Theodora Pappa ¹ Ariel L. Rivas ² Michelle J. Iandiorio ^2* Almira L. Hoogesteijn ³ Jeanne M. Fair ⁴ Andrea Paola Rojas Gil ⁵ Angeliki R. Burriel ⁵ Pantelis G. Bagos ^6* Stylianos Chatzipanagiotou ⁷ Anastasios Ioannidis ^5*

• ¹ Tripoli Panarkadian Hospital, Tripoli, Greece
• ² University of New Mexico, Albuquerque, United States
• ³ Department of Human Ecology, CINVESTAV, Merida, Yucatan, Mexico
• ⁴ Los Alamos National Laboratory (DOE), Los Alamos, New Mexico, United States
• ⁵ Department of Nursing, Faculty of Health Sciences, University of Peloponnese, Tripoli, Greece
• ⁶ Technological Educational Institute of Central Greece, Lamia, Greece
• ⁷ Department of Clinical Microbiology and Medical Biopathology, Aeginition Hospital, National and Kapodistrian University of Athens, Athens, Greece

Data overlapping of different biological conditions prevents personalized medical decision-making. For example, when the neutrophil percentages of surviving septic patients overlap with those of non-survivors, no individualized assessment is possible. To ameliorate this problem, an immunological method was explored in the context of sepsis.Blood leukocyte counts and relative percentages as well as the serum concentration of several proteins were investigated with 4072 longitudinal samples collected from 331 hospitalized patients classified as septic (n=286), non-septic (n=43), or not assigned (n=2). Two methodological approaches were evaluated: (i) a reductionist alternative, which analyzed variables in isolation; and (ii) a non-reductionist version, which examined interactions among six (leukocyte-, bacterial-, temporal-, personalized-, population-, and outcome-related) dimensions.The reductionist approach did not distinguish outcomes: the leukocyte and serum protein data of survivors and non-survivors overlapped. In contrast, the non-reductionist alternative differentiated several data groups, of which at least one was only composed of survivors (a finding observable since hospitalization day 1). Hence, the non-reductionist approach promoted personalized medical practices: every patient classified within a subset associated with 100 % survival subset was likely to survive. The non-reductionist method also revealed five inflammatory or disease-related stages (provisionally named 'early inflammation, early immunocompetence, intermediary immuno-suppression, late immuno-suppression, or other'). Mortality data validated these labels: both 'suppression' subsets revealed 100% mortality, the 'immunocompetence' group exhibited 100% survival, while the remaining sets reported twodigit mortality percentages. While the 'intermediary' suppression expressed an impaired monocyte-related function, the 'late' suppression displayed renal-related dysfunctions, as indicated by high concentrations of urea and creatinine.The data-driven differentiation of five data groups may foster early and non-overlapping