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1. Causal Graph Aided Causal Discovery in an Observational Aneurysmal Subarachnoid Hemorrhage Study

Author

Berzuini, Carlo, Luciani, Davide, and Patel, Hiren C.

Subjects
Statistics - Methodology, Statistics - Machine Learning
Abstract

Causal inference methods for observational data are increasingly recognized as a valuable complement to randomized clinical trials (RCTs). They can, under strong assumptions, emulate RCTs or help refine their focus. Our approach to causal inference uses causal directed acyclic graphs (DAGs). We are motivated by a concern that many observational studies in medicine begin without a clear definition of their objectives, without awareness of the scientific potential, and without tools to identify the necessary in itinere adjustments. We present and illustrate methods that provide "midway insights" during study's course, identify meaningful causal questions within the study's reach and point to the necessary data base enhancements for these questions to be meaningfully tackled. The method hinges on concepts of identification and positivity. Concepts are illustrated through an analysis of data generated by patients with aneurysmal Subarachnoid Hemorrhage (aSAH) halfway through a study, focusing in particular on the consequences of external ventricular drain (EVD) in strata of the aSAH population. In addition, we propose a method for multicenter studies, to monitor the impact of changes in practice at an individual center's level, by leveraging principles of instrumental variable (IV) inference., Comment: 30 pages in 13pt font. 4 TIKZ figures. 9 PDF figures

Published
2024

4. Statistical Guidelines for Handling Missing Data in Traumatic Brain Injury Clinical Research

Author

Nielson, Jessica L, Cooper, Shelly R, Seabury, Seth A, Luciani, Davide, Fabio, Anthony, Temkin, Nancy R, Ferguson, Adam R, Adeoye, Opeolu, Badjatia, Neeraj, Boase, Kim, Bodien, Yelena, Bullock, M Ross, Chesnut, Randall, Corrigan, John D, Crawford, Karen, Diaz-Arrastia, Ramon, Dikmen, Sureyya, Duhaime, Ann-Christine, Ellenbogen, Richard, Feeser, V Ramana, Foreman, Brandon, Gardner, Raquel, Gaudette, Etienne, Giacino, Joseph, Goldman, Dana, Gonzalez, Luis, Gopinath, Shankar, Gullapalli, Rao, Hemphill, J Claude, Hotz, Gillian, Jain, Sonia, Korley, Frederick K, Kramer, Joel, Kreitzer, Natalie, Levin, Harvey, Lindsell, Chris, Machamer, Joan, Madden, Christopher, Manley, Geoffrey T, Martin, Alastair, McAllister, Thomas, McCrea, Michael, Merchant, Randall, Mukherjee, Pratik, Nelson, Lindsay, Ngwenya, Laura B, Noel, Florence, Okonkwo, David, Palacios, Eva, Perl, Daniel, Puccio, Ava, Rabinowitz, Miri, Robertson, Claudia, Rosand, Jonathan, Sander, Angelle, Satris, Gabriella, Schnyer, David, Sherer, Mark, Stein, Murray, Taylor, Sabrina, Toga, Arthur, Valadka, Alex, Vassar, Mary, Vespa, Paul, Wang, Kevin, Yue, John K, Yuh, Esther, and Zafonte, Ross

Subjects
Traumatic Head and Spine Injury, Neurosciences, Brain Disorders, Clinical Research, Traumatic Brain Injury (TBI), Clinical Trials and Supportive Activities, Physical Injury - Accidents and Adverse Effects, Neurological, Injuries and accidents, Good Health and Well Being, Brain Injuries, Traumatic, Child, Data Interpretation, Statistical, Databases, Factual, Guidelines as Topic, Humans, assessment tools, missing data, statistical guidelines, TBI, TRACK-TBI Investigators, Clinical Sciences, Neurology & Neurosurgery
Abstract

Missing data is a persistent and unavoidable problem in even the most carefully designed traumatic brain injury (TBI) clinical research. Missing data patterns may result from participant dropout, non-compliance, technical issues, or even death. This review describes the types of missing data that are common in TBI research, and assesses the strengths and weaknesses of the statistical approaches used to draw conclusions and make clinical decisions from these data. We review recent innovations in missing values analysis (MVA), a relatively new branch of statistics, as applied to clinical TBI data. Our discussion focuses on studies from the International Traumatic Brain Injury Research (InTBIR) initiative project: Transforming Research and Clinical Knowledge in TBI (TRACK-TBI), Collaborative Research on Acute TBI in Intensive Care Medicine in Europe (CREACTIVE), and Approaches and Decisions in Acute Pediatric TBI Trial (ADAPT). In addition, using data from the TRACK-TBI pilot study (n = 586) and the completed clinical trial assessing valproate (VPA) for the treatment of post-traumatic epilepsy (n = 379) we present real-world examples of typical missing data patterns and the application of statistical techniques to mitigate the impact of missing data in order to draw sound conclusions from ongoing clinical studies.

Published
2021

5. Contributors

Author

Altomare, Cosimo Damiano, primary, Amoroso, Nicola, additional, Andola, Priyanka, additional, Aydın, Ahmet, additional, Bacelo, Daniel E., additional, Ballabio, Davide, additional, Banerjee, Adrija, additional, Benfenati, Emilio, additional, Bhargav, Anasuya, additional, Biswas, Avratanu, additional, Biziukova, Nadezhda Yu, additional, Çalışkan, Elifcan, additional, Campillo, Nuria E., additional, Charehsaz, Mohammad, additional, Chatterjee, Mainak, additional, Chauhan, Shweta Singh, additional, Chaurasia, Pratibha, additional, Cherkasov, Artem, additional, Chhabra, Sonali, additional, Choudhary, Aishwarya, additional, Ciriaco, Fulvio, additional, Colombo, Erika, additional, Consonni, Viviana, additional, Coutinho, Evans C., additional, Daré, Joyce K., additional, de Castro Gertrudes, Jadson, additional, de Faria, Adriana C., additional, Doganis, Philip, additional, Dubey, Gurudutt, additional, Duchowicz, Pablo R., additional, Dunbrack, Jr, Roland L., additional, Ester, Martin, additional, Fernandez, Michael, additional, Fioressi, Silvina E., additional, Freitas, Matheus P., additional, Gambacorta, Nicola, additional, Geronikaki, Athina, additional, Gini, Giuseppina, additional, Gousiadou, Chrysoula, additional, Guruprasad, Lalitha, additional, Hamidizadeh, Atia, additional, Ivanov, Sergey M., additional, Jamal, Tanya, additional, Janairo, Jose Isagani B., additional, Jayaram, B., additional, Joshi, Karan, additional, Kabieva, Shuanat Sh, additional, Kar, Supratik, additional, Karatzas, Pantelis, additional, Kashyap, Kushagra, additional, Kirubakaran, Sivapriya, additional, Laxman, Durgam, additional, Leszczynski, Jerzy, additional, Lombardo, Anna, additional, Luciani, Davide, additional, Mahale, Manas, additional, Maltarollo, Vinícius Gonçalves, additional, Martínez, María J., additional, Martis, Elvis A.F., additional, Mastrolorito, Fabrizio, additional, Matsuzaka, Yasunari, additional, Murumkar, Prashant R., additional, Nantasenamat, Chanin, additional, Nápoles-Duarte, J.M., additional, Naresh, Gatta K.R.S., additional, Naveiro, Roi, additional, Nicolotti, Orazio, additional, Önlü, Serli, additional, Pandey, Mohit, additional, Parker, Mitchell I., additional, Parkesh, Raman, additional, Parthasarathi, Ramakrishnan, additional, Pereira, Ingrid V., additional, Petrou, Anthi, additional, Ponzoni, Ignacio, additional, Poroikov, Vladimir V., additional, Prajapat, Devendra, additional, Radaeva, Mariia, additional, Ramachandran, Srinivasan, additional, Ríos-Insua, David, additional, Roy, Kunal, additional, Saçan, Melek Türker, additional, Sarimveis, Haralambos, additional, Sehrawat, Ashish, additional, Siddiqi, Mohammad Imran, additional, Singh, Anurag, additional, Sipahi, Hande, additional, Sotiropoulos, Iason, additional, Soto, Axel J., additional, Swarup, Sapna, additional, Tarasova, Olga A., additional, Todeschini, Roberto, additional, Togo, Maria Vittoria, additional, Tondo, Anna Rita, additional, Trisciuzzi, Daniela, additional, Tsantili-Kakoulidou, Anna, additional, Tsiros, Periklis, additional, Tsopelas, Fotios, additional, Tugcu, Gulcin, additional, Uesawa, Yoshihiro, additional, Vallianatou, Theodosia, additional, Veríssimo, Gabriel Corrêa, additional, Yadav, Mange Ram, additional, Yadav, Rasana, additional, and Yang, Siyun, additional

Published
2023
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7. A probabilistic network for the diagnosis of acute cardiopulmonary diseases

Author

Magrini, Alessandro, Luciani, Davide, and Stefanini, Federico Mattia

Subjects
Statistics - Machine Learning, Statistics - Applications, 62F15, 62P10
Abstract

In this paper, the development of a probabilistic network for the diagnosis of acute cardiopulmonary diseases is presented. This paper is a draft version of the article published after peer review in 2018 (https://doi.org/10.1002/bimj.201600206). A panel of expert physicians collaborated to specify the qualitative part, that is a directed acyclic graph defining a factorization of the joint probability distribution of domain variables. The quantitative part, that is the set of all conditional probability distributions defined by each factor, was estimated in the Bayesian paradigm: we applied a special formal representation, characterized by a low number of parameters and a parameterization intelligible for physicians, elicited the joint prior distribution of parameters from medical experts, and updated it by conditioning on a dataset of hospital patient records using Markov Chain Monte Carlo simulation. Refinement was cyclically performed until the probabilistic network provided satisfactory Concordance Index values for a selection of acute diseases and reasonable inference on six fictitious patient cases. The probabilistic network can be employed to perform medical diagnosis on a total of 63 diseases (38 acute and 25 chronic) on the basis of up to 167 patient findings., Comment: The DOI of the article published after peer review was added. A technical detail was added in Section 3.2, Formula 8 (as a consequence, the ID of all the subsequent formulas result augmented by 1 with respect to the previous version). The prior standard deviation of the Gamma distribution in Table 4 was fixed (in the previous version, the prior variance was indicated, instead)

Published
2016
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13. Benefit–risk assessment in a post-market setting: a case study integrating real-life experience into benefit–risk methodology†

Author

Hallgreen, Christine E., van den Ham, Hendrika A., Mt-Isa, Shahrul, Ashworth, Simon, Hermann, Richard, Hobbiger, Steve, Luciani, Davide, Micaleff, Alain, Thomson, Andrew, Wang, Nan, van Staa, Tjeerd P., Downey, Gerald, Hirsch, Ian, Hockley, Kimberley, Juhaeri, Juhaeri, Metcalf, Marilyn, Mwangi, Jeremiah, Nixon, Richard, Peters, Ruth, Stoeckert, Isabelle, Waddingham, Ed, Tzoulaki, Ioanna, Ashby, Deborah, and Wise, Lesley

Published
2014
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24. A probabilistic network for the diagnosis of acute cardiopulmonary diseases.

Author

Magrini, Alessandro, Luciani, Davide, and Stefanini, Federico M.

Abstract

In this paper, the development of a probabilistic network for the diagnosis of acute cardiopulmonary diseases is presented in detail. A panel of expert physicians collaborated to specify the qualitative part, which is a directed acyclic graph defining a factorization of the joint probability distribution of domain variables into univariate conditional distributions. The quantitative part, which is a set of parametric models defining these univariate conditional distributions, was estimated following the Bayesian paradigm. In particular, we exploited an original reparameterization of Beta and categorical logistic regression models to elicit the joint prior distribution of parameters from medical experts, and updated it by conditioning on a dataset of hospital records via Markov chain Monte Carlo simulation. Refinement was iteratively performed until the probabilistic network provided satisfactory concordance index values for several acute diseases and reasonable diagnosis for six fictitious patient cases. The probabilistic network can be employed to perform medical diagnosis on a total of 63 diseases (38 acute and 25 chronic) on the basis of up to 167 patient findings. [ABSTRACT FROM AUTHOR]

Published
2018
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25. Benefit-risk assessment in a post-market setting: a case study integrating real-life experience into benefit-risk methodology

Author

Sub Pharmacoepidemiology, Sub Pharmacotherapy, Theoretical, Pharmacoepidemiology and Clinical Pharmacology, Hallgreen, Christine E, van den Ham, Hendrika A, Mt-Isa, Shahrul, Ashworth, Simon, Hermann, Richard, Hobbiger, Steve, Luciani, Davide, Micaleff, Alain, Thomson, Andrew, Wang, Nan, van Staa, Tjeerd P, Downey, Gerald, Hirsch, Ian, Hockley, Kimberley, Juhaeri, Juhaeri, Metcalf, Marilyn, Mwangi, Jeremiah, Nixon, Richard, Peters, Ruth, Stoeckert, Isabelle, Waddingham, Ed, Tzoulaki, Ioanna, Ashby, Deborah, Wise, Lesley, Sub Pharmacoepidemiology, Sub Pharmacotherapy, Theoretical, Pharmacoepidemiology and Clinical Pharmacology, Hallgreen, Christine E, van den Ham, Hendrika A, Mt-Isa, Shahrul, Ashworth, Simon, Hermann, Richard, Hobbiger, Steve, Luciani, Davide, Micaleff, Alain, Thomson, Andrew, Wang, Nan, van Staa, Tjeerd P, Downey, Gerald, Hirsch, Ian, Hockley, Kimberley, Juhaeri, Juhaeri, Metcalf, Marilyn, Mwangi, Jeremiah, Nixon, Richard, Peters, Ruth, Stoeckert, Isabelle, Waddingham, Ed, Tzoulaki, Ioanna, Ashby, Deborah, and Wise, Lesley

Published
2014

26. Balancing benefit and risk of medicines: a systematic review and classification of available methodologies

Author

Sub Pharmacoepidemiology, Pharmacoepidemiology and Clinical Pharmacology, Mt-Isa, Shahrul, Hallgreen, Christine E, Wang, Nan, Callréus, Torbjörn, Genov, Georgy, Hirsch, Ian, Hobbiger, Stephen F, Hockley, Kimberley S, Luciani, Davide, Phillips, Lawrence D, Quartey, George, Sarac, Sinan B, Stoeckert, Isabelle, Tzoulaki, Ioanna, Micaleff, Alain, Ashby, Deborah, IMI-PROTECT benefit-risk participants, van Staa, Tjeerd, Sub Pharmacoepidemiology, Pharmacoepidemiology and Clinical Pharmacology, Mt-Isa, Shahrul, Hallgreen, Christine E, Wang, Nan, Callréus, Torbjörn, Genov, Georgy, Hirsch, Ian, Hobbiger, Stephen F, Hockley, Kimberley S, Luciani, Davide, Phillips, Lawrence D, Quartey, George, Sarac, Sinan B, Stoeckert, Isabelle, Tzoulaki, Ioanna, Micaleff, Alain, Ashby, Deborah, IMI-PROTECT benefit-risk participants, and van Staa, Tjeerd

Published
2014

27. Food Fried in Extra-Virgin Olive Oil Improves Postprandial Insulin Response in Obese, Insulin-Resistant Women

Author

Farnetti, Sara, Malandrino, Noemi, Luciani, Davide, Gasbarrini, Giovanni Battista, Capristo, Esmeralda, Capristo, Esmeralda (ORCID:0000-0002-5753-3495), Farnetti, Sara, Malandrino, Noemi, Luciani, Davide, Gasbarrini, Giovanni Battista, Capristo, Esmeralda, and Capristo, Esmeralda (ORCID:0000-0002-5753-3495)

Abstract

The benefits of low glycemic load (GL) diets on clinical outcome in several metabolic and cardiovascular diseases have extensively been demonstrated. The GL of a meal can be affected by modulating the bioavailability of carbohydrates or by changing food preparation. We investigated the effect on plasma glucose and insulin response in lean and obese women of adding raw or fried extra-virgin olive oil to a carbohydrate-containing meal. After an overnight fast, 12 obese insulin-resistant women (body mass index [BMI], 32.8 ± 2.2 kg/m(2)) and five lean subjects (BMI, 22.2 ± 1.2 kg/m(2)) were randomly assigned to receive two different meals (designated A and B). Meal A was composed of 60 g of pasta made from wheat flour and 150 g of grilled courgettes with 25 g of uncooked oil. Meal B included 15 g of oil in the 150 g of deep-fried courgettes and 10 g of oil in the 60 g of stir-fried pasta. Both meals included 150 g of apple. Blood samples were collected at baseline and every 30 minutes over a 3-hour post-meal period and were tested for levels of glucose, insulin, C-peptide, and triglycerides. The area under the curve (AUC) values were calculated. In obese women the AUCs for C-peptide were significantly higher after meal A than after meal B at 120 minutes (W [Wilcoxon sign rank test] = 27.5, P = .0020), 150 minutes (W = 26.5, P = .0039), and 180 minutes (W = 26.5, P = .0039). No differences were found in lean subjects. This study demonstrated that in obese, insulin-resistant women, food fried in extra-virgin olive oil significantly reduced both insulin and C-peptide responses after a meal.

Published
2011

28. Calibration belt for quality-of-care assessment based on dichotomous outcomes

Author

Finazzi, S, Poole, D, Luciani, D, Cogo, P, Bertolini, G, Bertolini, G., LUCIANI, DAVIDE, Finazzi, S, Poole, D, Luciani, D, Cogo, P, Bertolini, G, Bertolini, G., and LUCIANI, DAVIDE

Abstract

Prognostic models applied in medicine must be validated on independent samples, before their use can be recommended. The assessment of calibration, i.e., the model's ability to provide reliable predictions, is crucial in external validation studies. Besides having several shortcomings, statistical techniques such as the computation of the standardized mortality ratio (SMR) and its confidence intervals, the Hosmer-Lemeshow statistics, and the Cox calibration test, are all non-informative with respect to calibration across risk classes. Accordingly, calibration plots reporting expected versus observed outcomes across risk subsets have been used for many years. Erroneously, the points in the plot (frequently representing deciles of risk) have been connected with lines, generating false calibration curves. Here we propose a methodology to create a confidence band for the calibration curve based on a function that relates expected to observed probabilities across classes of risk. The calibration belt allows the ranges of risk to be spotted where there is a significant deviation from the ideal calibration, and the direction of the deviation to be indicated. This method thus offers a more analytical view in the assessment of quality of care, compared to other approaches. © 2011 Finazzi et al.

Published
2011

36. Simplified electrophysiological evaluation of peripheral nerves in critically ill patients: the Italian multi-centre CRIMYNE study

Author

Latronico, Nicola, Bertolini, Guido, Guarneri, Bruno, Botteri, Marco, Peli, Elena, Andreoletti, Serena, Bera, Paola, Luciani, Davide, Nardella, Anna, Vittorielli, Elena, Simini, Bruno, and Candiani, Andrea

Abstract

Introduction Critical illness myopathy and/or neuropathy (CRIMYNE) is frequent in intensive care unit (ICU) patients. Although complete electrophysiological tests of peripheral nerves and muscles are essential to diagnose it, they are time-consuming, precluding extensive use in daily ICU practice. We evaluated whether a simplified electrophysiological investigation of only two nerves could be used as an alternative to complete electrophysiological tests.Methods In this prospective, multi-centre study, 92 ICU patients were subjected to unilateral daily measurements of the action potential amplitude of the sural and peroneal nerves (compound muscle action potential [CMAP]). After the first ten days, complete electrophysiological investigations were carried out weekly until ICU discharge or death. At hospital discharge, complete neurological and electrophysiological investigations were performed.Results Electrophysiological signs of CRIMYNE occurred in 28 patients (30.4%, 95% confidence interval [CI] 21.9% to 40.4%). A unilateral peroneal CMAP reduction of more than two standard deviations of normal value showed the best combination of sensitivity (100%) and specificity (67%) in diagnosing CRIMYNE. All patients developed the electrophysiological signs of CRIMYNE within 13 days of ICU admission. Median time from ICU admission to CRIMYNE was six days (95% CI five to nine days). In 10 patients, the amplitude of the nerve action potential dropped progressively over a median of 3.0 days, and in 18 patients it dropped abruptly within 24 hours. Multi-organ failure occurred in 21 patients (22.8%, 95% CI 15.4% to 32.4%) and was strongly associated with CRIMYNE (odds ratio 4.58, 95% CI 1.64 to 12.81). Six patients with CRIMYNE died: three in the ICU and three after ICU discharge. Hospital mortality was similar in patients with and without CRIMYNE (21.4% and 17.2%; p = 0.771). At ICU discharge, electrophysiological signs of CRIMYNE persisted in 18 (64.3%) of 28 patients. At hospital discharge, diagnoses in the 15 survivors were critical illness myopathy (CIM) in six cases, critical illness polyneuropathy (CIP) in four, combined CIP and CIM in three, and undetermined in two.Conclusion A peroneal CMAP reduction below two standard deviations of normal value accurately identifies patients with CRIMYNE. These should have full neurological and neurophysiological evaluations before discharge from the acute hospital.

Published
2007
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37. Anti-beta 2-glycoprotein I, antiprothrombin antibodies, and the risk of thrombosis in the antiphospholipid syndrome.

Author

Galli M, Luciani D, Bertolini G, and Barbui T

Subjects
Antibodies chemistry, Cardiolipins blood, Cardiolipins immunology, Female, Glycoproteins chemistry, Humans, Odds Ratio, Pregnancy, Pregnancy Complications, Hematologic, Prothrombin chemistry, Retrospective Studies, beta 2-Glycoprotein I, Antiphospholipid Syndrome blood, Glycoproteins immunology, Prothrombin immunology, Thrombosis blood
Published
2003
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