and progressive visual field loss in glaucoma has been attributed to low nighttime blood pressure, especially when oral antihypertensives have been combined with beta-blocking eyedrops. In order to answer the question whether nocturnal blood pressure or blood pressure dip during ambulatory blood pressure monitoring are associated with progressive visual field loss we performed a systematic review and meta-analysis of studies in patients with primary open-angle glaucoma and normal tension glaucoma. METHODS: After searching MEDLINE, the Cochrane Library, and EMBASE, only 5 studies could be found reporting information on the method of ambulatory blood pressure measurements, separate data for daytime and nighttime blood pressure, definition of nocturnal blood pressure dip, and assessment of visual fields over a period of at least 2 years. RESULTS: There was no difference in mean systolic or diastolic diurnal and nocturnal blood pressure between patients with or without progressive visual field loss. The odds ratio for deteriorating visual fields over 2 years with nocturnal dips >10% in systolic or diastolic blood pressure was 3.32 (1.84-6.00) and 2.09 (1.20-3.64), respectively. Data allowing a separate analysis of over-dipping were not available. CONCLUSIONS: Nocturnal blood pressure fall is a risk factor for progressive visual field loss in glaucoma. However, prospective studies are needed to define a tolerable degree of dipping. Antihypertensive therapy in glaucomatous patients should be controlled with ambulatory blood pressure monitoring.

The use of postoperative suction drainage in total knee arthroplasty: a systematic review.

PURPOSE: The purpose of this systematic review and meta-analysis of randomised controlled trials is to assess the effectiveness of no drainage when compared to drainage in total knee arthroplasty, in terms of recovery of knee flexion, reduction in swelling, length of hospital stay and haemoglobin levels following TKA. METHODS: Six randomised controlled trials were included. RESULTS: There is no significant difference between the individuals who receive a drain and those who do not across any of the measures examined (p < 0.05). This analysis demonstrates no statistical difference in ROM [mean difference 0.03° (95 %CI -1.51 to 1.45, p = 0.64, I(2) = 0 %)]. , nor in knee circumference [mean difference 1.63 cm (95 % CI -1.07 - 4.34 cm, p = 0.34), [I(2) = 0.12]. CONCLUSION: The finding raises the possibility that drains are not required to assist in recovery following TKA.

Acoustic structure quantification ultrasound software proves imprecise in assessing liver fibrosis or cirrhosis in parenchymal liver diseases.

The present study was conducted to assess the diagnostic accuracy of Acoustic Structure Quantification (ASQ) ultrasound software in liver biopsy of patients with liver fibrosis and cirrhosis. Eighty patients (47 ± 14 y, 41 men) with chronic liver diseases underwent ultrasound examination of the liver and liver biopsy. In addition to the standard-care ultrasound examination, three valid gray-scale images were obtained for each patient. With the ASQ software, the average and peak values (Cm(2)) of each ultrasound gray-scale image were calculated and then compared with histologic fibrosis staging (F0-F4). No correlation was found between ASQ values and histologic fibrosis stage (p > 0.05). Areas under the curve for the diagnosis of no or mild fibrosis (F0 and F1), moderate/severe fibrosis (F2 and F3) and cirrhosis (F4) using average/peak Cm(2) values of small regions of interest were 0.46/0.43, 0.62/0.68 and 0.38/0.33. Determination of liver fibrosis with ASQ in its present form as an alternative approach to liver biopsy is too imprecise.