RESUMO
Purpose: Comparing IOL power calculation formulas in long eyes (AL≥26.00 mm) to find the best axial length (AL) adjustment/IOL power calculation formula combination. Design: Retrospective, comparative, case-series. Participants: Patients with long eyes that underwent cataract surgery. Methods: five-hundred-fifty-four eyes of 554 patients were examined before and after standard phacoemulsification without complications. Eyes were subdivided in 3 groups according to AL: 26.00≤AL<28.00 mm, 28.00≤AL<30.00 mm, AL≥30.00 mm. Eight formulas that do not require anterior chamber depth (ACD) were evaluated: Barrett Universal II (BUII), Emmetropia Verifying Optical (EVO) 2.0, Ladas Super Formula (LSF), Hoffer Q, Holladay 1, SRKT, T2 and T2.2. The lens constant of ULIB database and IOLCon database were used. Each formula was analyzed by using uncorrected AL (ALu) and following AL adjustments: Wang-Koch 1 (wk1), wk2, wk polinomial (wk-pol), estimated Cooke modified axial length (CMALe) and ALc correcting factor. Main outcome measures: Mean absolute error (MAE), median absolute error (MedAE) and percentage of eyes within ±0.50 and ± 1.00 diopters (D) of prediction error. Results: T2-ALu gave best outcome when 26.00 mm ≤ AL<28.00 mm. LSF-ALu, BUII-ALu, EVO 2.0-ALu, Holladay 1-wk-pol and T2.2-CMALe represented valid alternatives. EVO 2.0-ALc gave best outcomes when 28.00 mm ≤ AL<30.00 mm. Other thick-lens or hybrid artificial-intelligence-vergence based formulas (BUII-ALu, LSF-CMALe) and Holladay 1-wk2 demonstrated greater reliability compared to thin lens-based formulas. EVO 2.0-CMALe gave best outcomes when AL≥30.00 mm. Holladay 1-wk-pol e T2.2-wk1 represented valid alternatives (all p < 0.050). LSF could fail in 50 % of cases without ACD when AL≥30.00 mm. Conclusions: Choosing the best AL adjustment/IOL power calculation formula combination for each AL subrange, can improve refractive outcomes in patients with long eyes that undergo cataract surgery.
RESUMO
BACKGROUND: Comparing intraocular pressure (IOP) changes (ΔIOP) between obese subjects and non-obese controls in relation to different positions: standing, sitting, supine. METHODS: the IOP was measured in both obese patients and non-obese controls groups with Tono-Pen AVIA in different positions following this sequence: after 5 min (5') in the standing position, sitting, supine, supine after 5 min (supine 5') and immediately after standing. ΔIOP values obtained comparing all positions were, therefore, evaluated. RESULTS: 92 eyes of 46 obese subjects aged between 18 and 59 years (mean 38.07 ± 11.51 years) and of a Body Mass Index (BMI) between 31.84 and 60.65 (mean 41.84 ± 7.05) were evaluated. A total of 48 eyes of 24 non-obese controls aged between 23 and 55 (mean 35.21 ± 11.96 years) and of a BMI between 18.20 and 26.79 (mean 21.04 ± 2.36) were also recruited. In obese subjects, there were statistically significant differences between the IOP in the supine position and the supine positions 5' with all other IOP measurements (p < 0.05). There were statistically significant differences between ΔIOP in both supine positions and prolonged standing positions obtained by obese subjects and non-obese controls (p < 0.05). CONCLUSIONS: In obese subjects, there is a statistically significant increase in IOP in the supine positions that is significantly greater than the non-obese population. BMI is weakly correlated with IOP and ΔIOP in postural changes.
RESUMO
More than two years after the onset of the COVID-19 pandemic, healthcare providers are facing an emergency within an emergency, the so-called long COVID or post-COVID-19 syndrome (PCS). Patients diagnosed with PCS develop an extended range of persistent symptoms and/or complications from COVID-19. The risk factors and clinical manifestations are many and various. Advanced age, sex/gender, and pre-existing conditions certainly influence the pathogenesis and course of this syndrome. However, the absence of precise diagnostic and prognostic biomarkers may further complicate the clinical management of patients. This review aimed to summarize recent evidence on the factors influencing PCS, possible biomarkers, and therapeutic approaches. Older patients recovered approximately one month earlier than younger patients, with higher rates of symptoms. Fatigue during the acute phase of COVID-19 appears to be an important risk factor for symptom persistence. Female sex, older age, and active smoking are associated with a higher risk of developing PCS. The incidence of cognitive decline and the risk of death are higher in PCS patients than in controls. Complementary and alternative medicine appears to be associated with improvement in symptoms, particularly fatigue. The heterogeneous nature of post-COVID symptoms and the complexity of patients with PCS, who are often polytreated due to concomitant clinical conditions, suggest a holistic and integrated approach to provide useful guidance for the treatment and overall management of long COVID.