@misc{ahrq2017,
  author       = {{Healthcare Cost and Utilization Project (HCUP)}},
  title        = {Elixhauser Comorbidity Software for ICD-9-CM},
  year         = {2017},
  howpublished = {\url{https://hcup-us.ahrq.gov/toolssoftware/comorbidity/comorbidity.jsp}},
  note         = {Agency for Healthcare Research and Quality, Rockville, MD. Accessed: 2025-05-10}
}

@Manual{dewitt2026pccc,
  title = {pccc: Pediatric Complex Chronic Conditions},
  author = {Peter DeWitt and James Feinstein and Seth Russell},
  year = {2026},
  note = {R package version 1.0.7},
  url = {https://github.com/CUD2V/pccc},
}

@article{charlson1987,
  title = {A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation},
  journal = {Journal of Chronic Diseases},
  volume = {40},
  number = {5},
  pages = {373-383},
  year = {1987},
  issn = {0021-9681},
  doi = {https://doi.org/10.1016/0021-9681(87)90171-8},
  url = {https://www.sciencedirect.com/science/article/pii/0021968187901718},
  author = {Mary E. Charlson and Peter Pompei and Kathy L. Ales and C.Ronald MacKenzie},
  abstract = {The objective of this study was to develop a prospectively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies. A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients. The 1-yr mortality rates for the different scores were: “0”, 12% (181); “1–2”, 26% (225); “3–4”, 52% (71); and “⩾ 5”, 85% (82). The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up. The percent of patients who died of comorbid disease for the different scores were: “0”, 8% (588); “1”, 25% (54); “2”, 48% (25); “ ⩾ 3”, 59% (18). With each increased level of the comorbidity index, there were stepwise increases in the cumulative mortality attributable to comorbid disease (log rank χ2 = 165; p < 0.0001). In this longer follow-up, age was also a predictor of mortality (p < 0.001). The new index performed similarly to a previous system devised by Kaplan and Feinstein. The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies. Further work in larger populations is still required to refine the approach because the number of patients with any given condition in this study was relatively small.}
}

@article{deyo1992adapting,
  title={Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases},
  author={Deyo, Richard A and Cherkin, Daniel C and Ciol, Marcia A},
  journal={Journal of clinical epidemiology},
  volume={45},
  number={6},
  pages={613--619},
  year={1992},
  publisher={Elsevier},
  doi={https://doi.org/10.1016/0895-4356(92)90133-8}
}

@article{elixhauser1998,
  title={Comorbidity measures for use with administrative data},
  author={Elixhauser, Anne and Steiner, Claudia and Harris, D Robert and Coffey, Rosanna M},
  journal={Medical care},
  volume={36},
  number={1},
  pages={8--27},
  year={1998},
  publisher={LWW},
  doi={10.1097/00005650-199801000-00004}
}

@misc{ahrqicd10,
  author       = {Agency for Healthcare Research and Quality (AHRQ)},
  title        = {Elixhauser Comorbidity Software Refined for ICD-10-CM Healthcare Cost and Utilization Project (HCUP)},
  month        = {Nov},
  year         = {2025},
  url          = {https://hcup-us.ahrq.gov/toolssoftware/comorbidityicd10/comorbidity_icd10.jsp}
}

@article{feinstein2018pccc,
    author = {Feinstein, James A. and Russell, Seth and DeWitt, Peter E. and Feudtner, Chris and Dai, Dingwei and Bennett, Tellen D.},
    title = {R Package for Pediatric Complex Chronic Condition Classification},
    journal = {JAMA Pediatrics},
    volume = {172},
    number = {6},
    pages = {596-598},
    year = {2018},
    month = {06},
    abstract = {Identification of children with complex chronic conditions (CCCs) is necessary to improve health care delivery and perform clinical research, because this patient population uses significant inpatient and outpatient medical resources. The original CCC classification was published in 2000. A second version was published in 2014 to reflect additions to the International Classification of Diseases system and the US adoption of the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision. The CCC classification is widely used in research (currently cited in more than 100 peer-reviewed journal publications). However, the current approach to assigning the CCC categories in health care–related data sets is limited by proprietary software and computational inefficiency. SAS and Stata software to assign CCC categories were published as appendices to the 2014 update, but not all investigators have access to these statistical packages. In addition, increasingly large data sets are available to investigators. Although the data processing capability of individual computers continues to improve, the SAS and Stata software can take significant time to run on data sets with millions of observations. The objective of this project was to develop computationally efficient software to generate the CCC categories using R, a free, open-source statistical environment. We then compared the SAS, Stata, and R software with respect to accuracy and speed of classification on a typical desktop system.},
    issn = {2168-6203},
    doi = {10.1001/jamapediatrics.2018.0256},
    url = {https://doi.org/10.1001/jamapediatrics.2018.0256},
    eprint = {https://jamanetwork.com/journals/jamapediatrics/articlepdf/2677901/jamapediatrics\_feinstein\_2018\_ld\_180003.pdf},
}

@article{feinstein2024pediatric,
  title={Pediatric complex chronic condition system version 3},
  author={Feinstein, James A and Hall, Matt and Davidson, Amber and Feudtner, Chris},
  journal={JAMA Network Open},
  volume={7},
  number={7},
  pages={e2420579--e2420579},
  year={2024},
  publisher={American Medical Association},
  url = {https://doi.org/10.1001/jamanetworkopen.2024.20579}
}

@article{feudtner2014pediatric,
  title={Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation},
  author={Feudtner, Chris and Feinstein, James A and Zhong, Wenjun and Hall, Matt and Dai, Dingwei},
  journal={BMC pediatrics},
  volume={14},
  pages={1--7},
  year={2014},
  publisher={Springer},
  url = {https://doi.org/10.1186/1471-2431-14-199}
}

@article{glasheen2019,
  title={Charlson comorbidity index: ICD-9 update and ICD-10 translation},
  author={Glasheen, William P and Cordier, Tristan and Gumpina, Rajiv and Haugh, Gil and Davis, Jared and Renda, Andrew},
  journal={American health \& drug benefits},
  volume={12},
  number={4},
  pages={188},
  year={2019},
  url = {https://pubmed.ncbi.nlm.nih.gov/31428236/}
}

@article{martin2022characteristics,
    author = {Martin, Blake and DeWitt, Peter E. and Russell, Seth and Anand, Adit and Bradwell, Katie R. and Bremer, Carolyn and Gabriel, Davera and Girvin, Andrew T. and Hajagos, Janos G. and McMurry, Julie A. and Neumann, Andrew J. and Pfaff, Emily R. and Walden, Anita and Wooldridge, Jacob T. and Yoo, Yun Jae and Saltz, Joel and Gersing, Ken R. and Chute, Christopher G. and Haendel, Melissa A. and Moffitt, Richard and Bennett, Tellen D.},
    title = {Characteristics, Outcomes, and Severity Risk Factors Associated With SARS-CoV-2 Infection Among Children in the US National COVID Cohort Collaborative},
    journal = {JAMA Network Open},
    volume = {5},
    number = {2},
    pages = {e2143151-e2143151},
    year = {2022},
    month = {02},
    abstract = {Understanding of SARS-CoV-2 infection in US children has been limited by the lack of large, multicenter studies with granular data.To examine the characteristics, changes over time, outcomes, and severity risk factors of children with SARS-CoV-2 within the National COVID Cohort Collaborative (N3C).A prospective cohort study of encounters with end dates before September 24, 2021, was conducted at 56 N3C facilities throughout the US. Participants included children younger than 19 years at initial SARS-CoV-2 testing.Case incidence and severity over time, demographic and comorbidity severity risk factors, vital sign and laboratory trajectories, clinical outcomes, and acute COVID-19 vs multisystem inflammatory syndrome in children (MIS-C), and Delta vs pre-Delta variant differences for children with SARS-CoV-2.A total of 1 068 410 children were tested for SARS-CoV-2 and 167 262 test results (15.6\%) were positive (82 882 [49.6\%] girls; median age, 11.9 [IQR, 6.0-16.1] years). Among the 10 245 children (6.1\%) who were hospitalized, 1423 (13.9\%) met the criteria for severe disease: mechanical ventilation (796 [7.8\%]), vasopressor-inotropic support (868 [8.5\%]), extracorporeal membrane oxygenation (42 [0.4\%]), or death (131 [1.3\%]). Male sex (odds ratio [OR], 1.37; 95\% CI, 1.21-1.56), Black/African American race (OR, 1.25; 95\% CI, 1.06-1.47), obesity (OR, 1.19; 95\% CI, 1.01-1.41), and several pediatric complex chronic condition (PCCC) subcategories were associated with higher severity disease. Vital signs and many laboratory test values from the day of admission were predictive of peak disease severity. Variables associated with increased odds for MIS-C vs acute COVID-19 included male sex (OR, 1.59; 95\% CI, 1.33-1.90), Black/African American race (OR, 1.44; 95\% CI, 1.17-1.77), younger than 12 years (OR, 1.81; 95\% CI, 1.51-2.18), obesity (OR, 1.76; 95\% CI, 1.40-2.22), and not having a pediatric complex chronic condition (OR, 0.72; 95\% CI, 0.65-0.80). The children with MIS-C had a more inflammatory laboratory profile and severe clinical phenotype, with higher rates of invasive ventilation (117 of 707 [16.5\%] vs 514 of 8241 [6.2\%]; P \&lt; .001) and need for vasoactive-inotropic support (191 of 707 [27.0\%] vs 426 of 8241 [5.2\%]; P \&lt; .001) compared with those who had acute COVID-19. Comparing children during the Delta vs pre-Delta eras, there was no significant change in hospitalization rate (1738 [6.0\%] vs 8507 [6.2\%]; P = .18) and lower odds for severe disease (179 [10.3\%] vs 1242 [14.6\%]) (decreased by a factor of 0.67; 95\% CI, 0.57-0.79; P \&lt; .001).In this cohort study of US children with SARS-CoV-2, there were observed differences in demographic characteristics, preexisting comorbidities, and initial vital sign and laboratory values between severity subgroups. Taken together, these results suggest that early identification of children likely to progress to severe disease could be achieved using readily available data elements from the day of admission. Further work is needed to translate this knowledge into improved outcomes.},
    issn = {2574-3805},
    doi = {10.1001/jamanetworkopen.2021.43151},
    url = {https://doi.org/10.1001/jamanetworkopen.2021.43151},
    eprint = {https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2788844/martin\_2022\_oi\_211200\_1643735145.21695.pdf},
}

@article{martin2024recent,
  author       = {Martin, Blake and DeWitt, Peter E. and Russell, Seth and Haendel, Melissa and Sanchez-Pinto, Nelson and Albers, David J. and Jhaveri, Ravi R. and Moffitt, Richard and Bennett, Tellen D. and on behalf of the N3C Consortium},
  title        = {The Recent Increase in Invasive Bacterial Infections: A Report From the National COVID Cohort Collaborative},
  journal      = {The Pediatric Infectious Disease Journal},
  year         = {2024},
  keywords     = {invasive bacterial infection, COVID-19, post-viral},
  url          = {https://journals.lww.com/pidj/fulltext/9900/the_recent_increase_in_invasive_bacterial.1049.aspx},
  issn         = {0891-3668},
  abstract     = {Background: When coronavirus disease 2019 (COVID-19) mitigation efforts waned, viral respiratory infections (VRIs) surged, potentially increasing the risk of postviral invasive bacterial infections (IBIs). We sought to evaluate the change in epidemiology and relationships between specific VRIs and IBIs [complicated pneumonia, complicated sinusitis and invasive group A streptococcus (iGAS)] over time using the National COVID Cohort Collaborative (N3C) dataset.
    Methods: We performed a secondary analysis of all prospectively collected pediatric (<19 years old) and adult encounters at 58 N3C institutions, stratified by era: pre-pandemic (January 1, 2018, to February 28, 2020) versus pandemic (March 1, 2020, to June 1, 2023). We compared the characteristics and outcomes of patients with prespecified VRIs and IBIs, including correlation between VRI cases and subsequent IBI cases.
      Results: We identified 965,777 pediatric and 9,336,737 adult hospitalizations. Compared with pre-pandemic, pandemic-era children demonstrated higher mean monthly cases of adenovirus (121 vs. 79.1), iGAS (5.8 vs. 3.3), complicated pneumonia (282 vs. 178) and complicated sinusitis (29.8 vs. 16.3), P < 0.005 for all. Among pandemic-era children, peak correlation between RSV cases and subsequent complicated sinusitis cases occurred with a 60-day lag (correlation coefficient 0.56, 95% confidence interval: 0.52–0.59, P < 0.001) while peak correlation between influenza and complicated sinusitis occurred with a 33-day lag (0.55, 0.51–0.58, P < 0.001). Correlation among other VRI–IBI pairs was modest during the pandemic and often lower than during the pre-pandemic era.
      Conclusions: Since COVID-19 emerged, mean monthly cases of iGAS, complicated pneumonia, and complicated sinusitis have been higher. Pandemic-era RSV and influenza cases were correlated with subsequent cases of complicated sinusitis in children. However, many other VRI–IBI correlations decreased during the pandemic.}
}

@article{quan2005,
  author       = {Quan, Hude and Sundararajan, Vijaya and Halfon, Patricia and Fong, Andrew and Burnand, Bernard and Luthi, Jean-Christophe and Saunders, L Duncan and Beck, Catherine A. and Feasby, Thomas E. and Ghali, William A.},
  title        = {Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data},
  journal      = {Medical Care},
  year         = {2005},
  volume       = {43},
  number       = {11},
  pages        = {1130--1139},
  month        = {November},
  doi          = {10.1097/01.mlr.0000182534.19832.83},
  pmid         = {16224307}
}

@article{quan2011,
  author       = {Quan, Hude and Li, Bo and Couris, Colette M. and Fushimi, Kiyohide and Graham, Peter and Hider, Philip and Januel, Jean-Michel and Sundararajan, Vijaya},
  title        = {Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries},
  journal      = {American Journal of Epidemiology},
  year         = {2011},
  volume       = {173},
  number       = {6},
  pages        = {676--682},
  month        = {March 15},
  doi          = {10.1093/aje/kwq433},
  pmid         = {21330339},
  note         = {Epub 2011 Feb 17}
}

@article{sanchezpinto2024development,
    author = {Sanchez-Pinto, L. Nelson and Bennett, Tellen D. and DeWitt, Peter E. and Russell, Seth and Rebull, Margaret N. and Martin, Blake and Akech, Samuel and Albers, David J. and Alpern, Elizabeth R. and Balamuth, Fran and Bembea, Melania and Chisti, Mohammod Jobayer and Evans, Idris and Horvat, Christopher M. and Jaramillo-Bustamante, Juan Camilo and Kissoon, Niranjan and Menon, Kusum and Scott, Halden F. and Weiss, Scott L. and Wiens, Matthew O. and Zimmerman, Jerry J. and Argent, Andrew C. and Sorce, Lauren R. and Schlapbach, Luregn J. and Watson, R. Scott and Society of Critical Care Medicine Pediatric Sepsis Definition Task Force},
    title = {Development and Validation of the Phoenix Criteria for Pediatric Sepsis and Septic Shock},
    journal = {JAMA},
    volume = {331},
    number = {8},
    pages = {675-686},
    year = {2024},
    month = {02},
    abstract = {The Society of Critical Care Medicine Pediatric Sepsis Definition Task Force sought to develop and validate new clinical criteria for pediatric sepsis and septic shock using measures of organ dysfunction through a data-driven approach.To derive and validate novel criteria for pediatric sepsis and septic shock across differently resourced settings.Multicenter, international, retrospective cohort study in 10 health systems in the US, Colombia, Bangladesh, China, and Kenya, 3 of which were used as external validation sites. Data were collected from emergency and inpatient encounters for children (aged \&lt;18 years) from 2010 to 2019: 3 049 699 in the development (including derivation and internal validation) set and 581 317 in the external validation set.Stacked regression models to predict mortality in children with suspected infection were derived and validated using the best-performing organ dysfunction subscores from 8 existing scores. The final model was then translated into an integer-based score used to establish binary criteria for sepsis and septic shock.The primary outcome for all analyses was in-hospital mortality. Model- and integer-based score performance measures included the area under the precision recall curve (AUPRC; primary) and area under the receiver operating characteristic curve (AUROC; secondary). For binary criteria, primary performance measures were positive predictive value and sensitivity.Among the 172 984 children with suspected infection in the first 24 hours (development set; 1.2\% mortality), a 4-organ-system model performed best. The integer version of that model, the Phoenix Sepsis Score, had AUPRCs of 0.23 to 0.38 (95\% CI range, 0.20-0.39) and AUROCs of 0.71 to 0.92 (95\% CI range, 0.70-0.92) to predict mortality in the validation sets. Using a Phoenix Sepsis Score of 2 points or higher in children with suspected infection as criteria for sepsis and sepsis plus 1 or more cardiovascular point as criteria for septic shock resulted in a higher positive predictive value and higher or similar sensitivity compared with the 2005 International Pediatric Sepsis Consensus Conference (IPSCC) criteria across differently resourced settings.The novel Phoenix sepsis criteria, which were derived and validated using data from higher- and lower-resource settings, had improved performance for the diagnosis of pediatric sepsis and septic shock compared with the existing IPSCC criteria.},
    issn = {0098-7484},
    doi = {10.1001/jama.2024.0196},
    url = {https://doi.org/10.1001/jama.2024.0196},
    eprint = {https://jamanetwork.com/journals/jama/articlepdf/2814296/jama\_sanchezpinto\_2024\_oi\_240003\_1709591810.56162.pdf},
}

@article{schlapbach2024international,
    author = {Schlapbach, Luregn J. and Watson, R. Scott and Sorce, Lauren R. and Argent, Andrew C. and Menon, Kusum and Hall, Mark W. and Akech, Samuel and Albers, David J. and Alpern, Elizabeth R. and Balamuth, Fran and Bembea, Melania and Biban, Paolo and Carrol, Enitan D. and Chiotos, Kathleen and Chisti, Mohammod Jobayer and DeWitt, Peter E. and Evans, Idris and Flauzino de Oliveira, Cláudio  and Horvat, Christopher M. and Inwald, David and Ishimine, Paul and Jaramillo-Bustamante, Juan Camilo and Levin, Michael and Lodha, Rakesh and Martin, Blake and Nadel, Simon and Nakagawa, Satoshi and Peters, Mark J. and Randolph, Adrienne G. and Ranjit, Suchitra and Rebull, Margaret N. and Russell, Seth and Scott, Halden F. and de Souza, Daniela Carla and Tissieres, Pierre and Weiss, Scott L. and Wiens, Matthew O. and Wynn, James L. and Kissoon, Niranjan and Zimmerman, Jerry J. and Sanchez-Pinto, L. Nelson and Bennett, Tellen D. and Society of Critical Care Medicine Pediatric Sepsis Definition Task Force},
    title = {International Consensus Criteria for Pediatric Sepsis and Septic Shock},
    journal = {JAMA},
    volume = {331},
    number = {8},
    pages = {665-674},
    year = {2024},
    month = {02},
    abstract = {Sepsis is a leading cause of death among children worldwide. Current pediatric-specific criteria for sepsis were published in 2005 based on expert opinion. In 2016, the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) defined sepsis as life-threatening organ dysfunction caused by a dysregulated host response to infection, but it excluded children.To update and evaluate criteria for sepsis and septic shock in children.The Society of Critical Care Medicine (SCCM) convened a task force of 35 pediatric experts in critical care, emergency medicine, infectious diseases, general pediatrics, nursing, public health, and neonatology from 6 continents. Using evidence from an international survey, systematic review and meta-analysis, and a new organ dysfunction score developed based on more than 3 million electronic health record encounters from 10 sites on 4 continents, a modified Delphi consensus process was employed to develop criteria.Based on survey data, most pediatric clinicians used sepsis to refer to infection with life-threatening organ dysfunction, which differed from prior pediatric sepsis criteria that used systemic inflammatory response syndrome (SIRS) criteria, which have poor predictive properties, and included the redundant term, severe sepsis. The SCCM task force recommends that sepsis in children be identified by a Phoenix Sepsis Score of at least 2 points in children with suspected infection, which indicates potentially life-threatening dysfunction of the respiratory, cardiovascular, coagulation, and/or neurological systems. Children with a Phoenix Sepsis Score of at least 2 points had in-hospital mortality of 7.1\% in higher-resource settings and 28.5\% in lower-resource settings, more than 8 times that of children with suspected infection not meeting these criteria. Mortality was higher in children who had organ dysfunction in at least 1 of 4—respiratory, cardiovascular, coagulation, and/or neurological—organ systems that was not the primary site of infection. Septic shock was defined as children with sepsis who had cardiovascular dysfunction, indicated by at least 1 cardiovascular point in the Phoenix Sepsis Score, which included severe hypotension for age, blood lactate exceeding 5 mmol/L, or need for vasoactive medication. Children with septic shock had an in-hospital mortality rate of 10.8\% and 33.5\% in higher- and lower-resource settings, respectively.The Phoenix sepsis criteria for sepsis and septic shock in children were derived and validated by the international SCCM Pediatric Sepsis Definition Task Force using a large international database and survey, systematic review and meta-analysis, and modified Delphi consensus approach. A Phoenix Sepsis Score of at least 2 identified potentially life-threatening organ dysfunction in children younger than 18 years with infection, and its use has the potential to improve clinical care, epidemiological assessment, and research in pediatric sepsis and septic shock around the world.},
    issn = {0098-7484},
    doi = {10.1001/jama.2024.0179},
    url = {https://doi.org/10.1001/jama.2024.0179},
    eprint = {https://jamanetwork.com/journals/jama/articlepdf/2814297/jama\_schlapbach\_2024\_oi\_240002\_1711118634.86488.pdf},
}

@article{r-comorbidity,
  author = {Alessandro Gasparini},
  title = {comorbidity: An R package for computing comorbidity scores},
  journal = {Journal of Open Source Software},
  year = {2018},
  volume = {3},
  issue = {23},
  pages = {648},
  doi = {10.21105/joss.00648},
  url = {https://doi.org/10.21105/joss.00648},
}

@manual{r-icdcomorbid,
  title = {icdcomorbid: Mapping ICD Codes to Comorbidity},
  author = {April Nguyen and Seungwon Lee},
  year = {2024},
  note = {R package version 1.0.0},
  url = {https://CRAN.R-project.org/package=icdcomorbid},
  doi = {10.32614/CRAN.package.icdcomorbid},
}

@manual{r-multimorbidity,
  title = {multimorbidity: Harmonizing Various Comorbidity, Multimorbidity, and Frailty Measures},
  author = {Wyatt Bensken},
  year = {2023},
  note = {R package version 0.5.1},
  url = {https://CRAN.R-project.org/package=multimorbidity},
  doi = {10.32614/CRAN.package.multimorbidity},
}

@article{johnson2018mimic,
  title={The MIMIC Code Repository: enabling reproducibility in critical care research},
  author={Johnson, Alistair E W and Stone, David J and Celi, Leo A and Pollard, Tom J},
  journal={Journal of the American Medical Informatics Association},
  volume={25},
  number={1},
  pages={32--39},
  year={2018},
  publisher={Oxford University Press}
}
