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1.
J Med Phys ; 49(2): 250-260, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-39131428

RESUMO

Purpose: This study aims to minimize monitor units (MUs) of intensity-modulated treatments in the Monaco treatment planning system while preserving plan quality by optimizing the "Minimum Segment Width" (MSW) and "Fluence Smoothing" parameters. Materials and Methods: We retrospectively analyzed 30 prostate, 30 gynecological, 15 breast cancer, 10 head and neck tumor, 11 radiosurgery, and 10 hypo-fractionated plans. Original prostate plans employed "Fluence Smoothing" = Off and were reoptimized with Low, Medium, and High settings. The remaining pathologies initially used MSW = 0.5 cm and were reoptimized with MSW = 1.0 cm. Plan quality, including total MU, delivery time, and dosimetric constraints, was statistically analyzed with a paired t-test. Results: Prostate plans exhibited the highest MU variation when changing "Fluence Smoothing" from Off to High (average ΔMU = -5.1%; P < 0.001). However, a High setting may increase overall MU when MSW = 0.5 cm. Gynecological plans changed substantially when MSW increased from 0.5 cm to 1.0 cm (average ΔMU = -29%; P < 0.001). Organs at risk sparing and planning target volumes remained within 1.2% differences. Replanning other pathologies with MSW = 1.0 cm affected breast and head and neck tumor plans (average ΔMU = -168.38, average Δt = -11.74 s, and average ΔMU = -256.56, average Δt = -15.05 s, respectively; all with P < 0.004). Radiosurgery and hypofractioned highly modulated plans did not yield statistically significant results. Conclusions: In breast, pelvis, head and neck, and prostate plans, starting with MSW = 1.0 cm optimally reduces MU and treatment time without compromising plan quality. MSW has a greater impact on MU than the "Fluence Smoothing" parameter. Plans with high modulation might present divergent behavior, requiring a case-specific analysis with MSW values higher than 0.5 cm.

2.
EClinicalMedicine ; 64: 102212, 2023 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-37745025

RESUMO

Background: Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of SARS-CoV-2 infection. It remains unclear how MIS-C phenotypes vary across SARS-CoV-2 variants. We aimed to investigate clinical characteristics and outcomes of MIS-C across SARS-CoV-2 eras. Methods: We performed a multicentre observational retrospective study including seven paediatric hospitals in four countries (France, Spain, U.K., and U.S.). All consecutive confirmed patients with MIS-C hospitalised between February 1st, 2020, and May 31st, 2022, were included. Electronic Health Records (EHR) data were used to calculate pooled risk differences (RD) and effect sizes (ES) at site level, using Alpha as reference. Meta-analysis was used to pool data across sites. Findings: Of 598 patients with MIS-C (61% male, 39% female; mean age 9.7 years [SD 4.5]), 383 (64%) were admitted in the Alpha era, 111 (19%) in the Delta era, and 104 (17%) in the Omicron era. Compared with patients admitted in the Alpha era, those admitted in the Delta era were younger (ES -1.18 years [95% CI -2.05, -0.32]), had fewer respiratory symptoms (RD -0.15 [95% CI -0.33, -0.04]), less frequent non-cardiogenic shock or systemic inflammatory response syndrome (SIRS) (RD -0.35 [95% CI -0.64, -0.07]), lower lymphocyte count (ES -0.16 × 109/uL [95% CI -0.30, -0.01]), lower C-reactive protein (ES -28.5 mg/L [95% CI -46.3, -10.7]), and lower troponin (ES -0.14 ng/mL [95% CI -0.26, -0.03]). Patients admitted in the Omicron versus Alpha eras were younger (ES -1.6 years [95% CI -2.5, -0.8]), had less frequent SIRS (RD -0.18 [95% CI -0.30, -0.05]), lower lymphocyte count (ES -0.39 × 109/uL [95% CI -0.52, -0.25]), lower troponin (ES -0.16 ng/mL [95% CI -0.30, -0.01]) and less frequently received anticoagulation therapy (RD -0.19 [95% CI -0.37, -0.04]). Length of hospitalization was shorter in the Delta versus Alpha eras (-1.3 days [95% CI -2.3, -0.4]). Interpretation: Our study suggested that MIS-C clinical phenotypes varied across SARS-CoV-2 eras, with patients in Delta and Omicron eras being younger and less sick. EHR data can be effectively leveraged to identify rare complications of pandemic diseases and their variation over time. Funding: None.

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