Purpose Pathogenic variants affecting MLH1, MSH2, MSH6, and PMS2 cause Lynch syndrome and result in different but imprecisely known cancer risks. This study aimed to provide age and organ-specific cancer risks according to gene and gender and to determine survival after cancer. Methods We conducted an international, multicenter prospective observational study using independent test and validation cohorts of carriers of class 4 or class 5 variants. After validation the cohorts were merged providing 6350 participants and 51,646 follow-up years. Results There were 1808 prospectively observed cancers. Pathogenic MLH1 and MSH2 variants caused high penetrance dominant cancer syndromes sharing similar colorectal, endometrial, and ovarian cancer risks, but older MSH2 carriers had higher risk of cancers of the upper urinary tract, upper gastrointestinal tract, brain, and particularly prostate. Pathogenic MSH6 variants caused a sex-limited trait with high endometrial cancer risk but only modestly increased colorectal cancer risk in both genders. We did not demonstrate a significantly increased cancer risk in carriers of pathogenic PMS2 variants. Ten-year crude survival was over 80% following colon, endometrial, or ovarian cancer. Conclusion Management guidelines for Lynch syndrome may require revision in light of these different gene and gender-specific risks and the good prognosis for the most commonly associated cancers.

Infections with multidrug resistant (MDR) bacteria in hospital settings have substantial implications in terms of clinical and economic outcomes. However, due to clinical and methodological heterogeneity, estimates about the attributable economic and clinical effects of healthcare-associated infections (HAI) due to MDR microorganisms (MDR HAI) remain unclear. The objective was to review and synthesize the evidence on the impact of MDR HAI in adults on hospital costs, length of stay, and mortality at discharge. Literature searches were conducted in PubMed/MEDLINE, and Google Scholar databases to select studies that evaluated the impact of MDR HAI on economic and clinical outcomes. Eligible studies were conducted in adults, in order to ensure homogeneity of populations, used propensity score matched cohorts or included explicit confounding control, and had confirmed antibiotic susceptibility testing. Risk of bias was evaluated, and effects were measured with ratios of means (ROM) for cost and length of stay, and risk ratios (RR) for mortality. A systematic search was performed on 14^th March 2019, re-run on the 10^th of June 2019 and extended the 3^rd of September 2019. Small effect sizes were assessed by examination of funnel plots. Sixteen articles (6,122 patients with MDR HAI and 8,326 patients with non-MDR HAI) were included in the systematic review of which 12 articles assessed cost, 19 articles length of stay, and 14 mortality. Compared to susceptible infections, MDR HAI were associated with increased cost (ROM 1.33, 95%CI [1.15; 1.54]), prolonged length of stay (ROM 1.27, 95%CI [1.18; 1.37]), and excess in-hospital mortality (RR 1.61, 95%CI [1.36; 1.90]) in the random effects models. Risk of publication bias was only found to be significant for mortality, and overall study quality good. MDR HAI appears to be strongly associated with increases in direct cost, prolonged length of stay and increased mortality. However, further comprehensive studies in this setting are warranted. PROSPERO (CRD42019126288).

Liver fibrosis is the main determinant of long-term outcome in chronic liver diseases. Little is known about the prevalence of liver fibrosis in the general population. The aim of the study was to investigate the prevalence of liver fibrosis in the general adult population with unknown liver disease. This was a population-based, cross-sectional study performed in the Barcelona metropolitan area. Subjects aged 18 to 75 years old were identified randomly from citizens included in the primary health care registry. Of 4866 subjects invited, 3076 participated (63.2%). Liver fibrosis was estimated by measuring liver stiffness (LS) with transient elastography (TE). Liver histology was assessed in 92 subjects with increased LS. Prevalence estimates of increased LS (≥6.8, ≥8.0, and ≥9.0 kPa) were 9.0%, 5.8%, and 3.6%, respectively. The etiology of liver disease was mainly nonalcoholic fatty liver disease (NAFLD), followed by alcohol risk consumption (consumption of ≥21 standard drinking units/wk in men and ≥14 standard drinking units/wk in women). Factors independently associated with increased LS were male sex, abdominal obesity, type 2 diabetes, serum glucose, high-density lipoprotein, and triglyceride levels. Subjects without risk factors for NAFLD or without alcohol risk consumption had a very low prevalence of increased LS. The best cut-off value of LS for significant liver fibrosis (F2-F4) was 9.2 kPa, with high sensitivity and specificity. TE was more accurate than alanine aminotransferase, NAFLD fibrosis score, or Fibrosis 4. An algorithm for screening for liver fibrosis using TE in the community setting is proposed. These findings show a high prevalence of silent liver disease with advanced fibrosis mainly related to NAFLD in adult European subjects without known liver disease. An LS value less than 9.2 kPa predicts the absence of significant liver fibrosis with high accuracy and could be used for screening purposes.

Study Design.: Retrospective review of prospectively-collected, multicenter adult spinal deformity (ASD) databases. Objective.: To apply artificial intelligence (AI)-based hierarchical clustering as a step toward a classification scheme that optimizes overall quality, value, and safety for ASD surgery. Summary of Background Data.: Prior ASD classifications have focused on radiographic parameters associated with patient reported outcomes. Recent work suggests there are many other impactful preoperative data points. However, the ability to segregate patient patterns manually based on hundreds of data points is beyond practical application for surgeons. Unsupervised machine-based clustering of patient types alongside surgical options may simplify analysis of ASD patient types, procedures, and outcomes. Methods.: Two prospective cohorts were queried for surgical ASD patients with baseline, 1-year, and 2-year SRS-22/Oswestry Disability Index/SF-36v2 data. Two dendrograms were fitted, one with surgical features and one with patient characteristics. Both were built with Ward distances and optimized with the gap method. For each possible n patient cluster by m surgery, normalized 2-year improvement and major complication rates were computed. Results.: Five hundred-seventy patients were included. Three optimal patient types were identified: young with coronal plane deformity (YC, n = 195), older with prior spine surgeries (ORev, n = 157), and older without prior spine surgeries (OPrim, n = 218). Osteotomy type, instrumentation and interbody fusion were combined to define four surgical clusters. The intersection of patient-based and surgery-based clusters yielded 12 subgroups, with major complication rates ranging from 0% to 51.8% and 2-year normalized improvement ranging from −0.1% for SF36v2 MCS in cluster [1,3] to 100.2% for SRS self-image score in cluster [2,1]. Conclusion.: Unsupervised hierarchical clustering can identify data patterns that may augment preoperative decision-making through construction of a 2-year risk–benefit grid. In addition to creating a novel AI-based ASD classification, pattern identification may facilitate treatment optimization by educating surgeons on which treatment patterns yield optimal improvement with lowest risk. Level of Evidence: 4

Background: Digital proximity tracing apps have been released to mitigate the transmission of SARS-CoV-2, the virus known to cause COVID-19. However, it remains unclear how the acceptance and uptake of these apps can be improved. Objective: This study aimed to investigate the coverage of the SwissCovid app and the reasons for its nonuse in Switzerland during a period of increasing incidence of COVID-19 cases. Methods: We collected data between September 28 and October 8, 2020, via a nationwide online panel survey (COVID-19 Social Monitor, N=1511). We examined sociodemographic and behavioral factors associated with app use by using multivariable logistic regression, whereas reasons for app nonuse were analyzed descriptively. Results: Overall, 46.5% (703/1511) of the survey participants reported they used the SwissCovid app, which was an increase from 43.9% (662/1508) reported in the previous study wave conducted in July 2020. A higher monthly household income (ie, income >CHF 10,000 or >US $11,000 vs income ≤CHF 6000 or <US $6600 [reference]: odds ratio [OR] 1.92, 95% CI 1.40-2.64), more frequent internet use (ie, daily [reference] vs less than weekly: OR 0.37, 95% CI 0.16-0.85), better adherence to recommendations for wearing masks (ie, always or most of the time [reference] vs rarely or never: OR 0.28, 95% CI 0.15-0.52), and nonsmoker status (OR 1.32, 95% CI 1.01-1.71) were associated with an increased likelihood for app uptake. Citizenship status (ie, non-Swiss citizenship vs. Swiss [reference]: OR 0.61, 95% CI 0.43-0.87), and language region (French vs Swiss German [reference]: OR 0.61, 95% CI 0.46-0.80) were associated with a lower likelihood for app uptake. Further analysis in a randomly selected subsample (n=712) with more detailed information showed that higher levels of trust in government and health authorities were also associated with a higher likelihood for app uptake (ie, high vs low [reference] trust: OR 3.13, 95% CI 1.58-6.22). The most frequent reasons for app nonuse were lack of perceived benefit of using the app (297/808, 36.8%), followed by the lack of a compatible phone (184/808, 22.8%), and privacy concerns (181/808, 22.4%). Conclusions: Eliminating technical hurdles and communicating the benefits of digital proximity tracing apps are crucial to promote further uptake and adherence of such apps and, ultimately, enhance their effectiveness to aid pandemic mitigation strategies.