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Two doses of the BNT162b2 vaccine were associated mainly with low-grade local adverse effects that lasted 2 days or less and afforded nearly 50% protection against omicron infection and symptomatic illness, which was lower than that seen against delta. Greater protection in the youngest group was noted.

This study assesses the attributable impact of adherence to oral glucose medications as a risk factor for poor glycemic control in population subgroups of a large general population, using an objective medication adherence measure. Using electronic health records data, adherence to diabetes medications over a two-year period was calculated by prescription-based Medication Possession Ratios for adults with diabetes diagnosed before January 1, 2010. Glycemic control was determined by the HbA1c test closest to the last drug prescription during 2010-2012. Poor control was defined as HbA1c>75 mmol/mol (9.0%). Medication adherence was categorized as \"good\" (>80%), \"moderate\" (50-80%), or \"poor\" (<50%). Logistic regression models assessed the role medication adherence plays in the association between disease duration, age, and poor glycemic control. We calculated the change in the attributable fraction of glucose control if the non-adherent diabetic medication population would become adherent by age-groups. Among 228,846 diabetes patients treated by oral antiglycemic medication, 46.4% had good, 28.8% had moderate, and 24.8% had poor adherence. Good adherence rates increased with increasing disease duration, while glycemic control became worse. There was a strong inverse association between adherence level and poor control (OR = 2.50; CI = 2.43-2.58), and adherence was a significant mediator between age and poor control. A large portion of the diabetes population is reported to have poor adherence to oral diabetes medications, which is strongly associated with poor glycemic control in all disease durations. While poor adherence does not mediate the poorer glycemic control seen in patients with longer-standing disease, it is a significant mediator of poor glycemic control among younger diabetes patients. A greater fraction of poorly controlled younger patients, compared to older patients, could be prevented if at least 80% adherence to their medications was achieved. Therefore, our results suggest that interventions to improve adherence should focus on this younger sub-group.

Background. Streptococcus pneumoniae contributes considerably to the burden of pneumonia and invasive pneumococcal disease (IPD), with the effectiveness of the 23-valent pneumococcal polysaccharide vaccine (PPSV23) for preventing all-cause pneumonia still undetermined. The aim of this study was to control for common biases and confounders associated with previous observational studies and to assess PPSV23 vaccine effectiveness in preventing IPD and the most resource-intensive type of community-acquired pneumonia, hospital-treated pneumonia (HTP). Methods. This was a retrospective case-control study nested in a population-based cohort, with age-, sex-, and risk-matched controls as the base case. Demographic information, laboratory data, and diagnoses were extracted from the chronic disease registry and from inpatient and outpatient records in the Clalit Health Services database. Vaccine effectiveness for PPSV23 was assessed using multivariable conditional logistic regression. Subgroup, sensitivity, and secondary analyses were conducted to validate findings. Results. A total of 470 070 individuals aged ≥65 years were members of Clalit Health Services during the study period (1 January 2007 through 31 December 2010). The case cohort consisted of 212 participants with IPD and 23 441 with HTP. The adjusted association between vaccination and IPD was protective (odds ratio [OR], 0.58; 95% confidence interval [CI], .41–.81), whereas there was no demonstrated protective effect between vaccination and HTP (OR, 1.01; 95% CI, .97–1.04). The sensitivity analysis and all but 1 subgroup analysis provided consistent results to the base case. Conclusions. The PPSV23 vaccine is effective against the most severe invasive forms of pneumococcal disease, but the lack of effectiveness of PPSV23 in protecting against all-cause HTP should be considered for future vaccine policies.

ObjectivesTo assess whether the extent of deviation from chronic disease guideline recommendations is more prominent for specific diseases compared with combined-care across multiple conditions among multimorbid patients, and to examine reasons for this deviation.DesignA cross-sectional cohort.SettingMultimorbidity care management programme across 11 primary care clinics.PatientsPatients aged 45–95 years with at least two common chronic conditions, sampled according to being new (≤6 months) or veteran (≥1 year) to the programme.Main outcome measuresDeviation from guideline-recommended care was measured for each patient’s relevant conditions, aggregated and stratified across disease groups, calculated as measures of ‘disease-specific’ guideline deviation and ‘combined-care’ (all conditions) guideline deviation for: atrial fibrillation, congestive heart failure, chronic kidney disease, chronic obstructive pulmonary disorder, depression, diabetes, dyslipidaemia, hypertension and ischaemic heart disease. Combined-care deviation was evaluated for its association with specific diseases. Frequencies of previously derived reason types for deviation (biomedical, patient personal and contextual) were reported by nurse care managers, assessed across diseases and evaluated for their association with specific diseases.ResultsAmong 204 patients, disease-specific deviation varied more (from 14.7% to 48.2%) across diseases than combined-care deviation (from 14.7% to 25.6%). Depression and diabetes were significantly associated with more deviation (mean: 6% (95% CI: 2% to 10%) and 5% (95% CI: 2% to 9%), respectively). For some conditions, assessments were among small patient samples. Guideline deviation was often attributed to non-disease-specific reasons, such as physical limitations or care burden, as much as disease-specific reasons, which was reflected in the likelihood for guideline deviation to be due to different types of reasons for some diseases.ConclusionsWhen multimorbid patients are considered in disease groups rather than as ‘whole persons’, as in many quality of care studies, the cross-cutting factors in their care delivery can be missed. The types of reasons more likely to occur for specific diseases may inform improvement strategies.Trial registration numberNCT01811173; Pre-results.

Background With increasing diabetes prevalence worldwide, an impending diabetes “pandemic” has been reported. However, definitions of incident cases and the population at risk remain varied and ambiguous. This study analyzed trends in mortality and screening that contribute to diabetes prevalence and incidence, distinguishing between new incident cases and newly detected cases. Methods In an integrated provider-and-payer-system covering 53% of Israel’s population, a composite diabetes case-finding algorithm was built using diagnoses, lab tests, and antidiabetic medication purchases from the organization’s electronic medical record database. Data were extracted on adult members aged 26+ each year from January 1, 2004 through December 31, 2012. Rates of diabetes prevalence, incidence, screening, and mortality were reported, with incidence rates evaluated among the total, “previously-screened,” and “previously-unscreened” at-risk populations. Results There were 343,554 diabetes cases in 2012 (14.4%) out of 2,379,712 members aged 26+. A consistent but decelerating upward trend in diabetes prevalence was observed from 2004-2012. Annual mortality rates among diabetics decreased from 13.8/1000 to 10.7/1000 (p = 0.0002). Total population incidence rates declined from 13.3/1000 in 2006 to 10.8/1000 in 2012 (p < 0.0001), with similar incidence trends (13.2/1000 to 10.2/1000; p = 0.0007) among previously-screened at-risk members, and a rise in testing rates from 53.0% to 66.7% (p = 0.0004). The previously-unscreened group decreased 28.6%, and the incidence rates within this group remained stable. Conclusions The increase in diabetes prevalence is decelerating despite declining mortality and increasing testing rates. A decline in previously-screened incident cases and a shrinking pool of previously-unscreened members suggests that diabetes trends in Israel are moving toward equilibrium, rather than a growing epidemic.

Currently, clinicians rely mostly on population-level treatment effects from RCTs, usually considering the treatment's benefits. This study proposes a process, focused on practical usability, for translating RCT data into personalized treatment recommendations that weighs benefits against harms and integrates subjective perceptions of relative severity. Intensive blood pressure treatment (IBPT) was selected as the test case to demonstrate the suggested process, which was divided into three phases: (1) Prediction models were developed using the Systolic Blood-Pressure Intervention Trial (SPRINT) data for benefits and adverse events of IBPT. The models were externally validated using retrospective Clalit Health Services (CHS) data; (2) Predicted risk reductions and increases from these models were used to create a yes/no IBPT recommendation by calculating a severity-weighted benefit-to-harm ratio; (3) Analysis outputs were summarized in a decision support tool. Based on the individual benefit-to-harm ratios, 62 and 84% of the SPRINT and CHS populations, respectively, would theoretically be recommended IBPT. The original SPRINT trial results of significant decrease in cardiovascular outcomes following IBPT persisted only in the group that received a “yes-treatment” recommendation by the suggested process, while the rate of serious adverse events was slightly higher in the \"no-treatment\" recommendation group. This process can be used to translate RCT data into individualized recommendations by identifying patients for whom the treatment’s benefits outweigh the harms, while considering subjective views of perceived severity of the different outcomes. The proposed approach emphasizes clinical practicality by mimicking physicians’ clinical decision-making process and integrating all recommendation outputs into a usable decision support tool.