Summary Background Sperm selection strategies aimed at improving success rates of intracytoplasmic sperm injection (ICSI) include binding to hyaluronic acid (herein termed hyaluronan). Hyaluronan-selected sperm have reduced levels of DNA damage and aneuploidy. Use of hyaluronan-based sperm selection for ICSI (so-called physiological ICSI [PICSI]) is reported to reduce the proportion of pregnancies that end in miscarriage. However, the effect of PICSI on livebirth rates is uncertain. We aimed to investigate the efficacy of PICSI versus standard ICSI for improving livebirth rates among couples undergoing fertility treatment. Methods This parallel, two-group, randomised trial included couples undergoing an ICSI procedure with fresh embryo transfer at 16 assisted conception units in the UK. Eligible women (aged 18–43 years) had a body-mass index of 19–35 kg/m 2 and a follicle-stimulating hormone (FSH) concentration of 3·0–20·0 mIU/mL or, if no FSH measurement was available, an anti-müllerian hormone concentration of at least 1·5 pmol/L. Eligible men (aged 18–55 years) had not had a vasovasostomy or been treated for cancer in the 24 months before recruitment and were able, after at least 3 days of sexual abstinence, to produce freshly ejaculated sperm for the treatment cycle. Couples were randomly assigned (1:1) with an online system to receive either PICSI or a standard ICSI procedure. The primary outcome was full-term (≥37 weeks' gestational age) livebirth, which was assessed in all eligible couples who completed follow-up. This trial is registered, number ISRCTN99214271. Findings Between Feb 1, 2014, and Aug 31, 2016, 2772 couples were randomly assigned to receive PICSI (n=1387) or ICSI (n=1385), of whom 2752 (1381 in the PICSI group and 1371 in the ICSI group) were included in the primary analysis. The term livebirth rate did not differ significantly between PICSI (27·4% [379/1381]) and ICSI (25·2% [346/1371]) groups (odds ratio 1·12, 95% CI 0·95–1·34; p=0·18). There were 56 serious adverse events in total, including 31 in the PICSI group and 25 in the ICSI group; most were congenital abnormalities and none were attributed to treatment. Interpretation Compared with ICSI, PICSI does not significantly improve term livebirth rates. The wider use of PICSI, therefore, is not recommended at present. Funding National Institute for Health Research Efficacy and Mechanism Evaluation Programme.

Operative treatment is indicated for most toothache/dental abscesses, yet antibiotics instead of procedures are often prescribed. This ethnographic study aimed to identify clinician and patient factors influencing urgent dental care for adults during actual appointments; and to identify elements sensitive to context. Appointments were observed in out-of-hours and general dental practices. Follow-up interviews took place with dentists, dental nurses, and patients. Dentist and patient factors were identified through thematic analysis of observation records and appointment/interview transcripts. Dentist factors were based on a published list of factors influencing antibiotic prescribing for adults with acute conditions across primary health care and presented within the Capability-Opportunity-Motivation-Behaviour model. Contextually sensitive elements were revealed by comparing the factors between settings. In total, thirty-one dentist factors and nineteen patient factors were identified. Beliefs about antibiotics, goals for the appointment and access to dental services were important for both dentists and patients. Dentist factors included beliefs about the lifetime impact of urgent dental procedures on patients. Patient factors included their communication and negotiation skills. Contextual elements included dentists’ concerns about inflicting pain on regular patients in general dental practice; and patients’ difficulties accessing care to complete temporary treatment provided out of hours. This improved understanding of factors influencing shared decisions about treatments presents significant opportunity for new, evidence-based, contextually sensitive antibiotic stewardship interventions.

This study aims to examine the impact of periodontal disease in obesity on COVID-19 infection and associated outcomes. This retrospective longitudinal study included 58,897 UK Biobank participants tested for COVID-19 between March 2020 and February 2021. Self-reported oral health indicators (bleeding gums, painful gums, and loose teeth) were used as surrogates for periodontal disease. Body fat levels were quantified by body mass index (BMI) and categorized as normal weight (18.5 to 24.9 kg/m2), overweight (25 to 29.9 kg/m2), and obese (≥30 kg/m2). Multivariable logistic regression and Cox proportional hazard models were used to quantify risk of COVID-19 infection, hospital admission, and mortality, adjusted for participants’ demographics and covariates. Of 58,897 participants, 14,466 (24.6%) tested positive for COVID-19 infection. COVID-19 infection was higher for participants who were overweight (odds ratio, 1.18; 95% CI, 1.12 to 1.24) and obese (odds ratio, 1.33; 95% CI, 1.26 to 1.41) as compared with those of normal weight, but infection was not affected by periodontal disease. The hospital admission rate was 57% higher (hazard ratio, 1.57; 95% CI, 1.25 to 1.97) in the obese group with periodontal disease than without periodontal disease, and admission rates increased with BMI category (normal weight, 4.4%; overweight, 6.8%; obese, 10.1%). Mortality rates also increased with BMI category (normal weight, 1.9%; overweight, 3.17%; obese, 4.5%). In addition, for participants with obesity, the mortality rate was much higher (hazard ratio, 3.11; 95% CI, 1.91 to 5.06) in participants with periodontal disease than those without. Obesity is associated with higher hospitalization and mortality rates, and periodontal disease may exacerbate this impact. The results could inform health providers, policy makers, and the general public of the importance to maintain good oral health through seamless provision of dental services and public oral health prevention initiatives.

Objectives This study was to investigate the association between central obesity and tooth loss in non‐obese population. Material and Methods This national cross‐sectional study included 19436 participants, aged 19–74 years with body mass index(BMI) 18.5–29.9 kg/m2, from the National Health and Nutrition Examination Survey(NHANES) 1999–2012. Tooth loss was measured by the number of teeth missing. Central obesity was defined by a categorized 3‐level waist circumference according to the WHO recommendation. A zero‐inflated negative binomial model was used to investigate the association between tooth loss and central obesity. All models were adjusted for demographic, socioeconomic status, lifestyles, medical conditions and inflammatory biomarkers. Results For an overweight person with central obesity, the prevalence of tooth loss increased by 31% (Prevalence ratio [PR]: 1.31, 95% CI: 1.20–1.44) compared with a person with similar BMI but no central obesity, and increased by 40% (PR: 1.40, 95% CI: 1.26–1.56) if compared with a normal‐weight person without central obesity. There was a clear stepwise association between tooth loss and central obesity. Conclusion The results reveal that central obesity is significantly associated with tooth loss in the non‐obese population, which suggests that non‐obese individuals with central obesity may represent an important target population for oral health preventive strategies.

Clinicians should reassess understanding and information needs actively throughout treatment and identify support needs. Clinicians should refer patients to quality information sources and peer support groups.

This study aimed to identify systemic multimorbidity clusters in people with periodontitis via a novel artificial intelligence–based network analysis and to explore the effect of associated factors. This study utilized cross-sectional data of 3,736 participants across 3 cycles of the National Health and Nutrition Examination Survey (2009 to 2014). Periodontal examination was carried out by trained dentists for participants aged ≥30 y. The extent of periodontitis was represented by the proportion of sites with clinical attachment loss (CAL)≥ 3 mm, split into 4 equal quartiles. A range of systemic diseases reported during the survey were also extracted. Hypergraph network analysis with eigenvector centralities was applied to identify systemic multimorbidity clusters and single-disease influence in the overall population and when stratified by CAL quartile. Individual factors that could affect the systemic multimorbidity clusters were also explored by CAL quartile. In the study population, the top 3 prevalent diseases were hypertension (63.9%), arthritis (47.6%), and obesity (45.9%). A total of 106 unique systemic multimorbidity clusters were identified across the study population. Hypertension was the most centralized disease in the overall population (centrality [C]: 0.50), followed closely by arthritis (C: 0.45) and obesity (C: 0.42). Diabetes had higher centrality in the highest CAL quartile (C: 0.31) than the lowest (C: 0.26). “Hypertension, obesity” was the largest weighted multimorbidity cluster across CAL quartiles. This study has revealed a range of common systemic multimorbidity clusters in people with periodontitis. People with periodontitis are more likely to present with hypertension and obesity together, and diabetes is more influential to multimorbidity clusters in people with severe periodontitis. Factors such as ethnicity, deprivation, and smoking status may also influence the pattern of multimorbidity clusters.

Aim The aim was to assess study factors that impact the association of cognitive disorders in people with periodontal disease (PD). Method Medline, EMBASE and Cochrane databases were searched until February 2022 using keywords and MeSH: (periodon* OR tooth loss OR missing teeth) AND (dementia OR Alzheimer’s Disease OR cognitive*). Observational studies reporting prevalence or risk of cognitive decline, dementia or Alzheimer’s disease (AD) in people with PD compared with healthy controls were included. Meta-analysis quantified the prevalence and risk (relative risk[RR]) of cognitive decline, dementia/AD, respectively. Meta-regression/subgroup analysis explored the impact of study factors including PD severity and classification type, and gender. Results Overall, 39 studies were eligible for meta-analysis: 13 cross-sectional and 26 longitudinal studies. PD demonstrated increased risks of cognitive disorders (cognitive decline—RR = 1.33, 95% CI = 1.13–1.55; dementia/AD—RR = 1.22, 95% CI = 1.14–1.31). Risk of cognitive decline increased with PD severity (moderate—[RR] = 1.14, 95% confidence interval [CI] = 1.07–1.22; severe—RR = 1.25, 95% CI = 1.18–1.32). For every 10% population increase in females, the risk of cognitive decline increased by 34% (RR = 1.34, 95% CI = 1.16–1.55). Self-reported PD showed a lower risk of cognitive disorders compared with clinical classification (cognitive decline—RR = 0.77, 95% CI = 0.65–0.91; dementia/AD—RR = 0.86, 95% CI = 0.77–0.96). Conclusion The prevalence and risk estimates of cognitive disorders in association with PD can be influenced by gender, the disease classification of PD and its severity. Further homologous evidence taking these study factors into consideration is needed to form robust conclusions.

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