Psychological distress in adolescence and later economic and health outcomes in the United States population: A retrospective and modeling study. by Nathaniel Z Counts, Noemi Kreif, Timothy B Creedon, David E Bloom

“…This study faced limitations, including potential unmeasured confounding, missing data, and challenges to generalizability.<h4>Conclusions</h4>Our findings showed the impacts of adolescent mental health policies on the federal budget and found potentially large effects on the economy if policies achieve population-level change.…”
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Body Mass Index at Pediatric Leukemia Diagnosis and the Risks of Relapse and Mortality: Findings from a Single Institution and Meta-analysis by Ashleigh M. Saenz, Stacie Stapleton, Raquel G. Hernandez, Greg A. Hale, Neil A. Goldenberg, Skai Schwartz, Ernest K. Amankwah

“…The study included 181 pediatric leukemia patients. Sporadic missing data were multiply imputed, and hazard ratios (HR) and 95% confidence intervals (95% CI) were calculated using Cox proportional hazard. …”
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Clinical efficacy of 0.1% cyclosporine A in dry eye patients with inadequate responses to 0.05% cyclosporine A: a switching, prospective, open-label, multicenter study by Sook Hyun Yoon, Eun Chul Kim, In-Cheon You, Chul Young Choi, Jae Yong Kim, Jong Suk Song, Joon Young Hyon, Hong Kyun Kim, Kyoung Yul Seo

“…Statistical analysis was performed on the full analysis set (FAS) using the Markov Chain Monte Carlo (MCMC) method to account for missing data. After switching to 0.1% CsA, subjective symptoms assessed by the Symptom Assessment in Dry Eye (SANDE) and Ocular Discomfort Scale (ODS) showed improvement (p < 0.0001). …”
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National and subnational plans for primary prevention and early detection of oral and oropharyngeal cancer: a scoping review by Marcia Frias Pinto Marinho, Maria Clara Frias Lobo Marinho, Guido Artemio Marañón-Vásquez, Keith Bullia da Fonseca Simas, Mário José Romañach, Aline Corrêa Abrahão, Maria Augusta Visconti Rocha Pinto, Lucianne Cople Maia de Faria, Michelle Agostini

“…Despite the high oral and oropharyngeal cancer incidence in many countries, most cancer plans only indirectly covered it and showed a great diversity of preventive strategies. Missing data in available documents should not imply an absence of an oral and oropharyngeal cancer policy. …”
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Impact of non-invasive oxygen reserve index versus standard SpO2 monitoring on peripheral oxygen saturation during endotracheal intubation in the intensive care unit: Protocol for... by Hugo Hille, Aurélie Le Thuaut, Pierre Asfar, Quentin Quelven, Emmanuelle Mercier, Anthony Le Meur, Jean-Pierre Quenot, Virginie Lemiale, Grégoire Muller, Martin Cour, Alexis Ferré, Asael Berge, Anaïs Curtiaud, Maxime Touron, Gaetan Plantefeve, Jean-Charles Chakarian, Jean-Damien Ricard, Gwenhael Colin, Arthur Orieux, Patrick Girardie, Mathieu Jozwiak, Manon Rouaud, Camille Juhel, Jean Reignier, Jean-Baptiste Lascarrou, CRICS-TRIGGERSEP Network

“…Assuming a 10% standard deviation for the lowest SpO2 value in the control group, no missing data, and crossover of 5% of patients, with the bilateral alpha risk set at 0.05, including 950 patients will provide 85% power for detecting a 2% between-group absolute difference in the lowest SpO2 value. …”
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Large language models generating synthetic clinical datasets: a feasibility and comparative analysis with real-world perioperative data by Austin A. Barr, Joshua Quan, Eddie Guo, Emre Sezgin, Emre Sezgin

“…BackgroundClinical data is instrumental to medical research, machine learning (ML) model development, and advancing surgical care, but access is often constrained by privacy regulations and missing data. Synthetic data offers a promising solution to preserve privacy while enabling broader data access. …”
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Quality of routine malaria data captured at primary health facilities in the Hohoe Municipality, Ghana by Christopher Ayisah, Thywill Worlase Kpenu, Edem Kojo Dzantor, Clement Tetteh Narh

“…A data validation tool was developed to determine the quality of malaria indicators measuring availability, completeness (percentage of missing data), and accuracy. The data was analysed descriptively using Microsoft excel. …”
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Use of Machine Learning to Predict the Incidence of Type 2 Diabetes Among Relatively Healthy Adults: A 10-Year Longitudinal Study in Taiwan by Ying-Qiang Liu, Tzu-Wei Chang, Lung-Chun Lee, Chia-Yu Chen, Pi-Shan Hsu, Yu-Tse Tsan, Chao-Tung Yang, Wei-Min Chu

“…Individuals with diabetes and those with missing data were excluded. Ultimately, 6687 adults were included in the final analysis, where we implemented three different ML algorithms, including logistic regression (LR), random forest (RF) and extreme gradient boosting (XGBoost) in order to predict diabetes. …”
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Geospatial distribution and predictors of postnatal care utilization during the critical time in Ethiopia using EDHS 2019: A spatial and geographical weighted regression analysis. by Muluken Chanie Agimas, Tigabu Kidie Tesfie, Nebiyu Mekonnen Derseh, Meron Asmamaw, Habtamu Wagnew Abuhay, Getaneh Awoke Yismaw

“…The data for this analysis was taken from the 2019 EDHS, and missing data was managed by imputation. The spatial variation of postnatal care during the critical time was assessed using the Getis-Ord Gi* statistic; Moran's I statistics were conducted to test the autocorrelation; and Sat Scan statistics were also used to show the statistically significant clusters of early PNC utilization in Ethiopia. …”
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Prevalence and risk factors associated with prehypertension in Shunde District, southern China by Yuli Huang, Yunzhao Hu, Xiaoyan Cai, Wenke Qiu, Changhua Liu, Dingji Zhu, Jinghai Hua, Yanxian Wu, Dingli Xu

“…Prehypertension was further divided into low-range (BP 120–129/80–84 mm Hg) and high-range (BP 130–139/85–89 mm Hg) subgroups.Outcome measures The prevalence of prehypertension and the combined cardiovascular risk factors within the prehypertensive subgroups.Results Of the 5362 initially reviewed cases (aged ≥35 years), 651 were excluded because of missing data. The proportions of optimal BP, prehypertension and hypertension were 39.1%, 38.6% and 22.3%, respectively. …”
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Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients by Aref Andishgar, Sina Bazmi, Kamran B. Lankarani, Seyed Alireza Taghavi, Mohammad Hadi Imanieh, Gholamreza Sivandzadeh, Samira Saeian, Nazanin Dadashpour, Alireza Shamsaeefar, Mahdi Ravankhah, Hamed Nikoupour Deylami, Reza Tabrizi, Mohammad Hossein Imanieh

“…BC was diagnosed with ultrasounds and MRCP. Missing data was imputed using mean and median. Data preprocessing involved feature scaling and one-hot encoding. …”
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Development and external validation of the SMA2SH2ERS risk prediction model for aneurysmal subarachnoid haemorrhage in the general population: a population-based prospective cohort... by Kristiina Rannikmäe, Vita M. Klieverik, Jos P. Kanning, Ina L. Rissanen, Amy E. Martinsen, Bendik S. Winsvold, Mirjam I. Geerlings, Ynte M. Ruigrok

“…We aimed to develop and validate a risk prediction model for ASAH in the general population to identify high-risk individuals.Design We used the population-based prospective cohort studies of the United Kingdom (UK) Biobank for model development and the Trøndelag Health (HUNT) Study for model validation.Participants Participants missing data were excluded. A total of 456 856 individuals from the UK Biobank and 46 483 individuals from the HUNT Study were included.Primary and secondary outcome measures Incident ASAH identified using the International Classification of Diseases codes, ICD-9 430 and ICD-10 I600 to I609 codes.Results In the development cohort, ASAH occurred in 738 (0.2%) during 5 407 909 person-years of follow-up. …”
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Pooled prevalence and associated factors of traditional uvulectom among children in Africa: A systematic review and meta-analysis. by Solomon Demis Kebede, Kindu Agmas, Demewoz Kefale, Amare Kassaw, Tigabu Munye Aytenew

“…Heterogeneity among the included studies was assessed using a forest plot, I2 statistics, and Egger's test, ensuring the robustness and reliability of the findings. Missing data was handled by random effect model and sensitivity analysis. …”
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The Impact of Parental Support on Adherence to Therapist-Assisted Internet-Delivered Acceptance and Commitment Therapy in Primary Care for Adolescents With Anxiety: Naturalistic 12... by Anna Larsson, Sandra Weineland, Linnea Nissling, Josefine L Lilja

“…Nevertheless, due to a small and gender-biased sample size with a large proportion of dropouts and missing data, a nonrandomized assignment of intervention, and an analysis limited to within group, this study should be considered an explorative evaluation rather than an outcome study.…”
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The proper application of logistic regression model in complex survey data: a systematic review by Devjit Dey, Md. Samio Haque, Md. Mojahedul Islam, Umme Iffat Aishi, Sajida Sultana Shammy, Md. Sabbir Ahmed Mayen, Syed Toukir Ahmed Noor, Md. Jamal Uddin

“…Conclusions This systematic review highlights important gaps in the use of logistic regression with complex survey data, such as overlooking data dependencies, survey design, and proper validation techniques, along with neglecting outliers, missing data, and goodness-of-fit assessments, all of which point to the need for clearer methodological standards and more thorough reporting to improve the reliability of results. …”
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Imputation of missing land carbon sequestration data in the AR6 Scenarios Database by R. Prütz, R. Prütz, R. Prütz, R. Prütz, S. Fuss, S. Fuss, S. Fuss, J. Rogelj, J. Rogelj, J. Rogelj

“…We test and compare the performance of different regression models to impute missing data on land carbon sequestration for the global level and for several sub-global macro-regions from available data on net CO<span class="inline-formula">₂</span> emissions from agriculture, forestry, and other land uses. …”
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Measuring serious violence perpetration: comparison of police-recorded and self-reported data in a UK cohort by Rosie Cornish, Alison Teyhan, Kate Tilling, John Macleod, Iain Brennan

“…Multiple imputation using chained equations was used to impute self-reported violence data to examine the likely impact of missing data on estimates of prevalence. Results Self-reported violence perpetration in the past year ranged from 5.3% (at 25 years) to 12.9% (at 20 years) among males and 3.2% (at 17, 22, 24 and 25 years) to 6.4% (at 18 years) among females. …”
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Association of systemic immune-inflammation index (SII) with risk of psoriasis: a cross-sectional analysis of National Health and Nutrition Examination Survey 2011–2014 by Xuan Yang, Yuxin Pan, Yang Zhang, Yang Meng, Tang Tong, Mingyi Zhao

“…Multiple imputation was adopted as sensitivity analysis to address potential bias due to missing data. Results 9314 participants (≥ 20 years) were included. …”
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Thirty-six-year trends (1986–2022) in cigarette smoking and snus use in northern Sweden: a cross-sectional study by Stefan Söderberg, Maria Wennberg, Viktor Oskarsson, Jonas Andersson, Erica Sjödin, Maria Nordendahl, Lena Heldorsson Fjellström, Carolina Lundholm

“…A total of 191 participants were excluded due to missing data on either cigarette smoking or snus use.Results Cigarette smoking decreased on a survey-to-survey basis, reaching a minimum in 2022 of 4.9% among men and 9.7% among women, corresponding to a percentage point change of 26.3 and 20.8, respectively, compared with 1986 (pwithin-group&lt;0.01). …”
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Association between cardiovascular health and osteoporotic fractures: a national population-based study by Jun Ou, Tingting Wang, Ridan Lei, Mengting Sun, Xiaorui Ruan, Jianhui Wei, Jiabi Qin

“…A total of 17,606 adults aged 20 and above were included in the analysis after excluding participants with missing data on CVH or osteoporotic fractures. CVH was assessed using the LE8 score, which incorporates eight modifiable cardiovascular health metrics: diet, physical activity, tobacco use, sleep, body mass index (BMI), lipid levels, blood glucose, and blood pressure. …”
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