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More than 50 million older people worldwide are suffering from dementia, and this number is estimated to increase to 150 million by 2050. Greater caregiver burdens and financial impacts on the healthcare system are expected as we wait for an effective treatment for dementia. Researchers are constantly exploring new therapies and screening approaches for the early detection of dementia. Artificial intelligence (AI) is widely applied in dementia research, including machine learning and deep learning methods for dementia diagnosis and progression detection. Computerized apps are also convenient tools for patients and caregivers to monitor cognitive function changes. Furthermore, social robots can potentially provide daily life support or guidance for the elderly who live alone. This review aims to provide an overview of AI applications in dementia research. We divided the applications into three categories according to different stages of cognitive impairment: (1) cognitive screening and training, (2) diagnosis and prognosis for dementia, and (3) dementia care and interventions. There are numerous studies on AI applications for dementia research. However, one challenge that remains is comparing the effectiveness of different AI methods in real clinical settings.
While involving patients in health technology assessment (HTA) has become increasingly common and important around the world, little is known about the optimal methods of evaluating patients’ involvement (PI) in HTA. This scoping review was undertaken to provide an overview of currently available methods for the evaluation of PI, specifically the impact of PI on HTA recommendations.
A literature search was conducted using nine databases as well as a grey literature search of the websites of 26 organizations related to the conduct, practice or research of HTA to identify articles, reports and abstracts related to the evaluation of PI impact in HTA.
We identified 1,248 unique citations, six of which met our eligibility criteria. These six records (five articles, and one report) were all published after 2012. Four assessed the impact of patient experience submissions on final HTA recommendations; one evaluated the impact of direct involvement on HTA committees, and one assessed impact of multiple forms of involvement. Methods of evaluation included quantitative analyses of reimbursement decisions, qualitative interviews with those directly involved in an assessment, surveys of patient groups and committee members, and the review of HTA reports.
Quantitative evaluation of PI based on associations with funding decisions may not be feasible or fully capture the relevant impact of PI in the assessment of health technologies. Rather, a combination of both qualitative and quantitative strategies may allow for the most comprehensive assessment of the impact of PI on HTA recommendations when possible.
Seasonal influenza virus epidemics have a major impact on healthcare systems. Data on population susceptibility to emerging influenza virus strains during the interepidemic period can guide planning for resource allocation of an upcoming influenza season. This study sought to assess the population susceptibility to representative emerging influenza virus strains collected during the interepidemic period. The microneutralisation antibody titers (MN titers) of a human serum panel against representative emerging influenza strains collected during the interepidemic period before the 2018/2019 winter influenza season (H1N1-inter and H3N2-inter) were compared with those against influenza strains representative of previous epidemics (H1N1-pre and H3N2-pre). A multifaceted approach, incorporating both genetic and antigenic data, was used in selecting these representative influenza virus strains for the MN assay. A significantly higher proportion of individuals had a ⩾four-fold reduction in MN titers between H1N1-inter and H1N1-pre than that between H3N2-inter and H3N2-pre (28.5% (127/445) vs. 4.9% (22/445), P < 0.001). The geometric mean titer (GMT) of H1N1-inter was significantly lower than that of H1N1-pre (381 (95% CI 339–428) vs. 713 (95% CI 641–792), P < 0.001), while there was no significant difference in the GMT between H3N2-inter and H3N2-pre. Since A(H1N1) predominated the 2018–2019 winter influenza epidemic, our results corroborated the epidemic subtype.
Screening for depression in older adults is recommended.
To evaluate the diagnostic accuracy of the Two-Question Screen for older adults and compare it with other screening instruments for depression.
We undertook a literature search for studies assessing the diagnostic performance of depression screening instruments in older adults. Combined diagnostic accuracy including sensitivity and specificity were the primary outcomes. Potential risks of bias and the quality of studies were also assessed.
A total of 46506 participants from 132 studies were identified evaluating 16 screening instruments. The majority of studies (63/132) used various versions of the Geriatric Depression Scale (GDS) and 6 used the Two-Question Screen. The combined sensitivity and specificity for the Two-Question Screen were 91.8% (95% CI 85.2–95.6) and 67.7% (95% CI 58.1–76.0), respectively; the diagnostic performance area under the curve (AUC) was 90%. The Two-Question Screen showed comparable performance with other instruments, including clinician-rated scales. The One-Question Screen showed the lowest diagnostic performance with an AUC of 78%. In subgroup analysis, the Two-Question Screen also had good diagnostic performance in screening for major depressive disorder.
The Two-Question Screen is a simple and short instrument for depression screening. Its diagnostic performance is comparable with other instruments and, therefore, it would be favourable to use it for older adult screening programmes.
To assess the effectiveness of infection control preparedness for human infection with influenza A H7N9 in Hong Kong.
A descriptive study of responses to the emergence of influenza A H7N9.
A university-affiliated teaching hospital.
Healthcare workers (HCWs) with unprotected exposure (not wearing N95 respirator during aerosol-generating procedure) to a patient with influenza A H7N9.
A bundle approach including active and enhanced surveillance, early airborne infection isolation, rapid molecular diagnostic testing, and extensive contact tracing for HCWs with unprotected exposure was implemented. Seventy HCWs with unprotected exposure to an index case were interviewed especially regarding their patient care activities.
From April 1, 2013, through May 31, 2014, a total of 126 (0.08%) of 163,456 admitted patients were tested for the H7 gene by reverse transcription-polymerase chain reaction per protocol. Two confirmed cases were identified. Seventy (53.8%) of 130 HCWs had unprotected exposure to an index case, whereas 41 (58.6%) and 58 (82.9%) of 70 HCWs wore surgical masks and practiced hand hygiene after patient care, respectively. Sixteen (22.9%) of 70 HCWs were involved in high-risk patient contacts. More HCWs with high-risk patient contacts received oseltamivir prophylaxis (P=0.088) and significantly more had paired sera collected for H7 antibody testing (P<0.001). Ten (14.3%) of 70 HCWs developed influenza-like illness during medical surveillance, but none had positive results by reverse transcription-polymerase chain reaction. Paired sera was available from 33 of 70 HCWs with unprotected exposure, and none showed seroconversion against H7N9.
Despite the delay in airborne precautions implementation, no patient-to-HCW transmission of influenza A H7N9 was demonstrated.
A heuristic greedy algorithm is developed for efficiently tiling spatially dense redshift surveys. In its first application to the Galaxy and MassAssembly (GAMA) redshift survey we find it rapidly improves the spatial uniformity of our data, and naturally corrects for any spatial bias introduced by the 2dF multi-object spectrograph. We make conservative predictions for the final state of the GAMA redshift survey after our final allocation of time, and can be confident that even if worse than typical weather affects our observations, all of our main survey requirements will be met.
Nosocomial outbreaks of norovirus infection pose a great challenge to the infection control team.
Between November 1, 2009, and February 28, 2010, strategic infection control measures were implemented in a hospital network. In addition to timely staff education and promotion of directly observed hand hygiene, reverse-transcription polymerase chain reaction for norovirus was performed as an added test by the microbiology laboratory for all fecal specimens irrespective of the request for testing. Laboratory-confirmed cases were followed up by the infection control team for timely intervention. The incidence of hospital-acquired norovirus infection per 1,000 potentially infectious patient-days was compared with the corresponding period in the preceding 12 months, and the incidence in the other 6 hospital networks in Hong Kong was chosen as the concurrent control. Phylogenetic analysis of norovirus isolates was performed.
Of the 988 patients who were tested, 242 (25%) were positive for norovirus; 114 (47%) of those 242 patients had norovirus detected by our added test. Compared with the corresponding period in the preceding 12 months, the incidence of hospital-acquired norovirus infection decreased from 131 to 16 cases per 1,000 potentially infectious patient-days (P < .001 ), although the number of hospital-acquired infections was low in both the study period (n = 8) and the historical control periods (n = 11). The incidence of hospital-acquired norovirus infection in our hospital network (0.03 cases per 1,000 patient-days) was significantly lower than that of the concurrent control (0.06 cases per 1,000 patient-days) (P = .015). Forty-three (93%) of 46 norovirus isolates sequenced belonged to the genogroup II.4 variant.
Strategic infection control measures with an added test maybe useful in controlling nosocomial transmission of norovirus.
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