Magnitude Of Effect Estimates Research Articles

Vitamin D status of pregnant women with obesity in the UK and its association with pregnancy outcomes: a secondary analysis of the UK Pregnancies Better Eating and Activity Trial (UPBEAT) study.

Prenatal vitamin D deficiency is widely reported and may affect perinatal outcomes. In this secondary analysis of the UK Pregnancies Better Eating and Activity Trial, we examined vitamin D status and its relationship with selected pregnancy outcomes in women with obesity (BMI ≥ 30 kg/m2) from multi-ethnic inner-city settings in the UK. Determinants of vitamin D status at a mean of 17 ± 1 weeks' gestation were assessed using multivariable linear regression and reported as percent differences in serum 25-hydroxyvitamin D (25(OH)D). Associations between 25(OH)D and clinical outcomes were examined using logistic regression. Among 1089 participants, 67 % had 25(OH)D < 50 nmol/l and 26 % had concentrations < 25 nmol/l. In fully adjusted models accounting for socio-demographic and anthropometric characteristics, 25(OH)D was lower among women of Black (% difference = -33; 95 % CI: -39, -27), Asian (% difference = -43; 95 % CI: -51, -35) and other non-White (% difference = -26; 95 % CI: -35, -14) ethnicity compared with women of White ethnicity (n 1086; P < 0·001 for all). In unadjusted analysis, risk of gestational diabetes was greater in women with 25(OH)D < 25 nmol/l compared with ≥ 50 nmol/l (OR = 1·58; 95 % CI: 1·09, 2·31), but the magnitude of effect estimates was attenuated in the multivariable model (OR = 1·33; 95 % CI: 0·88, 2·00). There were no associations between 25(OH)D and risk of preeclampsia, preterm birth or small for gestational age or large-for-gestational-age delivery. These findings demonstrate low 25(OH)D among pregnant women with obesity and highlight ethnic disparities in vitamin D status in the UK. However, evidence for a greater risk of adverse perinatal outcomes among women with vitamin D deficiency was limited.

Should CINAHL be used as one of the main databases for evidence synthesis of health services intervention?

AbstractIntroductionCINAHL is not listed as one of the minimum databases for systematic review (SR) of interventions in the Methodological Expectations of the Cochrane Intervention Review.ObjectiveTo determine additional studies uniquely identified from the CINAHL search in SR of health services interventions (HSI).MethodsWe searched PubMed from inception to October 1, 2022 to identify SRs of HSI that determined clinical or humanistic outcomes of HSI and used CINAHL. Out of 5655 Systematic reviews identified, we randomly selected 374 SRs and extracted all primary studies included. We then explored the bibliographic databases in which the journals of those studies were indexed. The outcome of interest was the number of studies uniquely available in CINHAL. We also performed a subgroup analysis based on the type of HSI. We performed descriptive statistics to report the study outcomes using Excel (Microsoft 365).ResultsA total of 7550 primary studies were identified from the 374 Systematic reviews that met the inclusion criteria. Of these studies, 7380 were journal publications that have been indexed in MEDLINE/PubMed (75.1%), Scopus (74.5%), Sciences Citation Index, SCI (54.7%), Embase (48.1%), and CINAHL (34.9%). Only 83 out of 7380 (1.1%) studies were published in journals that were uniquely indexed in CINAHL. The percentage of studies that were only available in other databases was 9.7% (Scopus), 4.3% (MEDLINE/PubMed), 1.6% (SCI), and 0.3% (Embase). The number of studies that were unique to CINAHL in specific types of HSI were: 24/1570 (1.5%) for community health services, 20/1520 (1.3%) for preventive health services, 45/3624 (1.2%) for patient care, 8/1173 (0.7%) for mental health services, and 18/2804 (0.6%) for rehabilitation.ConclusionThe gain of CINAHL to identify unique primary studies for SR of HSI appears minimal. The impact of missing studies uniquely available in CINAHL on SR summary or magnitude of effect estimates from meta‐analysis requires further investigation.

Bidirectional Mendelian Randomization Study of Personality Traits Reveals a Positive Feedback Loop Between Neuroticism and Back Pain

We conducted a bidirectional Mendelian randomization study to examine the causal effects of six personality traits (anxiety, neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness) on back pain associated with health care use and the causal effect of back pain on the same risk factors. Genetic instruments for the personality traits and back pain were obtained from the largest published genome-wide association studies conducted in individuals of European ancestry. We used inverse weighted variance meta-analysis and Causal Analysis Using Summary Effect for primary analyses and sensitivity analyses to examine evidence for causal associations. We interpreted exposure-outcome associations as being consistent with a causal relationship if results of at least one primary analysis were statistically significant after accounting for multiple statistical testing (P-value < .0042), and the direction and magnitude of effect estimates were concordant between primary and sensitivity analyses. We found evidence for statistically significant bidirectional causal associations between neuroticism and back pain, with odds ratio 1.51 (95% confidence interval 1.37; 1.67) of back pain per neuroticism sum score standard deviation, P-value = 7.80e-16; and beta = .12, se = .04 of neuroticism sum score standard deviation per log odds of back pain, P-value = 2.48e-03. Other relationships did not meet our predefined criteria for causal association. PerspectiveThe significant positive feedback loop between neuroticism and back pain highlights the importance of considering neuroticism in the management of patients with back pain.

Causal effects of psychosocial factors on chronic back pain: a bidirectional Mendelian randomisation study.

Risk factors for chronic back pain (CBP) may share underlying genetic factors, making them difficult to study using conventional methods. We conducted a bi-directional Mendelian randomisation (MR) study to examine the causal effects of risk factors (education, smoking, alcohol consumption, physical activity, sleep and depression) on CBP and the causal effect of CBP on the same risk factors. Genetic instruments for risk factors and CBP were obtained from the largest published genome-wide association studies (GWAS) of risk factor traits conducted in individuals of European ancestry. We used inverse weighted variance meta-analysis (IVW), Causal Analysis Using Summary Effect (CAUSE) and sensitivity analyses to examine evidence for causal associations. We interpreted exposure-outcome associations as being consistent with a causal relationship if results with IVW or CAUSE were statistically significant after accounting for multiple statistical testing (p < 0.003), and the direction and magnitude of effect estimates were concordant between IVW, CAUSE, and sensitivity analyses. We found evidence for statistically significant causal associations between greater education (OR per 4.2years of schooling = 0.54), ever smoking (OR = 1.27), greater alcohol consumption (OR = 1.29 per consumption category increase) and major depressive disorder (OR = 1.41) and risk of CBP. Conversely, we found evidence for significant causal associations between CBP and greater alcohol consumption (OR = 1.19) and between CBP and smoking (OR = 1.21). Other relationships did not meet our pre-defined criteria for causal association. Fewer years of schooling, smoking, greater alcohol consumption, and major depressive disorder increase the risk of CBP. CBP increases the risk of greater alcohol consumption and smoking.

Palliative Care Teams Reduce Hospital Mortality and Utilization: Causal Evidence from a Quasi‐Experimental, Nationwide Evaluation in Ireland

Research ObjectiveTo evaluate the causal effect of palliative care consultation teams (PCCTs) on in‐hospital mortality and health care utilization in public hospitals in Ireland for the period 2005–2018 using a quasi‐experimental research design.Study Design Setting: Ireland is a country in north‐western Europe with a population of approximately 4.6million. The health system has both public and private provision, but the 40 acute public hospitals account for 95% &lt; of inpatient admissions and 90% &lt; of hospital deaths nationally. Population: All adults admitted to a public hospital with a primary diagnosis of advanced cancer, organ (heart, liver, kidney, lung) failure, or Alzheimer's disease. Analysis: We applied decomposed difference‐in‐differences (Goodman‐Bacon method) to exploit the implementation of PCCTs by different hospitals at different times across the study period. For each hospital we identified the year that a PCCT was founded, and so for each year allocated each hospital a treatment variable value of 1 (had a PCCT for the entirety of that year) or 0 (did not). The method then calculates a weighted average of all possible two‐group/two‐period difference‐in‐difference estimators in the data. We controlled for hospital size, type, location and socioeconomic catchment as additional predictors. Sources: We collected PCCT data by hand from each individual hospital service. Outcome data and other predictors were routinely collected administrative data from a national database.Population StudiedAll adults admitted to a public hospital with a primary diagnosis of advanced cancer, organ (heart, liver, kidney, lung) failure, or Alzheimer's disease.Principal FindingsWe had sufficient data for 34 hospitals (85% of sites, 90% &lt; relevant admissions to public hospitals in the study period). There were 600,306 eligible admissions in the data, with an overall mortality rate of 6% (N = 38,595) and a mean LOS of 10.0 days. Sixteen hospitals (47%) had a PCCT at the start of the study period and 34 hospitals (100%) had a PCCT at the end of the study period. Implementation of a PCCT was associated with a mean absolute reduction in in‐hospital mortality of 0.9% (95% CI: −1.6% to −0.2%), a proportional reduction of 10%. Implementation of a PCCT resulted in an absolute reduction in LOS of 0.86 days (95% CI: −1.3 days to −0.4 days), a proportional reduction of 8.6%. Secondary analysis of these data using validated unit costs for acute inpatient stays in Ireland suggests a mean estimated saving per admission of €1500 (~$1250) per admission.ConclusionsPCCTs improve the value of hospital care for people admitted with serious medical illness. These results were derived using quasi‐experimental methods, an important advance in a field where observational studies are at high risk of selection bias and high‐quality trials are rare. The magnitude of effect estimates is lower than reported by most previous studies. We consider the implications for future research.Implications for Policy or PracticePCCTs both reduce costs and improve outcomes for people admitted with serious illness. Services should be expanded to meet current and future needs. The optimal level of this expansion is unknown and requires further development of appropriate methods.Primary Funding SourceHealth Research Board (Ireland).

Performance of variable selection methods for assessing the health effects of correlated exposures in case–control studies

ObjectivesThere is growing recognition that simultaneously assessing multiple exposures may reduce false positive discoveries and improve epidemiological effect estimates. We evaluated the performance of statistical methods for identifying exposure–outcome associations...

The relationship between study sponsorship, risks of bias, and research outcomes in atrazine exposure studies conducted in non-human animals: Systematic review and meta-analysis

BackgroundA critical component of systematic review methodology is the assessment of the risks of bias of studies that are included in the review. There is controversy about whether funding source should be included in a risk of bias assessment of animal toxicology studies. ObjectiveTo determine whether industry research sponsorship is associated with methodological biases, the results, or conclusions of animal studies examining the effect of exposure to atrazine on reproductive or developmental outcomes. MethodsWe searched multiple electronic databases and the reference lists of relevant articles to identify original research studies examining the effect of any dose of atrazine exposure at any life stage on reproduction or development in non-human animals. We compared methodological risks of bias, the conclusions of the studies, the statistical significance of the findings, and the magnitude of effect estimates between industry sponsored and non-industry sponsored studies. ResultsFifty-one studies met the inclusion criteria. There were no differences in methodological risks of bias in industry versus non-industry sponsored studies. 39 studies tested environmentally relevant concentrations of atrazine (11 industry sponsored, 24 non-industry sponsored, 4 with no funding disclosures). Non-industry sponsored studies (12/24, 50.0%) were more likely to conclude that atrazine was harmful compared to industry sponsored studies (2/11, 18.1%) (p value=0.07). A higher proportion of non-industry sponsored studies reported statistically significant harmful effects (8/24, 33.3%) compared to industry-sponsored studies (1/11; 9.1%) (p value=0.13). The association of industry sponsorship with decreased effect sizes for harm outcomes was inconclusive. ConclusionOur findings support the inclusion of research sponsorship as a risk of bias criterion in tools used to assess risks of bias in animal studies for systematic reviews. The reporting of other empirically based risk of bias criteria for animal studies, such as blinded outcome assessment, randomization, and all animals included in analyses, needs to improve to facilitate the assessment of studies for systematic reviews.

Evaluation of contaminated drinking water and preterm birth, small for gestational age, and birth weight at Marine Corps Base Camp Lejeune, North Carolina: a cross-sectional study.

BackgroundBirths during 1968-1985 at Camp Lejeune were exposed to drinking water contaminated with trichloroethylene (TCE), tetrachloroethylene (PCE), and benzene.MethodsWe conducted a cross-sectional study to evaluate associations between residential prenatal exposure to contaminated drinking water at Camp Lejeune during 1968–1985 and preterm birth, small for gestational age (SGA), term low birth weight (TLBW), and mean birth weight (MBW) deficit. Birth certificates identified mothers residing at Camp Lejeune at delivery. We analyzed exposure data for the entire pregnancy and individual trimesters. For each period examined, births were categorized as unexposed if mothers did not reside at Camp Lejeune or if their residence on base received uncontaminated drinking water. Ground water contaminant fate/transport and distribution system models provided monthly estimated contaminant levels at residences. For PCE and TCE, the exposed group was divided into four levels: < median value, ≥ median value, ≥75th percentile, and ≥90th percentile. For benzene, the exposed group was categorized as <1 part per billion (ppb) versus ≥1 ppb because of sparse data. Magnitude of effect estimates and exposure response relationships were used to assess associations. Confidence intervals (CIs) indicated precision of estimates.ResultsFor the highest TCE exposure category during the entire pregnancy, odds ratios (ORs) were 1.5 (95% CI: 1.2, 1.9) and 1.3 (95% CI: 0.8, 2.2) for SGA and TLBW, respectively, and reduced MBW β = −78.3 g (95% CI: −115.0, −41.7). The OR =1.3 (95% CI: 1.0, 1.6) for preterm birth and the highest PCE exposure category during the entire pregnancy. Monotonic exposure-response relationships were observed for benzene exposure during the entire pregnancy and TLBW (highest category OR =1.5, 85% CI: 0.9, 2.3). Although a monotonic association between benzene and adjusted MBW difference was also observed (highest category β = −36.2 g, 95% CI: −72.3, −0.1), the association disappeared when TCE was also added to the model. We found no evidence suggesting any other associations between outcomes and exposures.ConclusionFindings suggested associations between in utero exposures to TCE and SGA, TLBW and reduced MBW; benzene and TLBW; and PCE and preterm birth.Electronic supplementary materialThe online version of this article (doi:10.1186/1476-069X-13-99) contains supplementary material, which is available to authorized users.

Predictive Factors Affecting Outcome After Cervical Laminoplasty

Systematic review. To determine whether various preoperative factors affect patient outcome after cervical laminoplasty for cervical spondylotic myelopathy (CSM) and/or ossification of posterior longitudinal ligament (OPLL). Cervical laminoplasty is a procedure designed to decompress the spinal cord by enlarging the spinal canal while preserving the lamina. Prior research has identified a variety of potential predictive factors that might affect outcomes after this procedure. A systematic search of multiple major medical reference databases was conducted to identify studies explicitly designed to evaluate the effect of preoperative factors on patient outcome after cervical laminoplasty for CSM or OPLL. Studies specifically designed to evaluate potential predictive factors and their associations with outcome were included. Only cohort studies that used multivariate analysis, enrolled at least 20 patients, and adjusted for age as a potential confounding variable were included. JOA (Japanese Orthopaedic Association), modified JOA, and JOACMEQ-L (JOA Cervical Myelopathy Evaluation Questionnaire lower extremity function section) scores were the main outcome measures. Clinical recommendations and consensus statements were made through a modified Delphi approach by applying the GRADE (Grading of Recommendation Assessment, Development and Evaluation)/AHRQ (Agency for Healthcare Research and Quality) criteria. The search strategy yielded 433 citations, of which 1 prospective and 11 retrospective cohort studies met our inclusion criteria. Overall, the strength of evidence from the 12 studies is low or insufficient for most of the predictive factors. Increased age was not associated with poorer JOA outcomes for patients with CSM, but there is insufficient evidence to make a conclusion for patients with OPLL. Increased severity of disease and a longer duration of symptoms might be associated with JOA outcomes for patients with CSM. Hill-shaped lesions might be associated with poorer JOA outcomes for patients with OPLL. There is insufficient evidence to permit conclusions regarding other predictive factors. Overall, the strength of evidence for all of the predictive factors was insufficient or low. Given that cervical myelopathy due to CSM tends to be progressive and that increased severity of myelopathy and duration of symptoms might be associated with poorer outcomes after cervical laminoplasty for CSM, it is preferable to perform laminoplasty in patients with CSM earlier rather than waiting for symptoms to get worse. Further research is needed to more clearly identify predictive factors that affect outcomes after cervical laminoplasty because there were relatively few studies identified that used multivariate analyses to control for confounding factors and many of these studies did not provide a detailed description of the multivariate analyses or the magnitude of effect estimates. EVIDENCE-BASED CLINICAL RECOMMENDATIONS: For patients with CSM, increased age is not a strong predictor of clinical neurological outcomes after laminoplasty; therefore, age by itself should not preclude cervical laminoplasty for CSM. Low. Strong. For patients with CSM, increased severity of disease and a longer duration of symptoms might be associated with poorer clinical neurological outcomes after laminoplasty; therefore, we recommend that patients be informed about this. Low. Strong. SUMMARY STATEMENTS: For patients with OPLL, hill-shaped lesions might be associated with poorer clinical neurological outcomes after laminoplasty; therefore, surgeons might consider potential benefits and risks of alternative or additional surgery.

Percentage of nonoverlapping corrected data

In the present study, we proposed a modification in one of the most frequently applied effect-size procedures in single-case data analysis: the percentage of nonoverlapping data. In contrast with other techniques, the calculus and interpretation of this procedure are straightforward and can be easily complemented by visual inspection of the graphed data. Although the percentage of nonoverlapping data has been found to perform reasonably well in N = 1 data, the magnitude of effect estimates that it yields can be distorted by trend and autocorrelation. Therefore, the data-correction procedure focuses on removing the baseline trend from data prior to estimating the change produced in the behavior as a result of intervention. A simulation study was carried out in order to compare the original and the modified procedures in several experimental conditions. The results suggest that the new proposal is unaffected by trend and autocorrelation and that it can be used in case of unstable baselines and sequentially related measurements.

The Secretory Pathway and Neuron Polarization

<h3>Objectives</h3> There is growing recognition that simultaneously assessing multiple exposures may reduce false positive discoveries and improve epidemiological effect estimates. We evaluated the performance of statistical methods for identifying exposure–outcome associations across various data structures typical of environmental and occupational epidemiology analyses. <h3>Methods</h3> We simulated a case–control study, generating 100 data sets for each of 270 different simulation scenarios; varying the number of exposure variables, the correlation between exposures, sample size, the number of effective exposures and the magnitude of effect estimates. We compared conventional analytical approaches, that is, univariable (with and without multiplicity adjustment), multivariable and stepwise logistic regression, with variable selection methods: sparse partial least squares discriminant analysis, boosting, and frequentist and Bayesian penalised regression approaches. <h3>Results</h3> The variable selection methods consistently yielded more precise effect estimates and generally improved selection accuracy compared with conventional logistic regression methods, especially for scenarios with higher correlation levels. Penalised lasso and elastic net regression both seemed to perform particularly well, specifically when statistical inference based on a balanced weighting of high sensitivity and a low proportion of false discoveries is sought. <h3>Conclusions</h3> In this extensive simulation study with multicollinear data, we found that most variable selection methods consistently outperformed conventional approaches, and demonstrated how performance is influenced by the structure of the data and underlying model.