The DOI matches its Crossref record; 26 of the 28 references it cites were found in a registry or an index.
A readers' guide to the interpretation of diagnostic test properties: clinical example of sepsis
Open accessAbstract
Background One of the most challenging practical and daily problems in intensive care medicine is the interpretation of the results from diagnostic tests. In neonatology and pediatric intensive care the early diagnosis of potentially life-threatening infections is a particularly important issue.Focus A plethora of tests have been suggested to improve diagnostic decision making in the clinical setting of infection which is a clinical example used in this article. Several criteria that are critical to evidence-based appraisal of published data are often not adhered to during the study or in reporting. To enhance the critical appraisal on articles on diagnostic tests we discuss various measures of test accuracy: sensitivity, specificity, receiver operating characteristic curves, positive and negative predictive values, likelihood ratios, pretest probability, posttest probability, and diagnostic odds ratio.Conclusions We suggest the following minimal requirements for reporting on the diagnostic accuracy of tests: a plot of the raw data, multilevel likelihood ratios, the area under the receiver operating characteristic curve, and the cutoff yielding the highest discriminative ability. For critical appraisal it is mandatory to report confidence intervals for each of these measures. Moreover, to allow comparison to the readers' patient population authors should provide data on study population characteristics, in particular on the spectrum of diseases and illness severity.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The AUC values ranged from .63 to .76 and were considered in acceptable range (Akobeng, 2007; Fischer et al., 2003).”
From Exercise habit formation in new gym members: a longitudinal study (2015) · cites this paper as Fischer et al., 2003
Citations
Cites
Measuring the Accuracy of Diagnostic Systems
Swets, J. A. (1988) · Science · doi:10.1126/science.3287615 · Cited by 10,058
Hanley, J. A., & McNeil, B. J. (1983) · Radiology · doi:10.1148/radiology.148.3.6878708 · Cited by 7,016
Users' Guides to the Medical Literature
Guyatt, G. H. (1993) · JAMA · doi:10.1001/jama.270.17.2096 · Cited by 3,083
Users' Guides to the Medical Literature
Jaeschke, R. (1994) · JAMA · doi:10.1001/jama.271.9.703 · Cited by 2,688
Self-citationEmpirical evidence of design-related bias in studies of diagnostic tests.
Lijmer, J. G. (1999) · JAMA · doi:10.1001/jama.282.11.1061 · Cited by 1,861
Mumber, M. P. (2005) · CRC Press eBooks · doi:10.1201/9780203088319-19 · Cited by 1,584
Fischhoff, B. (1980) · Operations Research · doi:10.1287/opre.28.1.28 · Cited by 1,423
The Threshold Approach to Clinical Decision Making
Pauker, S. G., & Kassirer, J. P. (1980) · New England Journal of Medicine · doi:10.1056/nejm198005153022003 · Cited by 1,371
Users' Guides to the Medical Literature
Jaeschke, R. (1994) · JAMA · doi:10.1001/jama.271.5.389 · Cited by 1,174
Self-citation(1975) · New England Journal of Medicine · doi:10.1056/nejm197507312930513 · Cited by 1,017
Cited by
Sorted by citations
Items 601–700 of 890
Clinical Trials and Accuracy of Diagnostic Tests
Lee, Y. K., & Lee, S. M. (2011) · Journal of genetic medicine · doi:10.5734/jgm.2011.8.1.28 · Cited by 5
Diagnostic value of circulating microRNAs for liver cirrhosis: a meta-analysis
Guo, L., Li, W., Hu, L., Zhou, H., Zheng, L., Yu, L., & Liang, W. (2017) · Oncotarget · doi:10.18632/oncotarget.23332 · Cited by 5
Clinical performance of seven prescreening tools for osteoporosis in Iranian postmenopausal women
Keshtkar, A., Tabatabaie, O., Matin, N., Mohammadi, Z., Ebrahimi, M., Khashayar, P., & Asadi, M. (2015) · Rheumatology International · doi:10.1007/s00296-015-3286-1 · Cited by 5
Digitized spiral analysis may be a potential biomarker for brachial dystonia
Ratliff, J. B., Ortega, R. A., Ooi, H. Y., Mirallave, A., Glickman, A., Yu, Q. P., Raymond, D., Bressman, S., Pullman, S. L., & Saunders-Pullman, R. J. (2018) · Parkinsonism & Related Disorders · doi:10.1016/j.parkreldis.2018.07.004 · Cited by 5
Performance and educational training of radiographers in lung nodule or mass detection
Teng, P.-H., Liang, C.-H., Lin, Y., Alberich‐Bayarri, Á., González, R. L., Li, P.-W., Weng, Y.-H., Chen, Y., Lin, C.-H., Chou, K.-J., et al. (2021) · Medicine · doi:10.1097/md.0000000000026270 · Cited by 5
Kumar, V. V., Chatterjee, B., & Tankha, G. (2021) · Sustainability · doi:10.3390/su13179828 · Cited by 5
Tangpaitoon, T., & Swatesutipun, V. (2022) · International Urology and Nephrology · doi:10.1007/s11255-022-03399-8 · Cited by 5
Andersen, K., Nielsen, B., Hesse, M., Mejldal, A., Bilberg, R., & Nielsen, A. S. (2023) · Nordic Journal of Psychiatry · doi:10.1080/08039488.2023.2200764 · Cited by 8
Nakaizumi, D., MIYATA, S., Uchiyama, K., & TAKAHASHI, I. (2024) · Physical Therapy Research · doi:10.1298/ptr.e10267 · Cited by 5
Cimenti, C., Erwa, W., Müller, W. D., & Resch, B. (2013) · InTech eBooks · doi:10.5772/54531 · Cited by 5
Agreement Between Chart Diagnoses and Standardized Instrument Ratings of Youth Psychopathology
Jensen‐Doss, A., Osterberg, L. D., Hickey, J. S., & Crossley, T. (2012) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-012-0436-6 · Cited by 5
The incidentally found leiomyoma that was in a resected stomach and its follow-up.
Chang, F. Y., Shih, C. Y., Lee, S.-D., & Tsay, S. (1998) · PubMed · Cited by 5
Determining an optimal cut-off point for TikTok addiction using the TikTok Addiction ScalePreprint
Galanis, P., Katsiroumpa, A., Moisoglou, I., & Konstantakopoulou, O. (2024) · Research Square · doi:10.21203/rs.3.rs-4782800/v1 · Cited by 5
Kim, B., Youm, C., Park, H., Choi, H., & Shin, S. (2024) · Frontiers in Public Health · doi:10.3389/fpubh.2024.1376736 · Cited by 4
McLean, K. A., Knight, S. R., Clark, N., Ademuyiwa, A. O., Adisa, A., Aguilera‐Arevalo, M., Ghosh, D., Haque, P. D., Lawani, I., la, M. A. R.-D., et al. (2024) · British journal of surgery · doi:10.1093/bjs/znae129 · Cited by 4
Rhudy, C. N., Perry, C. L., Wesley, M. J., Fardo, D. W., Bumgardner, C., Hassan, S. A., Barrett, T. A., & Talbert, J. (2024) · Crohn s & Colitis 360 · doi:10.1093/crocol/otae039 · Cited by 4
Feighelstein, M., Tomacheuski, R. M., Elias, G., Shashoua, N., van der Linden, D., Luna, S. P. L., & Zamansky, A. (2026) · Scientific Reports · doi:10.1038/s41598-026-39604-2 · Cited by 4
Kim, S. C., Kong, S. Y., Eom, S., Choe, B., & Hong, S. J. (2021) · Annals of Geriatric Medicine and Research · doi:10.4235/agmr.21.0027 · Cited by 4
Borges, L. L., Gerage, A. M., Monteiro, L. Z., Ulbrich, A. Z., & Silva, D. A. S. (2022) · Frontiers in Nutrition · doi:10.3389/fnut.2022.874047 · Cited by 4
Kobayashi, T., Iwasaki, T., Kurata, H., Nikaido, A., & Hata, Y. (2024) · IJC Heart & Vasculature · doi:10.1016/j.ijcha.2024.101442 · Cited by 4
Heffernan, S. M., Conway, G. E., McCarthy, C., Eustace, S. J., Waldron, M., VITO, G. D., & Delahunt, E. (2024) · The Knee · doi:10.1016/j.knee.2024.09.003 · Cited by 4
A Novel Machine Learning Model to Predict Revision ACL Reconstruction Failure in the MARS Cohort
MARS Group, Vasavada, K. D., Vasavada, V., Moran, J. T., Devana, S. K., Lee, C. H., Hame, S. L., Jazrawi, L. M., Sherman, O. H., Huston, L. J., et al. (2024) · Orthopaedic Journal of Sports Medicine · doi:10.1177/23259671241291920 · Cited by 4
Westfall, J. A. (2013) · Canadian Journal of Forest Research · doi:10.1139/cjfr-2013-0330 · Cited by 4
Is the hymen a suitable cut-off point for clinically relevant pelvic organ prolapse?
Wiegersma, M., Panman, C. M. C. R., Kollen, B. J., Berger, M. Y., van Leeuwen, Y., & Dekker, J. H. (2017) · Maturitas · doi:10.1016/j.maturitas.2017.02.012 · Cited by 4
Impact of renal arterial morphology on fluoroscopy time in chimney endovascular aneurysm repair
Sugimoto, M., Torsello, G. B., & Donas, K. P. (2017) · Vascular · doi:10.1177/1708538117700765 · Cited by 4
Gómez‐Gastiasoro, A., Peña, J., Zubiaurre‐Elorza, L., Ibarretxe‐Bilbao, N., & Ojeda, N. (2018) · Psychiatry Research · doi:10.1016/j.psychres.2018.09.051 · Cited by 4
Bruhn, S. M., Ingelsrud, L. H., Bandholm, T., Skou, S. T., Schrøder, H. M., Reventlow, S. D., Møller, A., Kjellberg, J., Kallemose, T., & Troelsen, A. (2021) · BMJ Open · doi:10.1136/bmjopen-2020-048411 · Cited by 4
Piao, J., Yoo, C., Kim, S. Y., Whang, Y.-W., Choi, C. U., & Shin, S. (2021) · Clinical Hemorheology and Microcirculation · doi:10.3233/ch-211185 · Cited by 4
Streiner, D. L., Norman, G. R., & Cairney, J. (2014) · doi:10.1093/med/9780199685219.003.0007 · Cited by 4
Laskawska, M. S., Hébert, H. L., Richardson, C., Berlouis, K., Cameron, P. A., Colvin, L., & Smith, B. H. (2022) · British Journal of Pain · doi:10.1177/20494637221092907 · Cited by 4
Shinohara, T., Saida, K., Tanaka, S., Murayama, A., & Higuchi, D. (2022) · Nippon Ronen Igakkai Zasshi Japanese Journal of Geriatrics · doi:10.3143/geriatrics.59.169 · Cited by 4
The psychometric properties of a caregiving-related strain scale in oncology
Longacre, M. L., Miller, M. F., & Fang, C. Y. (2022) · Quality of Life Research · doi:10.1007/s11136-022-03235-7 · Cited by 4
Tsuji, S., Nobuta, Y., Yoneoka, Y., Nakamura, A., Amano, T., Takebayashi, A., Hanada, T., & Murakami, T. (2023) · Journal of Minimally Invasive Gynecology · doi:10.1016/j.jmig.2023.03.012 · Cited by 4
Ghahremani, L., Nazari, M., Bahadori, F., Yarelahi, M., Abbasi, F., & Karimi, M. (2023) · Gerontology and Geriatric Medicine · doi:10.1177/23337214231185915 · Cited by 4
Sousa, H., Ribeiro, Ó. M., & de Figueiredo, D. M. P. (2024) · Quality of Life Research · doi:10.1007/s11136-024-03627-x · Cited by 5
Murofushi, K., Mitomo, S., Hirohata, K., Furuya, H., Katagiri, H., Kaneoka, K., Hara, S., & Yagishita, K. (2024) · Orthopaedic Journal of Sports Medicine · doi:10.1177/23259671241260517 · Cited by 4
Gómez–Restrepo, C., Peñaranda, A. P. B., Valencia, J. G., Guarín, M. R., Narváez, E. B., Jaramillo, L. E., Acosta, C. A. P., Pedraza, R. S., & Castro, S. (2012) · Revista Colombiana de Psiquiatría · doi:10.1016/s0034-7450(14)60044-5 · Cited by 4
Coherent fluctuation nephelometry as a promising method for diagnosis of bacteriuria
Gur’ev, A. S., Yudina, I. E., Lazareva, A., & Volkov, A. Y. (2018) · Practical Laboratory Medicine · doi:10.1016/j.plabm.2018.e00106 · Cited by 4
Prognostic Value of an Estimate-of-Risk Model in Critically Ill Obstetric Patients in Brazil
Silva, F. X., Parpinelli, M. A., Oliveira-Neto, A. F., do Valle, C. R., Souza, R. T., Costa, M. L., Correia, M. D. T., Katz, L., Payne, B., Ryan, H., et al. (2021) · Obstetrics and Gynecology · doi:10.1097/aog.0000000000004619 · Cited by 4
George, B., Scaria, L. M., Prasanna, G. L., Bhaskaran, D., Leela, L. M., & Remadevi, S. (2022) · The Indian Journal of Pediatrics · doi:10.1007/s12098-021-04021-y · Cited by 4
Kashiwagi, M., Sugimura, T., Matsusue, A., Hara, K., Waters, B., & Kubo, S. (2012) · Legal Medicine · doi:10.1016/j.legalmed.2012.11.001 · Cited by 4
Predicting Improvement of Functioning in Disability Claimants
Nieuwenhuijsen, K., Cornelius, L. R., de Boer, M. R., Groothoff, J. W., Frings‐Dresen, M. H. W., van der Klink, J. J. L., & Brouwer, S. (2013) · Journal of Occupational Rehabilitation · doi:10.1007/s10926-013-9469-2 · Cited by 4
Matsugi, A., Tani, K., Yoshioka, N., Yamashita, A., Mori, N., Oku, K., Murakami, Y., Nomura, S., Tamaru, Y., & Nagano, K. (2016) · Journal of Physical Therapy Science · doi:10.1589/jpts.28.2737 · Cited by 4
Outcome of burn care : the mortality perspective
Pompermaier, L. (2017) · Linköping University medical dissertations · doi:10.3384/diss.diva-142897 · Cited by 4
Hattori, Y., Pai, B. C.-J., Saito, T., Denadai, R., Chou, P., & Lo, L. (2024) · Journal of Cranio-Maxillofacial Surgery · doi:10.1016/j.jcms.2024.04.013 · Cited by 3
Gallagher, D. O., Bondar, K. J., Hirase, T., Harris, J., Vemu, S. M., Louie, P. K., Varthi, A. G., Lambert, B. S., & Saifi, C. (2025) · Journal of Bone and Joint Surgery · doi:10.2106/jbjs.23.01391 · Cited by 3
Yang, C., Shi, X., Zhang, S., Xiong, M., Hu, H., Hao, X., & Sha, W. (2025) · BMC Pulmonary Medicine · doi:10.1186/s12890-025-03947-9 · Cited by 3
Zhang, B., Li, M., Li, H., Zhou, Y., Zhang, H., Kong, X., & Chai, W. (2025) · The Bone & Joint Journal · doi:10.1302/0301-620x.107b11.bjj-2025-0473.r1 · Cited by 3
Popello, V., Zucco, C., Milano, M., & Cannataro, M. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11356777 · Cited by 3
Kosoku, A., Iwai, T., Masuda, H., Kabei, K., Nishide, S., Maeda, K., Yoshikawa, Y., Nakamura, Y., Geest, S. D., & Uchida, J. (2023) · Transplantation Direct · doi:10.1097/txd.0000000000001457 · Cited by 3
Heriyanto, R. S., Yanto, T. A., Octavius, G. S., Nisa, H., Ienawi, C., & Pasai, H. E. (2023) · Journal of Community Empowerment for Health · doi:10.22146/jcoemph.78698 · Cited by 3
A vehicle occupant injury prediction algorithm based on road crash and emergency medical data
NISHIMOTO, T., Kubota, K., & Ponte, G. (2024) · Journal of Safety Research · doi:10.1016/j.jsr.2024.09.015 · Cited by 3
Deep Learning-Based Identification of Echocardiographic Abnormalities From Electrocardiograms
Fujiki, G., Kodera, S., Setoguchi, N., Tanabe, K., Miyaji, K., Kushida, S., Saji, M., Nanasato, M., Maki, H., Fujita, H., et al. (2024) · JACC Asia · doi:10.1016/j.jacasi.2024.10.012 · Cited by 4
Singh, M., & Singh, M. K. (2025) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2025.110581 · Cited by 3
Évaluation statistique d’un biomarqueur
Ray, P., Manach, Y. L., Riou, B., & Houle, T. T. (2011) · Annales françaises de médecine d’urgence · doi:10.1007/s13341-011-0087-3 · Cited by 3
Saito, M., Kurashima, O., & Ito, M. (2016) · Climate Research · doi:10.3354/cr01377 · Cited by 3
Vukomanovic, A., Djurović, A., & Brdareski, Z. (2016) · Vojnosanitetski pregled · doi:10.2298/vsp150819056v · Cited by 3
The Concurrent Criterion Validity of the 32-Item Fitness-to-Drive Screening Measure
Medhizadah, S., Classen, S., & Johnson, A. M. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.00253 · Cited by 3
Pacífico, G. M., Jr., Viamont-Guerra, M.-R., Antonioli, E., Paião, I. D., Saffarini, M., & Guimarães, R. P. (2022) · Hip International · doi:10.1177/11207000211069522 · Cited by 3
DNA Repair Genes Polymorphisms: Impact on Acute Myeloid Leukemia Patients Outcome
Aref, S., Menshawy, N. E., Abouzeid, T., Gouda, E., & Aziz, N. A. (2022) · Asian Pacific Journal of Cancer Prevention · doi:10.31557/apjcp.2022.23.10.3577 · Cited by 3
Salivary Interleukin 1-Beta Concentration Associates With Sleep Quality in Older Individuals
Valle, V. I.-D., Ballestar‐Tarín, M. L., Mafla-España, M. A., Cauli, O., & Navarro-Martínez, R. (2023) · Biological Research For Nursing · doi:10.1177/10998004231181347 · Cited by 3
Salazar‐Frías, D., Rodríguez‐Bailón, M., Ricchetti, G., Navarro-Egido, A., & Funes, M. J. (2023) · The Clinical Neuropsychologist · doi:10.1080/13854046.2023.2278822 · Cited by 3
Konstantinopoulou, E., Vilou, I., Falega, I., Papadopoulou, V., Chatzidimitriou, E., Grigoriadis, N., Aretouli, E., & Ioannidis, P. (2023) · Archives of Clinical Neuropsychology · doi:10.1093/arclin/acad101 · Cited by 3
Coulon, A., Bourmorck, D., Steenebruggen, F., Knoops, L., Brauwer, I. D., & On behalf of the COPE Project (2024) · Palliative Medicine Reports · doi:10.1089/pmr.2024.0010 · Cited by 3
Wang, Y., Wu, Q., Zhu, X. D., Wu, X., & Zhu, P. (2025) · The American Journal of Emergency Medicine · doi:10.1016/j.ajem.2025.03.010 · Cited by 3
ACURÁCIA DE TESTES FUNCIONAIS NA IDENTIFICAÇÃO DA PRÉ-ATIVAÇÃO DE MÚSCULOS LOMBOPÉLVICOS
Jassi, F. J., Antônio, T. D., de Oliveira, R. G., de Oliveira, L. C., Alves, N., de Azevedo, F. M., Chaves, T. C., & Filho, R. D. F. N. (2016) · Revista Brasileira de Medicina do Esporte · doi:10.1590/1517-869220162204156108 · Cited by 3
Yang, C., Ge, J., Zhang, R., Chen, C., Yi, L., & Shen, L. (2020) · The Heart Surgery Forum · doi:10.1532/hsf.2957 · Cited by 3
Wan, Z., Lee, C., Yuan, S., & Lee, O. K.-S. (2020) · Sao Paulo Medical Journal · doi:10.1590/1516-3180.2020.0021.r3.24062020 · Cited by 3
Packness, A., Christensen, K. S., & Simonsen, E. H. (2023) · Nordic Journal of Psychiatry · doi:10.1080/08039488.2023.2174593 · Cited by 4
A fast and accurate diagnostic test for severe sepsis using kernel classifiers
Parente, J. D., Chase, J. G., Shaw, G. M., Lee, D., & Lin, J. (2010) · UKACC International Conference on Control · doi:10.1049/ic.2010.0388 · Cited by 3
Živković, M., Kolaković, A., Radak, D. J., Dinčić, D., Radak, S., Djurić, T., & Stanković, A. (2012) · Molecular Biology Reports · doi:10.1007/s11033-012-1475-5 · Cited by 3
Bertelli, J. A., Gasparelo, K. R., & Seltser, A. (2021) · Journal of neurosurgery · doi:10.3171/2021.6.jns21956 · Cited by 3
Silva, F. X., Parpinelli, M. Â., Neto, A. F. O., do Valle, C. C. R., Souza, R. T., Costa, M. L., Correia, M. D. T., Katz, L., & Cecatti, J. G. (2022) · International Journal of Gynecology & Obstetrics · doi:10.1002/ijgo.14127 · Cited by 3
Online Misinformation Susceptibility Scale: An adapted version for health-related misinformationPreprint
Katsiroumpa, A., Konstantakopoulou, O., Gallos, P., Moisoglou, I., Μangoulia, P., Galani, O., Tsiachri, M., & Galanis, P. (2025) · medRxiv · doi:10.1101/2025.09.11.25335589 · Cited by 3
Yang, X., Wang, N., Xing, H., Wu, D., Zhang, B., Du, H., Gao, C., & Hao, A.-H. (2023) · European Spine Journal · doi:10.1007/s00586-023-07531-9 · Cited by 2
Nanjo, K., IKEDA, T., Kaneyama, R., Okuyama, H., Sakai, T., & Jinno, T. (2025) · Journal of Back and Musculoskeletal Rehabilitation · doi:10.1177/10538127251323980 · Cited by 2
Harmful Animal Detection Using Visual Information for Wire-Type Mobile Robots
Doi, T., Mizuta, A., & Nagumo, K. (2025) · Journal of Robotics and Mechatronics · doi:10.20965/jrm.2025.p0742 · Cited by 2
de Oliveira, R. G., de Oliveira, R. F., Remonte, A. K., Garcia, S. C., Sczepanski, C. R. B., Menossi, B. R. D. S., dos Santos, C. F., Martini, F. A. N., Lirani, L. D. S., & de Oliveira, L. C. (2017) · Manual Therapy Posturology & Rehabilitation Journal · doi:10.17784/mtprehabjournal.2017.15.542 · Cited by 2
Tei, R., Plana‐Ripoll, O., Brink, O., & Langdahl, B. L. (2019) · Calcified Tissue International · doi:10.1007/s00223-019-00535-y · Cited by 2
Production and perception of Korean word-initial stops from a sound change perspective
Jin-Woo, K. (2021) · Phonetics and Speech Sciences · doi:10.13064/ksss.2021.13.3.039 · Cited by 2
Development of the 8-Item Phlegm Pattern Questionnaire (PPQ-8) Using Rasch Analysis
Park, Y.-J. (2021) · Evidence-based Complementary and Alternative Medicine · doi:10.1155/2021/6528891 · Cited by 2
Dube, M. K., Nour, S., Shafee, A., Lahart, I. M., & Carmichael, A. R. (2022) · Annals of The Royal College of Surgeons of England · doi:10.1308/rcsann.2021.0152 · Cited by 2
Park, I. R., Choi, J., Ha, E. Y., Chung, S. M., Moon, J. S., Shin, S., Kim, S. G., & Won, K. C. (2022) · Clinical Hemorheology and Microcirculation · doi:10.3233/ch-211326 · Cited by 2
Camasca, J. B. C., Flores-Vargas, E., & Bernabé‐Ortiz, A. (2022) · Revista Española de Nutrición Humana y Dietética · doi:10.14306/renhyd.26.2.1513 · Cited by 2
Introduction to hip implants and biomarker testing
Swiatkowska, I., Sabah, S. A., Horga, L.-M., & Hart, A. J. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-821596-8.00003-3 · Cited by 2
Nishizawa, T., Hanabusa, S., Kameya, Y., Takahashi, K., Tsuboi, N., & Mizuno, T. (2023) · International Conference on Medical and Health Informatics (ICMHI) · doi:10.1145/3608298.3608311 · Cited by 2
Kim, S., Currao, A., Brown, E. M., Milberg, W., & Fortier, C. B. (2023) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617723000711 · Cited by 2
Takahata, K., Horiuchi, S., Miyauchi, A., Tadokoro, Y., & Shuo, T. (2024) · Japan Journal of Nursing Science · doi:10.1111/jjns.12588 · Cited by 2
The endothelin‐1 system among high‐risk pregnant women with obstructive sleep apnea
Shirk, S., Kozakiewicz, M. L., Sheehan, K. N., Xiang, K. R., Saha, A. K., Stamilio, D. M., Zhang, J., Koch, A. L., & Namen, A. M. (2025) · Journal of Sleep Research · doi:10.1111/jsr.70008 · Cited by 2
The predictive value of suPAR for glomerular segmental sclerosis lesions in renal pathology
Zhang, Z., Liu, C., Han, Y., Li, D., Huang, Y., Shi, K., Xia, S., Wei, J., Liu, H., Sun, L., et al. (2025) · Renal Failure · doi:10.1080/0886022x.2025.2498628 · Cited by 2
Mizan sleep quality and Sleep Hygiene Index MiSQuaSHI: a psychometric investigation.
Manzar, M. D. (2021) · PubMed Central · doi:10.5935/1984-0063.20200052 · Cited by 2
Reliability and Accuracy of Infrared Temperature: A Systematic Review
Park, S.-H. (2014) · Korean Journal of Adult Nursing · doi:10.7475/kjan.2014.26.6.668 · Cited by 2
Can Serum Mannose‐Binding Lectin Levels Aid with the Diagnosis of Invasive Aspergillosis?
Kalil, A. C. (2009) · Clinical Infectious Diseases · doi:10.1086/644620 · Cited by 2
Kane, G. (2013) · Journal of Negative Results in BioMedicine · doi:10.1186/1477-5751-12-16 · Cited by 2
Saito, M. U., Kurashima, O., & Itô, M. (2015) · Plant Ecology & Diversity · doi:10.1080/17550874.2015.1051153 · Cited by 2
Streiner, D. L. (2017) · Journal of Clinical Psychopharmacology · doi:10.1097/jcp.0000000000000753 · Cited by 2
Ogle, Z., Koen, L., & Niehaus, D. J. H. (2018) · African Journal of Primary Health Care & Family Medicine · doi:10.4102/phcfm.v10i1.1722 · Cited by 2
Role of bile acids in the prediction of hepatocellular carcinoma in HCV-induced liver cirrhosis
Khalil, A. A., Elsheashaey, A., Abdelsameea, E., Obada, M., Bayomy, F. F. M., & El‐Said, H. (2021) · Egyptian Liver Journal · doi:10.1186/s43066-021-00142-3 · Cited by 2
Factors Related to Pediatric Readmissions of Four Major Diagnostic Categories in Hawai`i.
Morrison, B., Lim, E., Ahn, H. J., & Chen, J. J. (2022) · PubMed Central · Cited by 2
Khodeir, A. A., El-Shimi, O. S., assem, S. M. K., & Mohammed, M. A. (2022) · Benha Journal of Applied Sciences · doi:10.21608/bjas.2022.221157 · Cited by 2
Metadata
- Authors
- Fischer, J. E., Bachmann, L. M., & Jaeschke, R.
- Affiliations
- University Children's Hospital Zurich (CH)
- McMaster University (CA)
- Corresponding author
- Fischer, Joachim E.
- Venue
- Intensive Care Medicine
- Published
- 2003-07-01
- Volume
- 29
- Issue
- 7
- Pages
- 1043-1051
- ISSN
- 0342-4642 (ISSN-L)
- 1432-1238
- OpenAlex
- W1997033640
- Cited by
- 890
- References
- 28
- Citations by year
- 2026: 14 · 2025: 65 · 2024: 66 · 2023: 77 · 2022: 82 · 2021: 68 · 2020: 69 · 2019: 40 · 2018: 49 · 2017: 47 · 2016: 39 · 2015: 39 · 2014: 45 · 2013: 32 · 2012: 26
- FWCI
- 3.86
- Type
- journal article
- Language
- en
- Open access
- green
- www.zora.uzh.ch
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- Intensive Care Medicine (publishedVersion)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, other-oa)
- reroDoc Digital Library (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
- Zurich Open Repository and Archive (University of Zurich)
- Topics
- Health Sciences › Medicine › Critical Care and Intensive Care Medicine › Sepsis Diagnosis and Treatment
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- diagnostic accuracy, sepsis, critical appraisal, sensitivity and specificity, likelihood ratios, predictive value, receiver operating characteristic, diagnostic odds ratio, reporting guidelines, infection diagnosis
- MeSH terms
- Bayes Theorem, Diagnostic Tests, Routine, Humans, ROC Curve, Sensitivity and Specificity, Switzerland, Confidence Intervals, Likelihood Functions, Odds Ratio, Sepsis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review