Aspheric intraocular lens in cataract surgery

This thesis, by prior publication, encompasses an overview and critical analysis of 6 publications on aspheric intraocular lenses (IOLs) carried out at St. Thomas’ Hospital, Guy’s & St. Thomas’ NHS Foundation Trust, London between 2006 2012. The focus is on two areas: the visual and optical performance of aspheric IOLs with different values of asphericity, and their effect on posterior capsule opacification (PCO). Chapter 1 describes the history of IOLs and the evolution of aspheric IOLs. It also presents relevant optical concepts. The three publications presented in Chapter 2 compare aspheric IOLs with spherical IOLs. The results come from two prospective, randomised, fellow-eye comparison studies: one comparing a spherical Alcon AcrySof SN60AT versus the aspheric Alcon AcrySof SN60WF (with negative asphericity), which partially corrects corneal spherical aberrations, and the other comparing the Zeiss AcriSmart 36A (with negative asphericity), which partially corrects corneal spherical aberrations, and the Bausch & Lomb Akreos MI60 (with neutral asphericity), which has zero spherical aberration. The third publication reports changes in vertical coma after implantation of all the above lenses and additionally includes data on two spherical IOLs from a previous study by our group (the three piece Alcon MA60AC IOL and the plate haptic HumanOptic MC611MI IOL). For this study, the data were divided according to their asphericity and not design. To avoid confounding from aberrometric differences due to astigmatism and surgical techniques, standard incision sizes of 2.75 mm and 2.4 mm were used in the two felloweye, randomised studies and a single surgeon performed all the surgeries using same incision size for each study. Results demonstrated that the aspheric IOLs significantly reduced spherical aberration, improved mesopic contrast sensitivity and reduced depth-of-focus. Asphericity differences up to 20 μm were not associated with depth-of-focus and the degree of asphericity was not associated with best-corrected distance visual acuity. The vertical coma varied within IOL groups of the same asphericity but there was no statistically significant difference between the two spherical IOLs (AcrySof SN60AT and AcrySof MA60AC). Further critical analysis of our data already published showed no statistically significant difference in mean vertical coma between the AcrySof MA60AC (-0.060 ± 0.211μm) with that of Akreos MI60 (- 0.042 ± 0.148μm) (p=0.70) and AcriSmart 36A (-0.034 ± 0.141μm) (p=0.58) even though the AcrySof MA60AC, Akreos MI60 and AcriSmart 36A IOLs had different asphericity. This may be due to the difference in the IOL designs, decentration and difference in the sample sizes between groups. Chapter 3 discusses the findings of three publications related to posterior capsule opacification (PCO). The first publication is an in vitro study assessing posterior optic square edges of various commercially available spherical and aspherical IOLs. Results demonstrated hydrophilic IOLs had less sharp square edges compared to hydrophobic IOLs. Although these in vitro results are potentially significant, there are currently no in vivo studies on the lenses used to compare our results with. The other two publications are based on the PCO outcomes from the prospective, randomised, fellow-eye studies described above. There was no difference in the PCO rates between hydrophobic spherical AcrySof SN60AT and aspheric AcrySof SN60WF IOLs of the same design at 2 years. In contrast, we found a significant increase in the PCO with both the hydrophilic acrylic AcriSmart 36A and Akreos MI60 IOLs (one with negative asphericity and one with neutral asphericity). Variation in asphericity did not appear to be an important factor contributing to the PCO but it was apparent that the edge design and material of the IOL were important with regards to the PCO formation. Finally, since these publications, some of manufacturers have changed their IOL models and today a majority of the IOLs have are aspheric and have a sharp edge profile. The overall, benefit of using aspheric IOLs seems to be limited as it is dependent on the natural pupil size

Trypanosoma brucei RAP1 Maintains Telomere and Subtelomere Integrity by Suppressing TERRA and Telomeric RNA: DNA Hybrids

Trypanosoma brucei causes human African trypanosomiasis and regularly switches its major surface antigen, VSG, thereby evading the host\u27s immune response. VSGs are monoallelically expressed from subtelomeric expression sites (ESs), and VSG switching exploits subtelomere plasticity. However, subtelomere integrity is essential for T. brucei viability. The telomeric transcript, TERRA, was detected in T. brucei previously. We now show that the active ES-adjacent telomere is transcribed. We find that TbRAP1, a telomere protein essential for VSG silencing, suppresses VSG gene conversionmediated switching. Importantly, TbRAP1 depletion increases the TERRA level, which appears to result from longer read-through into the telomere downstream of the active ES. Depletion of TbRAP1 also results in more telomeric RNA:DNA hybrids and more double strand breaks (DSBs) at telomeres and subtelomeres. In TbRAP1-depleted cells, expression of excessive TbRNaseH1, which cleaves the RNA strand of the RNA:DNA hybrid, brought telomeric RNA:DNA hybrids, telomeric/subtelomeric DSBs and VSG switching frequency back to WT levels. Therefore, TbRAP1-regulated appropriate levels of TERRA and telomeric RNA:DNA hybrid are fundamental to subtelomere/telomere integrity. Our study revealed for the first time an important role of a long, non-coding RNA in antigenic variation and demonstrated a link between telomeric silencing and subtelomere/telomere integrity through TbRAP1-regulated telomere transcription

Jugoslavenska mornarica u završnim operacijama ,,Jadranu sloboda"

The trial was funded by the National Institute of Health Research (NIHR) Health Technology Assessment Panel (project reference number HTA 13/04/46 and was sponsored by University College London (UCL).Purpose To report the 3-month results of a randomized trial (Femtosecond Laser-Assisted Cataract Trial [FACT]) comparing femtosecond laser-assisted cataract surgery (FLACS) with standard phacoemulsification cataract surgery (PCS). Design Multicenter, randomized controlled trial funded by the UK National Institute of Health Research (HTA 13/04/46/). Participants Seven hundred eighty-five patients with age-related cataract. Methods This trial took place in 3 hospitals in the UK National Health Service (NHS). Randomization (1:1) was stratified by site, surgeon, and 1 or both eyes eligible using a secure web-based system. Postoperative assessments were masked to the allocated intervention. The primary outcome was unaided distance visual acuity (UDVA) in the study eye at 3 months. Secondary outcomes included corrected distance visual acuity, complications, and patient-reported outcomes measures. The noninferiority margin was 0.1 logarithm of the minimum angle of resolution (logMAR). ISRCTN.com registry, number ISRCTN77602616. Main Outcome Measures We enrolled 785 participants between May 2015 and September 2017 and randomly assigned 392 to FLACS and 393 to PCS. At 3 months postoperatively, mean UDVA difference between treatment arms was −0.01 logMAR (−0.05 to 0.03), and mean corrected distance visual acuity difference was −0.01 logMAR (95% confidence interval [CI], −0.05 to 0.02). Seventy-one percent of both FLACS and PCS cases were within ±0.5 diopters (D) of the refractive target, and 93% of FLACS and 92% of PCS cases were within ±1.0 D. There were 2 posterior capsule tears in the PCS arm and none in the FLACS arm. There were no significant differences between arms for any secondary outcome. Conclusions Femtosecond laser-assisted cataract surgery is not inferior to conventional PCS surgery 3 months after surgery. Both methods are as good in terms of vision, patient-reported health, and safety outcomes at 3 months. Longer-term outcomes of the clinical effectiveness and cost-effectiveness are awaited.Publisher PDFPeer reviewe

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions. Funding: Bill & Melinda Gates Foundation