Shared genetic and environmental etiology between substance use disorders and suicidal behavior

Background Previous studies have demonstrated substantial associations between substance use disorders (SUD) and suicidal behavior. The current study empirically assesses the extent to which shared genetic and/or environmental factors contribute to associations between alcohol use disorders (AUD) or drug use disorders (DUD) and suicidal behavior, including attempts and death. Methods The authors used Swedish national registry data, including medical, pharmacy, criminal, and death registrations, for a large cohort of twins, full siblings, and half siblings (N = 1 314 990) born 1960–1980 and followed through 2017. They conducted twin-sibling modeling of suicide attempt (SA) or suicide death (SD) with AUD and DUD to estimate genetic and environmental correlations between outcomes. Analyses were stratified by sex. Results Genetic correlations between SA and SUD ranged from rA = 0.60–0.88; corresponding shared environmental correlations were rC = 0.42–0.89 but accounted for little overall variance; and unique environmental correlations were rE = 0.42–0.57. When replacing attempt with SD, genetic and shared environmental correlations with AUD and DUD were comparable (rA = 0.48–0.72, rC = 0.92–1.00), but were attenuated for unique environmental factors (rE = −0.01 to 0.31). Conclusions These findings indicate that shared genetic and unique environmental factors contribute to comorbidity of suicidal behavior and SUD, in conjunction with previously reported causal associations. Thus, each outcome should be considered an indicator of risk for the others. Opportunities for joint prevention and intervention, while limited by the polygenic nature of these outcomes, may be feasible considering moderate environmental correlations between SA and SUD.

Influenza Hospitalizations during Childhood in Children born Preterm

Objective: To determine if children born preterm were at increased risk of influenza hospitalization up to age five. Methods: National registry data on all children born in Norway between 2008 and 2011 was used in Cox regression models to estimate adjusted hazard ratios (aHR) for influenza hospitalizations up to age five in children born preterm (<37 pregnancy weeks). HRs were also estimated separately for very preterm (<32 weeks), early term (37-38 weeks), and post-term (≥42 weeks) children. Results: Among 238 628 children born in Norway from January 2008 to December 2011, 15 086 (6.3%) were born preterm. There were 754 (0.3%) children hospitalized with influenza before age five. The rate of hospitalizations in children born preterm was 1.4 per 10 000 person-years (95% confidence interval [CI]: 1.1-1.7), and 0.6 per 10 000 person-years (95% CI: 0.5-0.6) in children born at term (≥37 weeks). Children born preterm had a higher risk of influenza hospitalization before age 5: aHR 2.33 (95% CI: 1.85-2.93). The risk increased with decreasing gestational age and was highest among those born very preterm; aHR 4.07 (95% CI: 2.63-6.31). Compared to children born at 40-41 weeks, children born early term also had an elevated risk of influenza hospitalization; aHR (37 weeks) 1.89 (95% CI: 1.43-2.40), aHR (38 weeks) 1.43 (95% CI: 1.15-1.78). Conclusion: Children born preterm had a higher risk of influenza hospitalizations before age five. An elevated risk was also present among children born at an early term. Children born preterm would benefit from influenza vaccinations.

Symptom burden in multimorbidity: a population-based combined questionnaire and registry study from Denmark

ObjectivePatients with multimorbidity may carry a large symptom burden. Symptoms are often what drive patients to seek healthcare and they also assist doctors with diagnosis. We examined whether symptom burden is additive in people with multimorbidity compared with people with a single morbidity.DesignThis is a longitudinal cohort study drawing on questionnaire and Danish national registry data. Multimorbidity was defined as having diagnoses from at least two out of ten morbidity groups. Associations between morbidity groups and symptom burden were estimated with multivariable models.ParticipantsIn 2012, 47 452 participants from the Danish Symptom Cohort answered a questionnaire about symptoms (36 symptoms in total), including whether symptoms were affecting their daily activities (impairment score) and their worries about present symptoms (worry score) (the highest score among the 36 symptoms on a 0–4 scale).Main outcome measureThe primary outcome was symptom burden.ResultsParticipants without morbidity reported 4.77 symptoms (out of 36 possible). Participants with one, two or three morbidities reported more symptoms than patients without morbidity (0.95 (CI 0.86 to 1.03), 1.87 (CI 1.73 to 2.01) and 2.89 (CI 2.66 to 3.12), respectively). Furthermore, they reported a higher impairment score (0.36 (0.32 to 0.39), 0.65 (0.60 to 0.70) and 1.06 (0.98 to 1.14)) and a higher worry score (0.34 (0.31 to 0.37), 0.62 (0.57 to 0.66) and 1.02 (0.94 to 1.10)) than participants without morbidity. In 45 possible combinations of multimorbidity (participants with two morbidities), interaction effects were additive in 37, 41 and 36 combinations for the number of symptoms, impairment score and worry score, respectively.ConclusionParticipants without morbidity reported a substantial number of symptoms. Having a single morbidity or multimorbidity resulted in approximately one extra symptom for each extra morbidity. In most combinations of multimorbidity, symptom burden was additive.

Linkage of Australian national registry data using a statistical linkage key

Background Data from clinical registries may be linked to gain additional insights into disease processes, risk factors and outcomes. Identifying information varies from full names, addresses and unique identification codes to statistical linkage keys to no direct identifying information at all. A number of databases in Australia contain the statistical linkage key 581 (SLK-581). Our aim was to investigate the ability to link data using SLK-581 between two national databases, and to compare this linkage to that achieved with direct identifiers or other non-identifying variables. Methods The Australian and New Zealand Society of Cardiothoracic Surgeons database (ANZSCTS-CSD) contains fully identified data. The Australian and New Zealand Intensive Care Society database (ANZICS-APD) contains non-identified data together with SLK-581. Identifying data is removed at participating hospitals prior to central collation and storage. We used the local hospital ANZICS-APD data at a large single tertiary centre prior to deidentification and linked this to ANZSCTS-CSD data. We compared linkage using SLK-581 to linkage using non-identifying variables (dates of admission and discharge, age and sex) and linkage using a complete set of unique identifiers. We compared the rate of match, rate of mismatch and clinical characteristics between unmatched patients using the different methods. Results There were 1283 patients eligible for matching in the ANZSCTS-CSD. 1242 were matched using unique identifiers. Using non-identifying variables 1151/1242 (92.6%) patients were matched. Using SLK-581, 1202/1242 (96.7%) patients were matched. The addition of non-identifying data to SLK-581 provided few additional patients (1211/1242, 97.5%). Patients who did not match were younger, had a higher mortality risk and more non-standard procedures vs matched patients. The differences between unmatched patients using different matching strategies were small. Conclusion All strategies provided an acceptable linkage. SLK-581 improved the linkage compared to non-identifying variables, but was not as successful as direct identifiers. SLK-581 may be used to improve linkage between national registries where identifying information is not available or cannot be released.

Results from the first Kuwait National Bariatric Surgery Report

Background Currently, more than 30% of the population in the gulf demonstrate a body mass index (BMI) exceeding 30. This burden of obesity has proven to take a toll on the population; therefore, we created the first Kuwait National Bariatric Surgery Database to report on bariatric surgeries performed in Kuwait. Methods Data was collected from the six public hospitals in Kuwait. This data was then submitted to a merged National Registry. Data web portal were used to upload, merge, and analyze the data. Results The average age for participants was 32.6 years. The average preoperative BMI was 45.9 kg/m2 for males and 43.3 kg/m2 for females. 16.4% of males and 12.3% of females presented with type 2 diabetes, while the most prevalent obesity related disease was a poor functional status in both males and females (90.8% and 90.5%, respectively). Most procedures performed in Kuwait are sleeve gastrectomy. The most encountered in-hospital complication after primary bariatric surgery was bleeding (1.5%), with Roux-en-Y gastric bypass (RYGB) having the highest recorded rate of post-operative complications (3.6% bleeding). The overall rate of operative complications was 2.6%, which was most prevalent post-RYGB (10.3%) and lowest post-sleeve gastrectomy (2.5%). Conclusion The importance of tracking and documenting the journey and change in the rates of obesity and effectiveness of bariatric procedures in individual countries with significantly high obesity rates is imperative to be able to create a plan of action to tackle this worldwide epidemic. This report will be able to provide the population with an accurate accounting that demonstrates further the safety of bariatric/metabolic surgery.

Results from the First Kuwait National Bariatric Surgery Report

Background Currently, more than 30% of the population in the gulf demonstrate a body mass index(BMI) exceeding 30. This burden of obesity has proven to take a toll on the population; therefore, we created the first Kuwait National Bariatric Surgery Database to report on bariatric surgeries performed in Kuwait.Methods Data was collected from the six public hospitals in Kuwait. This data was then submitted to a merged National Registry. Data web portal were used to upload, merge, and analyze the data.Results The average age for participants was 32.6 years. The average preoperative BMI was 45.9kg/m2 for males and 43.3kg/m2 for females. 16.4% of males and 12.3% of females presented with type 2 diabetes, while the most prevalent obesity related disease was a poor functional status in both males and females (90.8% and 90.5%, respectively). Most procedures performed in Kuwait are sleeve gastrectomy. The most encountered in-hospital complication after primary bariatric surgery was bleeding (1.5%), with Roux-en-Y gastric bypass (RYGB) having the highest recorded rate of post-operative complications (3.6% bleeding). The overall rate of operative complications was 2.6%, which was most prevalent post-RYGB (10.3%) and lowest post-sleeve gastrectomy (2.5%).Conclusion The importance of tracking and documenting the journey and change in the rates of obesity and effectiveness of bariatric procedures in individual countries with significantly high obesity rates is imperative to be able to create a plan of action to tackle this worldwide epidemic. This report will be able to provide the population with an accurate accounting that demonstrates further the safety of bariatric/metabolic surgery.

Predicting suicide attempt or suicide death following a visit to psychiatric specialty care: A machine learning study using Swedish national registry data

Background Suicide is a major public health concern globally. Accurately predicting suicidal behavior remains challenging. This study aimed to use machine learning approaches to examine the potential of the Swedish national registry data for prediction of suicidal behavior. Methods and findings The study sample consisted of 541,300 inpatient and outpatient visits by 126,205 Sweden-born patients (54% female and 46% male) aged 18 to 39 (mean age at the visit: 27.3) years to psychiatric specialty care in Sweden between January 1, 2011 and December 31, 2012. The most common psychiatric diagnoses at the visit were anxiety disorders (20.0%), major depressive disorder (16.9%), and substance use disorders (13.6%). A total of 425 candidate predictors covering demographic characteristics, socioeconomic status (SES), electronic medical records, criminality, as well as family history of disease and crime were extracted from the Swedish registry data. The sample was randomly split into an 80% training set containing 433,024 visits and a 20% test set containing 108,276 visits. Models were trained separately for suicide attempt/death within 90 and 30 days following a visit using multiple machine learning algorithms. Model discrimination and calibration were both evaluated. Among all eligible visits, 3.5% (18,682) were followed by a suicide attempt/death within 90 days and 1.7% (9,099) within 30 days. The final models were based on ensemble learning that combined predictions from elastic net penalized logistic regression, random forest, gradient boosting, and a neural network. The area under the receiver operating characteristic (ROC) curves (AUCs) on the test set were 0.88 (95% confidence interval [CI] = 0.87–0.89) and 0.89 (95% CI = 0.88–0.90) for the outcome within 90 days and 30 days, respectively, both being significantly better than chance (i.e., AUC = 0.50) (p < 0.01). Sensitivity, specificity, and predictive values were reported at different risk thresholds. A limitation of our study is that our models have not yet been externally validated, and thus, the generalizability of the models to other populations remains unknown. Conclusions By combining the ensemble method of multiple machine learning algorithms and high-quality data solely from the Swedish registers, we developed prognostic models to predict short-term suicide attempt/death with good discrimination and calibration. Whether novel predictors can improve predictive performance requires further investigation.