Browsing by Author "Chen L."

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    Optimal algorithms for scheduling under time-of-use tariffs
    (Springer, 2021) Chen L.; Megow N.; Rischke R.; Stougie L.; Verschae J.
    © 2021, The Author(s).We consider a natural generalization of classical scheduling problems to a setting in which using a time unit for processing a job causes some time-dependent cost, the time-of-use tariff, which must be paid in addition to the standard scheduling cost. We focus on preemptive single-machine scheduling and two classical scheduling cost functions, the sum of (weighted) completion times and the maximum completion time, that is, the makespan. While these problems are easy to solve in the classical scheduling setting, they are considerably more complex when time-of-use tariffs must be considered. We contribute optimal polynomial-time algorithms and best possible approximation algorithms. For the problem of minimizing the total (weighted) completion time on a single machine, we present a polynomial-time algorithm that computes for any given sequence of jobs an optimal schedule, i.e., the optimal set of time slots to be used for preemptively scheduling jobs according to the given sequence. This result is based on dynamic programming using a subtle analysis of the structure of optimal solutions and a potential function argument. With this algorithm, we solve the unweighted problem optimally in polynomial time. For the more general problem, in which jobs may have individual weights, we develop a polynomial-time approximation scheme (PTAS) based on a dual scheduling approach introduced for scheduling on a machine of varying speed. As the weighted problem is strongly NP-hard, our PTAS is the best possible approximation we can hope for. For preemptive scheduling to minimize the makespan, we show that there is a comparably simple optimal algorithm with polynomial running time. This is true even in a certain generalized model with unrelated machines.
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    Reverse Triggering Dyssynchrony 24 h after Initiation of Mechanical Ventilation
    (Lippincott Williams and Wilkins, 2021) Mellado Artigas R.; Damiani L.F.; Pham T.; Chen L.; Rauseo M.; Telias I.; Soliman I.; Junhasavasdikul D.; Santis C.; Smith O.M.; Comtois N.; Sinderby C.; Heunks L.; Brochard L.; Piraino T.; Telias I.; Mellado Artigas R.; Damiani L.F.; Pham T.; Chen L.; Rauseo M.; Telias I.; Soliman I.; Junhasavasdikul D.; Santis C.; Goligher E.; Brochard L.; Smith O.M.; Mellado Artigas R.; Mellado Artigas R.; Comtois N.; Damiani L.F.; Goligher E.; Goligher E.; Heunks L.; Junhasavasdikul D.; Pham T.; Pham T.; Pham T.
    © 2021 Lippincott Williams and Wilkins. All rights reserved.Background: Reverse triggering is a delayed asynchronous contraction of the diaphragm triggered by passive insufflation by the ventilator in sedated mechanically ventilated patients. The incidence of reverse triggering is unknown. This study aimed at determining the incidence of reverse triggering in critically ill patients under controlled ventilation. Methods: In this ancillary study, patients were continuously monitored with a catheter measuring the electrical activity of the diaphragm. A method for automatic detection of reverse triggering using electrical activity of the diaphragm was developed in a derivation sample and validated in a subsequent sample. The authors assessed the predictive value of the software. In 39 recently intubated patients under assist-control ventilation, a 1-h recording obtained 24 h after intubation was used to determine the primary outcome of the study. The authors also compared patients' demographics, sedation depth, ventilation settings, and time to transition to assisted ventilation or extubation according to the median rate of reverse triggering. Results: The positive and negative predictive value of the software for detecting reverse triggering were 0.74 (95% CI, 0.67 to 0.81) and 0.97 (95% CI, 0.96 to 0.98). Using a threshold of 1 μV of electrical activity to define diaphragm activation, median reverse triggering rate was 8% (range, 0.1 to 75), with 44% (17 of 39) of patients having greater than or equal to 10% of breaths with reverse triggering. Using a threshold of 3 μV, 26% (10 of 39) of patients had greater than or equal to 10% reverse triggering. Patients with more reverse triggering were more likely to progress to an assisted mode or extubation within the following 24 h (12 of 39 [68%]) vs. 7 of 20 [35%]; P = 0.039). Conclusions: Reverse triggering detection based on electrical activity of the diaphragm suggests that this asynchrony is highly prevalent at 24 h after intubation under assist-control ventilation. Reverse triggering seems to occur during the transition phase between deep sedation and the onset of patient triggering.
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    Risk Factors for Thyroid Dysfunction in Pregnancy: An Individual Participant Data Meta-Analysis
    (2024) Osinga J.A.; Liu Y.; Mannisto T.; Vafeiadi M.; Tao F.-B.; Vaidya B.; Vrijkotte T.G.; Mosso L.; Bassols J.; Lopez-Bermejo A.; Boucai L.; Aminorroaya A.; Feldt-Rasmussen U.; Hisada A.; Yoshinaga J.; Broeren M.A.; Itoh S.; Kishi R.; Ashoor G.; Chen L.; Veltri F.; Lu X.; Taylor P.N.; Brown S.J.; Chatzi L.; Popova P.V.; Grineva E.N.; Ghafoor F.; Pirzada A.; Kianpour M.; Oken E.; Suvanto E.; Hattersley A.; Rebagliato M.; Riano-Galan I.; Irizar A.; Vrijheid M.; Delgado-Saborit J.M.; Fernandez-Somoano A.; Santa-Marina L.; Boelaert K.; Brenta G.; Dhillon-Smith R.; Dosiou C.; Eaton J.L.; Guan H.; Lee S.Y.; Maraka S.; Morris-Wiseman L.F.; Nguyen C.T.; Shan Z.; Guxens M.; Pop V.J.; Walsh J.P.; Nicolaides K.H.; D'Alton M.E.; Visser W.E.; Carty D.M.; Delles C.; Nelson S.M.; Alexander E.K.; Chaker L.; Palomaki G.E.; Peeters R.P.; Bliddal S.; Huang K.; Poppe K.G.; Pearce E.N.; Derakhshan A.; Korevaar T.I.; NCD Risk Factor Collaboration (NCD-RisC)
    Copyright 2024, © American Thyroid Association; Published by Mary Ann Liebert, Inc.Background: International guidelines recommend targeted screening to identify gestational thyroid dysfunction. However, currently used risk factors have questionable discriminative ability. We quantified the risk for thyroid function test abnormalities for a subset of risk factors currently used in international guidelines. Methods: We included prospective cohort studies with data on gestational maternal thyroid function and potential risk factors (maternal age, body mass index [BMI], parity, smoking status, pregnancy through in vitro fertilization, twin pregnancy, gestational age, maternal education, and thyroid peroxidase antibody [TPOAb] or thyroglobulin antibody [TgAb] positivity). Exclusion criteria were pre-existing thyroid disease and use of thyroid interfering medication. We analyzed individual participant data using mixed-effects regression models. Primary outcomes were overt and subclinical hypothyroidism and a treatment indication (defined as overt hypothyroidism, subclinical hypothyroidism with thyrotropin >10 mU/L, or subclinical hypothyroidism with TPOAb positivity). Results: The study population comprised 65,559 participants in 25 cohorts. The screening rate in cohorts using risk factors currently recommended (age >30 years, parity ≥2, BMI ≥40) was 58%, with a detection rate for overt and subclinical hypothyroidism of 59%. The absolute risk for overt or subclinical hypothyroidism varied <2% over the full range of age and BMI and for any parity. Receiver operating characteristic curves, fitted using maternal age, BMI, smoking status, parity, and gestational age at blood sampling as explanatory variables, yielded areas under the curve ranging from 0.58 to 0.63 for the primary outcomes. TPOAbs/TgAbs positivity was associated with overt hypothyroidism (approximate risk for antibody negativity 0.1%, isolated TgAb positivity 2.4%, isolated TPOAb positivity 3.8%, combined antibody positivity 7.0%; p < 0.001), subclinical hypothyroidism (risk for antibody negativity 2.2%, isolated TgAb positivity 8.1%, isolated TPOAb positivity 14.2%, combined antibody positivity 20.0%; p < 0.001) and a treatment indication (risk for antibody negativity 0.2%, isolated TgAb positivity 2.2%, isolated TPOAb positivity 3.0%, and combined antibody positivity 5.1%; p < 0.001). Twin pregnancy was associated with a higher risk of overt hyperthyroidism (5.6% vs. 0.7%; p < 0.001). Conclusions: The risk factors assessed in this study had poor predictive ability for detecting thyroid function test abnormalities, questioning their clinical usability for targeted screening. As expected, TPOAb positivity (used as a benchmark) was a relevant risk factor for (subclinical) hypothyroidism. These results provide insights into different risk factors for gestational thyroid dysfunction.