Investigating the correlation between chemical parameters, risk assessment, and sensitivity analysis of fluoride and nitrate in regional groundwater sources using Monte Carlo

morovati, Roya; Badeenezhad, Ahmad; Najafi, Mitra; Azhdarpoor, Abooalfazl

doi:10.1007/s10653-023-01819-x

Environ Geochem Health

2023

DOI: 10.1007/s10653-023-01819-x

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Investigating the correlation between chemical parameters, risk assessment, and sensitivity analysis of fluoride and nitrate in regional groundwater sources using Monte Carlo

Roya morovati,

Ahmad Badeenezhad,

Mitra Najafi

et al.

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2024

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Cited by 4 publications

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Comparing robotic and open partial nephrectomy under the prism of surgical precision: a meta-analysis of the average blood loss rate as a novel variable

Artsitas,

Koronaki

et al. 2024

J Robotic Surg

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Exploration of surgical precision in robotic procedures is extensive, yet lacks a unified framework for comparability. This study examines tissue handling precision by comparing the per-minute blood loss rate between robotic and open partial nephrectomy. A literature search from August 2022 to June 2024 identified 43 relevant studies providing data on estimated blood loss and procedure duration. The expected values and standard errors of these variables were used to compute the per-minute blood loss rate (Q). Meta-analytical methods estimated pooled and subgroup-level mean differences, favoring robotic surgery (MDQ = − 1.043 ml/min, CI95% = [− 1.338; − 0.747]). Subgroup analyses by publication year, patient matching, referral center count, and ROBINS-I status consistently supported this advantage. Sensitivity analyses confirmed the above benefit in studies with increased accuracy in reported results (MDQ = – 0.957 ml/min, CI95% = [– 1.269; – 0.646]), low risk of bias involving matched comparisons (MDQ = – 0.563 ml/min, CI95% = [– 0.716; – 0.410]), large sample sizes and increased statistical power (MDQ = – 0.780 ml/min, CI95% = [– 1.134; – 0.425]), and multicenter analyses with patient matching (MDQ = – 0.481 ml/min, CI95% = [– 0.698; – 0.263]). The subsequent analysis of correlation between the original variables suggested a slight reduction in the robotic advantage when the latter were proportionally related. Multilevel meta-regression at both temporal and qualitative scales consistently indicated a comparative benefit of the robotic approach. Potentially, lower per-minute blood loss compared to open surgery suggests that robotic partial nephrectomy demonstrates enhanced precision in tissue handling.

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Comparing robotic and open partial nephrectomy under the prism of surgical precision: a meta-analysis of the average blood loss rate as a novel variable

Artsitas,

Koronaki

et al. 2024

J Robotic Surg

View full text Add to dashboard Cite

show abstract

Groundwater health risk assessment and its temporal and spatial evolution based on trapezoidal fuzzy number-Monte Carlo stochastic simulation: A case study in western Jilin province

Li,

Bian,

Ruan

et al. 2024

Ecotoxicology and Environmental Safety

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Application of Monte Carlo simulation and artificial neural network model to probabilistic health risk assessment in fluoride-endemic areas

Islam,

Sinha,

Hussain

et al. 2024

Heliyon

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Investigating the correlation between chemical parameters, risk assessment, and sensitivity analysis of fluoride and nitrate in regional groundwater sources using Monte Carlo

Cited by 4 publications

References 44 publications

Comparing robotic and open partial nephrectomy under the prism of surgical precision: a meta-analysis of the average blood loss rate as a novel variable

Comparing robotic and open partial nephrectomy under the prism of surgical precision: a meta-analysis of the average blood loss rate as a novel variable

Groundwater health risk assessment and its temporal and spatial evolution based on trapezoidal fuzzy number-Monte Carlo stochastic simulation: A case study in western Jilin province

Application of Monte Carlo simulation and artificial neural network model to probabilistic health risk assessment in fluoride-endemic areas

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