Association between diarrhea quantity and in-hospital mortality in intensive care unit patients: A retrospective cohort study

Association between diarrhea quantity and in-hospital mortality in intensive care unit patients: A retrospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Association between diarrhea quantity and in-hospital mortality in intensive care unit patients: A retrospective cohort study Ryohei Yamamoto, Hajime Yamazaki, Shungo Yamamoto, Yuna Ueta, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-859799/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Previous studies have shown that diarrhea is associated with increased mortality of patients in intensive care units (ICUs). However, these studies used dichotomized cutoff values, even if diarrhea was a continuous condition. This study aimed to assess the association between diarrhea quantity and mortality in ICU patients with newly developed diarrhea. Methods We conducted this single-center retrospective cohort study at the Kameda Medical Center ICU. We consecutively included all adult ICU patients with newly developed diarrhea in the ICU between January 2017 and December 2018. Newly developed diarrhea was defined based on a Bristol stool chart scale ≥ 6 and frequency of diarrhea ≥ 3 times per day. We excluded patients who already had diarrhea on the day of ICU admission among other criteria. We collected data on the quantity of diarrhea on the day when patients newly developed diarrhea. The primary outcome was in-hospital mortality. The risk ratio (RR) and 95% confidence interval (CI) for the association between the quantity of diarrhea and mortality were estimated using multivariable-modified Poisson regression models adjusted for the Charlson Comorbidity Index, sequential organ failure assessment score, and serum albumin levels. Results Among 231 participants, 68.4% (158/231) were men; the median age of the patients was 72 years. The median quantity of diarrhea was 401 g (interquartile range [IQR] 230‒645 g), and in-hospital mortality was 22.9% (53/231). More diarrhea at baseline was associated with higher in-hospital mortality; the unadjusted RR (95% CI) per 200-g increase was 1.10 (1.01‒1.19). This association remained in the multivariable-adjusted analysis; the adjusted RR (95% CI) per 200-g increase was 1.10 (1.01‒1.20). Conclusions A greater quantity of diarrhea was an independent risk factor for in-hospital mortality. The quantity of diarrhea may be an indicator of disease severity in ICU patients. Critical Care & Emergency Medicine Molecular Epidemiology intensive care diarrhea mortality retrospective cohort study Figures Figure 1 Background Diarrhea is a common gastrointestinal symptom in the intensive care unit (ICU), with an incidence of 10–78% [ 1 ]. In ICU patients, enteral nutrition (composition, osmolarity, speed, intermittent or continuous, fiber), drugs (e.g., antibiotics, laxatives), infectious diseases (e.g., Clostridium difficile infection [CDI]), and comorbidity (e.g., anemia, cirrhosis) are common causes of diarrhea [ 2 ]. The effects of diarrhea include increased risk of contamination of devices and wounds, dehydration, electrolyte abnormalities, and malabsorption [ 3 – 5 ]. Several studies have shown an association between diarrhea and mortality [ 6 – 14 ], and this association remained even in ICU patients without CDI [ 8 ]. Taito et al. conducted a systematic review and demonstrated that diarrhea was associated with the length of hospital stay and ICU mortality [ 14 ]; however, all previous studies defined diarrhea based on dichotomized criteria with respect to consistency and frequency. The European Society of Intensive Care Medicine (ESICM) has adopted dichotomized criteria for the quantity of diarrhea as a component of the definition of diarrhea in the ICU [ 3 ]. However, healthcare providers need to make decisions based on continuous conditions rather than dichotomized conditions in practice [ 15 , 16 ]. For example, more diarrhea may cause worse electrolyte imbalance, nutritional deficit, and hemodynamic instability owing to water loss [ 17 , 18 ], which leads to changes in clinical management. Moreover, more diarrhea may result in more deaths. To clarify this, it is necessary to quantify the relationship between the quantity of diarrhea and death. This retrospective cohort study aimed to investigate the association between the quantity of diarrhea and mortality in ICU patients with newly developed diarrhea. Methods Study design and setting We conducted this single-center retrospective cohort study at Kameda Medical Center ICU. This study was reviewed and approved by the institutional review board of Kameda Medical Center and Kyoto University. These committees waived the requirement of informed consent from all participants enrolled in this study because of the retrospective study design. This study was conducted according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [ 19 ]. Study population From January 2017 to December 2018, we consecutively included all patients aged ≥ 18 years with newly developed diarrhea in the ICU. We defined newly developed diarrhea in the ICU as three or more loose or liquid stools per day according to the World Health Organization (WHO) definition [ 20 ]. To include patients with newly developed diarrhea in the ICU, the following patients were excluded on the day of ICU admission: patients with a stoma, chronic diarrhea (e.g., inflammatory bowel syndrome, short bowel syndrome), post-gastrointestinal surgery, gastrointestinal bleeding, or bacterial and viral enteritis (including Clostridium difficile enteritis and cytomegalovirus enteritis) or those who already had diarrhea on the day of ICU admission. In addition, patients readmitted to the ICU and those who died on the day of admission were excluded. Data collection We collected data such as age, sex, admission category (medical or surgery), sepsis defined by sepsis-3 [ 21 ], ICU readmission, Charlson Comorbidity Index (CCI) [ 22 ], and treatment limitation (limitations in providing ICU-specific life-sustaining therapies such as mechanical ventilation, cardiopulmonary resuscitation) from electronic health record reviews. Other data such as Acute Physiology and Chronic Health Evaluation (APACHE) II score [ 23 ], Simplified Acute Physiology Score (SAPS) II [ 24 ], Sequential Organ Failure Assessment (SOFA) score [ 25 ], potential causes of diarrhea (proton pump inhibitor, enteral nutrition, antibiotics, laxative drugs), testing for CDI (glutamate dehydrogenase test, CD toxin, or stool culture), and biopsy-diagnosed cytomegalovirus enteritis were also collected. We refer to CCI with age score as “CCI” and defined CCI without age score as “CCI without age score.” Measurement of diarrhea Stool data of ICU patients were collected from electronic health records. Nurses routinely checked the presence or absence of stools every 2–4 h. If there was a stool, consistency and quantity were assessed. Each stool sample was evaluated using the Bristol Stool Chart Scale (BSCS) [ 26 ]. The BSCS is a 7-point scale in which stools are scored according to cohesion and surface cracking as follows: 1. separate hard lumps like nuts; 2. sausage shaped but lumpy; 3. like a sausage or snake but with cracks on its surface; 4. like a sausage or snake and smooth and soft; 5. soft blobs with a clear-cut edge; 6. fluffy pieces with ragged edges and mushy; and 7. watery with no solid pieces. A BSCS of 6 or 7 is classified as diarrhea [ 27 , 28 ]. This scale has been evaluated for its concordance and is a widely used scale [ 28 – 34 ]. The quantity of stool was measured using a weight scale and recorded in the electronic medical records. Since most ICU patients had urinary catheters, contamination of the stool by urine was minimized. The main exposure was the quantity of diarrhea per day on the day of the diarrhea diagnosis. The daily quantity of diarrhea was calculated from calendar days (total quantity from 0:00 to 24:00). These data were collected from the electronic health records. Outcome measurement The primary outcome was in-hospital mortality. Secondary outcomes included ICU, 28-day, and 90-day mortalities; ICU-free days at the 28th day [ 35 ]; and hospital-free days at the 90th day [ 36 ]. In these free days, we used the event-free survival day (the number of event-free days was considered to be zero for patients who died in the time frame) to measure these outcomes [ 33 , 34 , 38 ]. Statistical analyses Patient characteristics are described as median and interquartile range (IQR). Modified Poisson regression models were used to estimate risk ratios (RRs) and 95% confidence intervals (CIs) for the association between the quantity of diarrhea (per 200-g increase) and in-hospital mortality [ 37 , 38 ]. The reason for using the unit of 200 g is that the ESICM definition of diarrhea is 200–250 g [ 3 ]. The multivariable analysis was adjusted for CCI, SOFA score, and serum albumin levels. These covariates were selected a priori based on clinical plausibility and previous studies [ 2 , 8 , 13 ]. We performed multiple imputations for missing values using multiple imputations by chained equation (MICE) with 50 iterations that generated 100 datasets with imputed missing values [ 39 , 40 ]. To perform sensitivity analyses, we tested several modified Poisson regression models to assess the robustness of the primary analysis. First, we adjusted for the following covariates: model 1 for age, sex, CCI without age score, SOFA score, and serum albumin; model 2 for CCI, APACHE II score, and serum albumin; model 3 for CCI, SAPS II score, and serum albumin; and model 4 for CCI, SOFA score, serum albumin, and enteral nutrition. Second, we conducted a complete case analysis. Third, because CDI and cytomegalovirus enteritis affect mortality, we performed a further analysis excluding patients diagnosed with them after ICU admission. Finally, instead of using continuous data (the actual quantity of diarrhea), we used categorical data (near quartiles of the quantity of diarrhea) for the primary model. We applied the same analyses as that for the primary outcome to assess the association between the quantity of diarrhea (per 200-g increase) and the following secondary outcomes: ICU mortality, 28-day mortality, and 90-day mortality. We reported 95% CIs as an informal measure of uncertainty and avoided using terms such as statistical significance according to the recommendation of the American Statistical Association [ 41 ]. The analyses were performed using R software, version 4.0.3 (The R Foundation for Statistical Computing, Vienna, Austria; https://www.R-project.org/ ). Results Patient characteristics During the study period, 1579 adult patients were admitted to the ICU, and 334 patients with newly developed diarrhea were included in this study. Among those patients, 103 were excluded. Finally, 231 patients were included in the analysis (Fig. 1 ). The median age of patients was 72 (IQR [64, 80]) years, 158/231 (68.4%) patients were men, median CCI was two (IQR [ 1 , 3 ]), median APACHE II score was 21 (IQR [ 14 , 28 ]), and median SOFA score was 9 (IQR [ 6 , 12 ]). Patients admitted for nonoperative reasons were the most prevalent (162/231, 70.1%). Sepsis was diagnosed in 121 patients (52.4%). Antimicrobials and laxative drugs as possible causes of diarrhea were administered to 214/231 (92.6%) and 119/231 (51.5%) patients, respectively. Overall, 2/231 (0.9%) patients were diagnosed with CDI in the ICU, and two (0.9%) patients were diagnosed with CMV by colonoscopic biopsy in the ICU. The medina number of days from ICU admission to newly developed diarrhea was 3 (IQR [ 2 , 6 ]), and the median quantity of diarrhea was 401 (IQR [230.5, 645]) g. Other patient characteristics on ICU admission are summarized in Table 1 . Three patients had missing values for the severity score because arterial blood gas was not measured. There were no missing measurements for other variables, including the quantity of diarrhea. Table 1 Baseline characteristics of the study patients Total n = 231 Sex, males, n (%) 158 (68.4) Age, median [IQR] 72 [64, 80] Admission source, n (%) Hospital ward 56 (24.2) Emergency department 106 (45.9) Elective surgery 39 (16.9) Emergency surgery 30 (13.0) Charlson comorbidity index, median [IQR] 2 [ 1 , 3 ] Serum albumin, median [IQR], g/dL 2.80 [2.20, 3.20] SOFA score*, median [IQR] 9 [ 6 , 12 ] APACHE II score*, median [IQR] 21 [ 14 , 28 ] SAPS II score*, median [IQR] 48 [37, 60] ARDS, n (%) 42 (18.2) Sepsis, n (%) 121 (52.4) Acute kidney injury, n (%) 105 (41.1) Renal replacement therapy, n (%) 58 (25.1) Mechanical ventilation, n (%) 147 (63.6) Noradrenaline, n (%) 139 (60.2) Proton pump inhibitor, n (%) 196 (84.8) Laxative drug, n (%) 119 (51.5) Antibiotics, n (%) 214 (92.6) Antiviral, n (%) 18 (7.8) Chemotherapy, n (%) 8 (3.5) Enteral nutrition, n (%) 157 (68.0) Clostridium difficile infection † , n (%) 2 (0.9) Cytomegalovirus enteritis, n (%) 2 (0.9) Quantity of diarrhea, median [IQR], g 401 [230, 645] Onset of diarrhea ‡ , median [IQR], day 3 [ 2 , 6 ] *Three missing data †Defined by glutamate dehydrogenase positivity and Clostridium difficile toxin positivity. ‡Number of days from ICU admission to the onset of diarrhea IQR: Interquartile range, SOFA: Sequential organ dysfunction assessment, ARDS: Acute respiratory distress syndrome, APACHE II: Acute Physiology and Chronic Health Disease Classification System, SAPS II: Simplified acute physiology score. Association between the quantity of diarrhea and outcomes Table 2 presents the primary and secondary outcomes. Two and 16 patients were lost to 28-day and 90-day follow-ups, respectively. In the unadjusted analysis, the quantity of diarrhea was associated with increased in-hospital mortality (unadjusted RR per 200 g increased: 1.10 [95% CI 1.01–1.19], p = 0.03). After adjusting for CCI, SOFA score, and serum albumin level, this association remained (adjusted RR per 200-g increase: 1.10 [95% CI 1.01–1.20], p = 0.03) (Table 3 ). Table 2 Summary of primary and secondary outcomes Total n = 231 Primary outcome Hospital mortality, n/total n (%) 53/231 (22.9) Secondary outcomes ICU mortality, n/total n (%) 21/231 (9.1) 28-day mortality*, n/total n (%) 35/229 (15.3) 90-day mortality † , n/total n (%) 52/215 (24.2) ICU LOS, median [IQR], day 7.0 [4.0, 12.4] ICU-free day survival at 28*, median [IQR], day 20.0 [14.0, 23.0] Hospital LOS, median [IQR], day 35.0 [18.4, 58.0] Hospital-free day survival at 90 † , median [IQR], day 45.0 [0, 66.5] *Two patients lost to follow-up, †16 patients lost to follow-up. There were no missing measurements in other outcomes. IQR: Interquartile range, LOS: Length of stay, IQR: Interquartile range, LOS: Length of stay Table 3 Association between the quantity of diarrhea and in-hospital mortality Unadjusted Adjusted RR [95% CI] p-value RR [95% CI] p-value Primary analysis (per 200-g diarrhea increase) 1.10 [1.01, 1.19] 0.031 1.10 [1.01, 1.20] 0.029 Sensitivity analyses (per 200-g diarrhea increase) Model 1 1.09 [0.98, 1.20] 0.080 Model 2 1.10 [1.01, 1.20] 0.028 Model 3 1.11 [1.02, 1.22] 0.018 Model 4 1.10 [1.00, 1.20] 0.041 Complete case analysis 1.10 [1.05, 1.15] 0.001> 1.10 [1.04, 1.17] 0.002 Exclude CDI or CMV diagnosed in ICU 1.10 [1.03, 1.17] 0.006 1.14 [1.04, 1.24] 0.004 Quantile-defined categories Mild (< 250 g) 1.00 (reference) 1.00 (reference) Moderate (250‒399 g) 0.97 [0.38, 2.49] 0.953 1.02 [0.51, 2.04] 0.963 Severe (400‒649 g) 1.11 [0.46, 2.68] 0.823 1.29 [0.69, 2.43] 0.421 Very severe (≥ 650 g) 1.61 [0.85, 3.04] 0.145 1.77 [0.99, 3.21] 0.056 Primary model: CCI, SOFA score, and serum albumin, Model 1: age, sex, CCI without age score, SOFA score, and serum albumin. Model 2: CCI, APACHE II score, and serum albumin. Model 3: CCI, SAPS II score, and serum albumin. Model 4: CCI, SOFA score, serum albumin, and enteral nutrition RR: Risk ratio, CI: Confidence interval, CCI: Charlson comorbidity index, SOFA: Sequential Organ Failure Assessment, CDI: Clostridium difficile infection, CMV: Cytomegalovirus enteritis Sensitivity analyses for the primary analysis The association between the quantity of diarrhea and in-hospital mortality remained similar in various multivariable analysis models and other sensitivity analyses (Table 3 ). We also performed a sensitivity analysis using the categories of the quantity of diarrhea. With no established criteria to distinguish the quantity of diarrhea, we used near-quantile-defined categories of the quantity of diarrhea. The quartiles of diarrhea were 230 g in the 25th percentile, 401 g in the 50th percentile, and 645 g in the 75th percentile. Therefore, the patients were divided into the following categories: mild (< 250 g), moderate (250–399 g), severe (400–649 g), and very severe (≥ 650 g). In-hospital mortality was 19.7% (12/61) for mild, 19.2% (10/52) for moderate, 21.3% (13/61) for severe, and 31.6% (18/57) for very severe. Multivariable-modified Poisson regression analysis using these categories, with the same adjustments as in the primary model, showed a trend toward increased in-hospital mortality as the quantity of diarrhea increased (Table 3 ). Secondary analyses For secondary analyses, a similar association was observed between the quantity of diarrhea and ICU 28-day and 90-day mortalities (Table 4 ). Multivariable analysis showed a similar trend of higher mortality with higher quantities of diarrhea. Table 4 Association between 200-g increase in the quantity of diarrhea and secondary outcomes Unadjusted Adjusted RR [95% CI] p-value RR [95% CI] p-value ICU mortality 1.17 [1.07, 1.29] 0.001 1.20 [1.07, 1.35] 0.002 28-day mortality 1.11 [1.01, 1.23] 0.028 1.11 [0.99, 1.23] 0.053 90-day mortality 1.10 [1.01, 1.19] 0.028 1.11 [1.01, 1.21] 0.025 All analyses were adjusted for CCI, SOFA score, and serum albumin level. RR: Risk ratio, CI: Confidence interval, CCI: Charlson comorbidity index, SOFA: Sequential Organ Failure Assessment Discussion In this retrospective study, we investigated the association between the quantity of diarrhea and in-hospital mortality in 231 patients with newly developed diarrhea in the ICU. Multivariable analysis revealed that diarrhea quantity was an independent predictor of in-hospital mortality. This association was consistent across several sensitivity analyses. Similarly, the greater the quantity of diarrhea, the higher the ICU 28-day and 90-day mortalities. To the best of our knowledge, this is the first study to show an association between the quantity of diarrhea and mortality. Previous studies have reported an association between the presence of diarrhea and mortality; however, no studies have examined whether mortality increases with a greater quantity of diarrhea [ 14 , 42 ]. A systematic review of 12 studies, most of which used the definition of diarrhea as three or more loose or liquid stools, showed an association between diarrhea and mortality (RR: 1.43; 95% CI: 1.03–1.98; I 2 = 86.7%; n = 11,866) [ 14 ]. We focused on the quantity of diarrhea in this study and showed that mortality increased with increasing quantity of diarrhea according to the adjusted RR in patients with newly developed diarrhea in the ICU. More diarrhea leads to worse electrolyte imbalance, nutritional deficit, and hemodynamic instability owing to water loss [ 17 , 18 ]. Clinicians need to correct electrolytes, adjust enteral nutrition, and increase fluid administration as diarrhea increases. The reason for the higher mortality rate among patients with a greater quantity of diarrhea remains unclear. Patients with CDI or cytomegalovirus enteritis, which are common diseases causing diarrhea, have been reported to have higher mortality, but they were excluded from our study. Indeed, diarrhea can cause dehydration, electrolyte abnormalities, metabolic acidosis, malnutrition, device contamination, and wound contamination [ 1 ]. However, since dehydration and electrolyte abnormalities are carefully corrected in the ICU, it is questionable to assume that diarrhea directly contributes to mortality. Possible explanations for the relationship between diarrhea and mortality are as follows. First, diarrhea can be a sign of gastrointestinal organ failure that is associated with a high risk of mortality [ 4 , 14 , 43 ]. Patients with diarrhea have higher severity scores than those without diarrhea [ 2 , 6 , 8 – 10 , 14 ]. In our study, most patients received treatments that could cause diarrhea, such as enteral nutrition and antimicrobials. These interventions are part of the treatment regimen for critically ill patients. In addition, approximately 60% of patients were on ventilation and used vasopressors, which means that patients with diarrhea have a higher severity of illness. In our analysis, we adjusted for the SOFA score, an organ disorder score that does not include gastrointestinal function and showed that diarrhea is a risk factor for mortality independent of other organ disorders. The quantity of diarrhea may be a candidate when adjusting for organ dysfunction. Second, diarrhea can be a sign of a disorder of the gut microbiota, which is called dysbiosis. This dysbiosis is believed to increase vulnerability to nosocomial infections, sepsis, organ failure, and mortality [ 44 , 45 ]. The development of diarrhea might be associated with dysbiosis in the gut microbiota of ICU patients [ 46 ]. However, our data and analyses are not sufficiently conclusive to prove them. Further research is needed to test these hypotheses. This study had several limitations. First, the measurement of diarrhea was not completely accurate. If diarrhea spills out of the diaper, it may not be measured. In this case, this may have led to an underestimation of the quantity of diarrhea. However, we believe that this measurement of the quantity of diarrhea reflects real clinical practice. Second, the inter-rater reliability of BSCS was not confirmed in our study. The reliability of BSCS has been studied and widely used [ 26 – 32 ], and our nurses were trained to measure BSCS in clinical practice, which should have minimized the inter-rater variability. Third, we did not obtain information on urinary catheter insertion. However, we expect that most patients in this study had urinary catheters because only critically ill patients were admitted to our ICU (a median SOFA score of 9 and 63.6% of them were on ventilators). Finally, this was a single-center study, and the generalizability of the results is limited. Conclusions In ICU patients with newly developed diarrhea, greater quantity of diarrhea was associated with higher mortality. The quantity of diarrhea may be considered an indicator of disease severity in ICU patients. Further research is needed to determine if there is a causal relationship between the quantity of diarrhea and death. Abbreviations ICU Intensive care unit RR Risk ratio IQR Interquartile range CI Confidence interval ESICM European Society of Intensive Care Medicine CDI Clostridium difficile infection CMV Cytomegalovirus STROBE Strengthening the Reporting of Observational studies in Epidemiology WHO World Health Organization BSCS Bristol stool chart scale CCI Charlson Comorbidity Index APACHE Acute Physiology and Chronic Health Evaluation SAPS Simplified Acute Physiology Score SOFA Sequential Organ Failure Assessment Declarations Ethics approval and consent to participate This study was approved, and the need for informed consent was waived by the institutional review boards of the participating hospital. Consent for publication Not applicable. Availability of data and materials The dataset of this study is not publicly available based on the decision of the first author. Competing interests All authors have no conflicts of interest to declare. Funding This study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ contributions RY has complete access to the study data and takes responsibility for the data integrity. All authors contributed to the study concept and design. RY and YU contributed to data acquisition. RY and RU contributed to data analysis and interpretation. RY, RU, and HY drafted the manuscript. All authors are responsible for the critical revision of the manuscript for important intellectual content and have approved the final manuscript. Acknowledgments The authors thank the staff of the ICU of the Kameda Medical Center. We thank the Japanese Society of Education for Physicians and Trainees in the Intensive Care Clinical Trial Group for their suggestions and comments on the earlier concept of this study. References Reintam Blaser A, Deane AM, Fruhwald S. Diarrhoea in the critically ill. Curr Opin Crit Care. 2015;21(2):142–53. Thibault R, Graf S, Clerc A, Delieuvin N, Heidegger C, Pichard C. Diarrhoea in the ICU: respective contribution of feeding and antibiotics. Crit Care. 2013;17(4):R153. Reintam Blaser A, Malbrain MLNG, Starkopf J, Fruhwald S, Jakob SM, De Waele J, et al. Gastrointestinal function in intensive care patients: terminology, definitions and management. Recommendations of the ESICM Working Group on Abdominal Problems. Intensive Care Med. 2012;38(3):384–94. Reintam A, Parm P, Kitus R, Kern H, Starkopf J. Gastrointestinal symptoms in intensive care patients. Acta Anaesthesiol Scand. 2009;53(3):318–24. Hiesmayr M, Schindler K, Pernicka E, Schuh C, Schoeniger-Hekele A, Bauer P, et al. Decreased food intake is a risk factor for mortality in hospitalised patients: the NutritionDay survey 2006. Clin Nutr. 2009;28(5):484–91. Borges SL, Pinheiro BDV, Pace FHDL, Chebli JMF. Diarréia nosocomial em unidade de terapia intensiva: incidência e fatores de risco. Arq Gastroenterol. 2008;45(2):117–23. Ozgur M, Girgin NK, Akalin H, Iscimen R, Sinirtas M, Kahveci F. A retrospective evaluation of the incidence and risk factors of nosocomial diarrhea in critically ill adult patients. Acta Medica. 2016;32:741–6. Tirlapur N, Puthucheary ZA, Cooper JA, Sanders J, Coen PG, Moonesinghe SR, et al. Diarrhoea in the critically ill is common, associated with poor outcome and rarely due to Clostridium difficile. Sci Rep. 2016;6(1):24691. Wu TJ, Liu ZJ, Zhao YM, Yang CL, Zhang CY. [Clinical analysis of the factors related to diarrhea in intensive care unit]. Zhongguo Wei Zhong Bing Ji Jiu Yi Xue. 2004;16(12):747–9. Jakob SM, Bütikofer L, Berger D, Coslovsky M, Takala J. A randomized controlled pilot study to evaluate the effect of an enteral formulation designed to improve gastrointestinal tolerance in the critically ill patient—the SPIRIT trial. Critical Care. 2017;21(1). Vieira LV, Pedrosa LAC, Souza VS, Paula CA, Rocha R. Incidence of diarrhea and associated risk factors in patients with traumatic brain injury and enteral nutrition. Metab Brain Dis. 2018;33(5):1755–60. Rodrigues de Barros J, Fraga Lobo IM, Melo Soares F, Ferreira de Almeida DSS. Factors associated with diarrhea in a unit of intensive therapy: cohort study. NUTRICION CLINICA Y DIETETICA HOSPITALARIA. 2018;38(2):122–7. Atasever AG, Ozcan PE, Kasali K, Abdullah T, Orhun G, Senturk E. The frequency, risk factors, and complications of gastrointestinal dysfunction during enteral nutrition in critically ill patients. Ther Clin Risk Manag. 2018;14:385–91. Taito S, Kawai Y, Liu K, Ariie T, Tsujimoto Y, Banno M, et al. Diarrhea and patient outcomes in the intensive care unit: Systematic review and meta-analysis. J Crit Care. 2019;53:142–8. Altman DG, Royston P. The cost of dichotomising continuous variables. BMJ. 2006;332(7549):1080.1. Dawson NV, Weiss R. Dichotomizing Continuous Variables in Statistical Analysis. Med Decis Making. 2012;32(2):225–6. Wierdsma NJ, Peters JH, Weijs PJ, Keur MB, Girbes AR, Van Bodegraven AA, et al. Malabsorption and nutritional balance in the ICU: fecal weight as a biomarker: a prospective observational pilot study. Crit Care. 2011;15(6):R264. Anigilaje EA. Management of Diarrhoeal Dehydration in Childhood: A Review for Clinicians in Developing Countries. Front Pediatr. 2018;6:28. Von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting Observational Studies. Ann Intern Med. 2007;147(8):573. Diarrhoeal disease 2017 [updated 2. May 2017. Available from: https://www.who.int/en/news-room/fact-sheets/detail/diarrhoeal-disease . Seymour CW, Liu VX, Iwashyna TJ, Brunkhorst FM, Rea TD, Scherag A, et al. Assessment of Clinical Criteria for Sepsis. JAMA. 2016;315(8):762. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13(10):818–29. Le Gall JR, Lemeshow S, Saulnier F. A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study. Jama. 1993;270(24):2957–63. Vincent JL, Moreno R, Takala J, Willatts S, De Mendonça A, Bruining H, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22(7):707–10. O'Donnell LJ, Virjee J, Heaton KW. Detection of pseudodiarrhoea by simple clinical assessment of intestinal transit rate. BMJ. 1990;300(6722):439–40. Lacy BE, Mearin F, Chang L, Chey WD, Lembo AJ, Simren M, et al. Bowel Disorders Gastroenterology. 2016;150(6):1393 – 407.e5. Cook DJ, Johnstone J, Marshall JC, Lauzier F, Thabane L, Mehta S, et al. Probiotics: Prevention of Severe Pneumonia and Endotracheal Colonization Trial—PROSPECT: a pilot trial. Trials. 2016;17(1). Koh H, Lee MJ, Kim MJ, Shin JI, Chung KS. Simple diagnostic approach to childhood fecal retention using the Leech score and Bristol stool form scale in medical practice. J Gastroenterol Hepatol. 2010;25(2):334–8. Dionne JC, Sullivan K, Mbuagbaw L, Takaoka A, Duan EH, Alhazzani W, et al. Diarrhoea: interventions, consequences and epidemiology in the intensive care unit (DICE-ICU): a protocol for a prospective multicentre cohort study. BMJ Open. 2019;9(6):e028237. Caroff DA, Edelstein PH, Hamilton K, Pegues DA. The Bristol Stool Scale and Its Relationship to Clostridium difficile Infection. J Clin Microbiol. 2014;52(9):3437–9. Lewis SJ, Heaton KW. Stool Form Scale as a Useful Guide to Intestinal Transit Time. Scand J Gastroenterol. 1997;32(9):920–4. Bishop S, Young H, Goldsmith D, Buldock D, Chin M, Bellomo R. Bowel motions in critically ill patients: a pilot observational study. Crit Care Resusc. 2010;12(3):182–5. Schmidt SB, Kulig W, Winter R, Vasold AS, Knoll AE, Rollnik JD. The effect of a natural food based tube feeding in minimizing diarrhea in critically ill neurological patients. Clin Nutr. 2019;38(1):332–40. Agus MSD, Wypij D, Hirshberg EL, Srinivasan V, Faustino EV, Luckett PM, et al. Tight Glycemic Control in Critically Ill Children. N Engl J Med. 2017;376(8):729–41. Self WH, Semler MW, Wanderer JP, Wang L, Byrne DW, Collins SP, et al. Balanced Crystalloids versus Saline in Noncritically Ill Adults. N Engl J Med. 2018;378(9):819–28. Zou G. A Modified Poisson Regression Approach to Prospective Studies with Binary Data. Am J Epidemiol. 2004;159(7):702–6. Holmberg MJ, Andersen LW. Estimating Risk Ratios and Risk Differences. JAMA. 2020;324(11):1098. Rubin DB. Multiple imputation for nonresponse in surveys. John Wiley & Sons; 2004. Groothuis-Oudshoorn K, Van Buuren S. Mice: multivariate imputation by chained equations in R. J Stat Softw. 2011;45(3):1–67. Wasserstein RL, Lazar NA. The ASA Statement on p-Values: Context, Process, and Purpose. The American Statistician. 2016;70(2):129–33. Lebak KJ, Bliss DZ, Savik K, Patten-Marsh KM. What's New on Defining Diarrhea in Tube-Feeding Studies? Clinical Nursing Research. 2003;12(2):174–204. Reintam Blaser A, Poeze M, Malbrain MLNG, Björck M, Oudemans-Van Straaten HM, Starkopf J. Gastrointestinal symptoms during the first week of intensive care are associated with poor outcome: a prospective multicentre study. Intensive Care Med. 2013;39(5):899–909. Kitsios GD, Morowitz MJ, Dickson RP, Huffnagle GB, McVerry BJ, Morris A. Dysbiosis in the intensive care unit: Microbiome science coming to the bedside. J Crit Care. 2017;38:84–91. Mcdonald D, Ackermann G, Khailova L, Baird C, Heyland D, Kozar R, et al. Extreme Dysbiosis of the Microbiome in Critical Illness mSphere. 2016;1(4):e00199-16. Duan J, Meng X, Liu S, Zhou P, Zeng C, Fu C, et al. Gut Microbiota Composition Associated With Clostridium difficile-Positive Diarrhea and C. difficile Type in ICU Patients. Frontiers in Cellular and Infection Microbiology. 2020;10. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-859799","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":49241955,"identity":"e410d275-79dc-4f45-bc5c-807f1824a828","order_by":0,"name":"Ryohei Yamamoto","email":"","orcid":"https://orcid.org/0000-0002-5144-6585","institution":"Kyoto University Graduate School of Medicine Faculty of Medicine: Kyoto Daigaku Daigakuin Igaku Kenkyuka Igakubu","correspondingAuthor":false,"prefix":"","firstName":"Ryohei","middleName":"","lastName":"Yamamoto","suffix":""},{"id":49241956,"identity":"33f7fee7-985e-4c2d-9378-212ed2d73c7b","order_by":1,"name":"Hajime Yamazaki","email":"","orcid":"","institution":"Kyoto University: Kyoto Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Hajime","middleName":"","lastName":"Yamazaki","suffix":""},{"id":49241957,"identity":"0fec2f22-3be9-444f-8bd8-c92fece4345f","order_by":2,"name":"Shungo Yamamoto","email":"","orcid":"","institution":"Kyoto University: Kyoto Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Shungo","middleName":"","lastName":"Yamamoto","suffix":""},{"id":49241958,"identity":"2d22137e-3cf4-4576-bbaa-4cc65b43f47c","order_by":3,"name":"Yuna Ueta","email":"","orcid":"","institution":"Kameda Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Yuna","middleName":"","lastName":"Ueta","suffix":""},{"id":49241959,"identity":"92c39814-0a6c-4285-a324-f98fc974e07d","order_by":4,"name":"Ryo Ueno","email":"","orcid":"","institution":"Australian and New Zealand intensive care research center","correspondingAuthor":false,"prefix":"","firstName":"Ryo","middleName":"","lastName":"Ueno","suffix":""},{"id":49241960,"identity":"410151f1-1071-4c68-8bf0-4a611838a5ad","order_by":5,"name":"Yosuke Yamamoto","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0003-1104-2612","institution":"Australian and New Zealand intensive care research center","correspondingAuthor":true,"prefix":"","firstName":"Yosuke","middleName":"","lastName":"Yamamoto","suffix":""}],"badges":[],"createdAt":"2021-08-30 19:59:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-859799/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-859799/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":13018254,"identity":"1821007b-c64d-4bbb-9532-a7226bc7c7cd","added_by":"auto","created_at":"2021-09-02 15:28:32","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":140786,"visible":true,"origin":"","legend":"Flow diagram","description":"","filename":"Figure1flowdiagram.jpg","url":"https://assets-eu.researchsquare.com/files/rs-859799/v1/292d656cec9c17c174804dea.jpg"},{"id":13712593,"identity":"b6f50a72-1af8-40c5-ad73-c700a8efe9f9","added_by":"auto","created_at":"2021-09-17 14:28:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":459634,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-859799/v1/f6981c43-3f2b-4dab-b433-5f1bc06d08b2.pdf"}],"financialInterests":"","formattedTitle":"Association between diarrhea quantity and in-hospital mortality in intensive care unit patients: A retrospective cohort study","fulltext":[{"header":"Background","content":"\u003cp\u003eDiarrhea is a common gastrointestinal symptom in the intensive care unit (ICU), with an incidence of 10\u0026ndash;78% [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In ICU patients, enteral nutrition (composition, osmolarity, speed, intermittent or continuous, fiber), drugs (e.g., antibiotics, laxatives), infectious diseases (e.g., \u003cem\u003eClostridium difficile\u003c/em\u003e infection [CDI]), and comorbidity (e.g., anemia, cirrhosis) are common causes of diarrhea [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The effects of diarrhea include increased risk of contamination of devices and wounds, dehydration, electrolyte abnormalities, and malabsorption [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral studies have shown an association between diarrhea and mortality [\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10 CR11 CR12 CR13\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and this association remained even in ICU patients without CDI [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Taito et al. conducted a systematic review and demonstrated that diarrhea was associated with the length of hospital stay and ICU mortality [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]; however, all previous studies defined diarrhea based on dichotomized criteria with respect to consistency and frequency. The European Society of Intensive Care Medicine (ESICM) has adopted dichotomized criteria for the quantity of diarrhea as a component of the definition of diarrhea in the ICU [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, healthcare providers need to make decisions based on continuous conditions rather than dichotomized conditions in practice [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. For example, more diarrhea may cause worse electrolyte imbalance, nutritional deficit, and hemodynamic instability owing to water loss [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], which leads to changes in clinical management. Moreover, more diarrhea may result in more deaths. To clarify this, it is necessary to quantify the relationship between the quantity of diarrhea and death.\u003c/p\u003e \u003cp\u003eThis retrospective cohort study aimed to investigate the association between the quantity of diarrhea and mortality in ICU patients with newly developed diarrhea.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eWe conducted this single-center retrospective cohort study at Kameda Medical Center ICU. This study was reviewed and approved by the institutional review board of Kameda Medical Center and Kyoto University. These committees waived the requirement of informed consent from all participants enrolled in this study because of the retrospective study design. This study was conducted according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eFrom January 2017 to December 2018, we consecutively included all patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years with newly developed diarrhea in the ICU. We defined newly developed diarrhea in the ICU as three or more loose or liquid stools per day according to the World Health Organization (WHO) definition [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. To include patients with newly developed diarrhea in the ICU, the following patients were excluded on the day of ICU admission: patients with a stoma, chronic diarrhea (e.g., inflammatory bowel syndrome, short bowel syndrome), post-gastrointestinal surgery, gastrointestinal bleeding, or bacterial and viral enteritis (including \u003cem\u003eClostridium difficile\u003c/em\u003e enteritis and cytomegalovirus enteritis) or those who already had diarrhea on the day of ICU admission. In addition, patients readmitted to the ICU and those who died on the day of admission were excluded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eWe collected data such as age, sex, admission category (medical or surgery), sepsis defined by sepsis-3 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], ICU readmission, Charlson Comorbidity Index (CCI) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and treatment limitation (limitations in providing ICU-specific life-sustaining therapies such as mechanical ventilation, cardiopulmonary resuscitation) from electronic health record reviews. Other data such as Acute Physiology and Chronic Health Evaluation (APACHE) II score [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], Simplified Acute Physiology Score (SAPS) II [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], Sequential Organ Failure Assessment (SOFA) score [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], potential causes of diarrhea (proton pump inhibitor, enteral nutrition, antibiotics, laxative drugs), testing for CDI (glutamate dehydrogenase test, CD toxin, or stool culture), and biopsy-diagnosed cytomegalovirus enteritis were also collected. We refer to CCI with age score as \u0026ldquo;CCI\u0026rdquo; and defined CCI without age score as \u0026ldquo;CCI without age score.\u0026rdquo;\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement of diarrhea\u003c/h2\u003e \u003cp\u003eStool data of ICU patients were collected from electronic health records. Nurses routinely checked the presence or absence of stools every 2\u0026ndash;4 h. If there was a stool, consistency and quantity were assessed. Each stool sample was evaluated using the Bristol Stool Chart Scale (BSCS) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The BSCS is a 7-point scale in which stools are scored according to cohesion and surface cracking as follows: 1. separate hard lumps like nuts; 2. sausage shaped but lumpy; 3. like a sausage or snake but with cracks on its surface; 4. like a sausage or snake and smooth and soft; 5. soft blobs with a clear-cut edge; 6. fluffy pieces with ragged edges and mushy; and 7. watery with no solid pieces. A BSCS of 6 or 7 is classified as diarrhea [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This scale has been evaluated for its concordance and is a widely used scale [\u003cspan additionalcitationids=\"CR29 CR30 CR31 CR32 CR33\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The quantity of stool was measured using a weight scale and recorded in the electronic medical records. Since most ICU patients had urinary catheters, contamination of the stool by urine was minimized. The main exposure was the quantity of diarrhea per day on the day of the diarrhea diagnosis. The daily quantity of diarrhea was calculated from calendar days (total quantity from 0:00 to 24:00). These data were collected from the electronic health records.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eOutcome measurement\u003c/h2\u003e \u003cp\u003eThe primary outcome was in-hospital mortality. Secondary outcomes included ICU, 28-day, and 90-day mortalities; ICU-free days at the 28th day [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]; and hospital-free days at the 90th day [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In these free days, we used the event-free survival day (the number of event-free days was considered to be zero for patients who died in the time frame) to measure these outcomes [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003ePatient characteristics are described as median and interquartile range (IQR). Modified Poisson regression models were used to estimate risk ratios (RRs) and 95% confidence intervals (CIs) for the association between the quantity of diarrhea (per 200-g increase) and in-hospital mortality [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The reason for using the unit of 200 g is that the ESICM definition of diarrhea is 200\u0026ndash;250 g [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The multivariable analysis was adjusted for CCI, SOFA score, and serum albumin levels. These covariates were selected a priori based on clinical plausibility and previous studies [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. We performed multiple imputations for missing values using multiple imputations by chained equation (MICE) with 50 iterations that generated 100 datasets with imputed missing values [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo perform sensitivity analyses, we tested several modified Poisson regression models to assess the robustness of the primary analysis. First, we adjusted for the following covariates: model 1 for age, sex, CCI without age score, SOFA score, and serum albumin; model 2 for CCI, APACHE II score, and serum albumin; model 3 for CCI, SAPS II score, and serum albumin; and model 4 for CCI, SOFA score, serum albumin, and enteral nutrition. Second, we conducted a complete case analysis. Third, because CDI and cytomegalovirus enteritis affect mortality, we performed a further analysis excluding patients diagnosed with them after ICU admission. Finally, instead of using continuous data (the actual quantity of diarrhea), we used categorical data (near quartiles of the quantity of diarrhea) for the primary model.\u003c/p\u003e \u003cp\u003eWe applied the same analyses as that for the primary outcome to assess the association between the quantity of diarrhea (per 200-g increase) and the following secondary outcomes: ICU mortality, 28-day mortality, and 90-day mortality.\u003c/p\u003e \u003cp\u003eWe reported 95% CIs as an informal measure of uncertainty and avoided using terms such as statistical significance according to the recommendation of the American Statistical Association [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The analyses were performed using R software, version 4.0.3 (The R Foundation for Statistical Computing, Vienna, Austria; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.R-project.org/\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics\u003c/h2\u003e \u003cp\u003eDuring the study period, 1579 adult patients were admitted to the ICU, and 334 patients with newly developed diarrhea were included in this study. Among those patients, 103 were excluded. Finally, 231 patients were included in the analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe median age of patients was 72 (IQR [64, 80]) years, 158/231 (68.4%) patients were men, median CCI was two (IQR [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]), median APACHE II score was 21 (IQR [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]), and median SOFA score was 9 (IQR [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]). Patients admitted for nonoperative reasons were the most prevalent (162/231, 70.1%). Sepsis was diagnosed in 121 patients (52.4%). Antimicrobials and laxative drugs as possible causes of diarrhea were administered to 214/231 (92.6%) and 119/231 (51.5%) patients, respectively. Overall, 2/231 (0.9%) patients were diagnosed with CDI in the ICU, and two (0.9%) patients were diagnosed with CMV by colonoscopic biopsy in the ICU. The medina number of days from ICU admission to newly developed diarrhea was 3 (IQR [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]), and the median quantity of diarrhea was 401 (IQR [230.5, 645]) g. Other patient characteristics on ICU admission are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Three patients had missing values for the severity score because arterial blood gas was not measured. There were no missing measurements for other variables, including the quantity of diarrhea.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of the study patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal n\u0026thinsp;=\u0026thinsp;231\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, males, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158 (68.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 [64, 80]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdmission source, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital ward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (24.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency department\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e106 (45.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElective surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (16.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (13.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharlson comorbidity index, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum albumin, median [IQR], g/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.80 [2.20, 3.20]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA score*, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPACHE II score*, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAPS II score*, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 [37, 60]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARDS, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (18.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121 (52.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute kidney injury, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105 (41.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal replacement therapy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (25.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical ventilation, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147 (63.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNoradrenaline, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139 (60.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProton pump inhibitor, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e196 (84.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaxative drug, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e119 (51.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntibiotics, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214 (92.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntiviral, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (7.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (3.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnteral nutrition, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157 (68.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eClostridium difficile\u003c/em\u003e infection\u003csup\u003e\u0026dagger;\u003c/sup\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCytomegalovirus enteritis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuantity of diarrhea, median [IQR], g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e401 [230, 645]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnset of diarrhea\u003csup\u003e\u0026Dagger;\u003c/sup\u003e, median [IQR], day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e*Three missing data\u003c/p\u003e \u003cp\u003e\u0026dagger;Defined by glutamate dehydrogenase positivity and \u003cem\u003eClostridium difficile\u003c/em\u003e toxin positivity.\u003c/p\u003e \u003cp\u003e\u0026Dagger;Number of days from ICU admission to the onset of diarrhea\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eIQR: Interquartile range, SOFA: Sequential organ dysfunction assessment, ARDS: Acute respiratory distress syndrome, APACHE II: Acute Physiology and Chronic Health Disease Classification System, SAPS II: Simplified acute physiology score.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between the quantity of diarrhea and outcomes\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the primary and secondary outcomes. Two and 16 patients were lost to 28-day and 90-day follow-ups, respectively. In the unadjusted analysis, the quantity of diarrhea was associated with increased in-hospital mortality (unadjusted RR per 200 g increased: 1.10 [95% CI 1.01\u0026ndash;1.19], p\u0026thinsp;=\u0026thinsp;0.03). After adjusting for CCI, SOFA score, and serum albumin level, this association remained (adjusted RR per 200-g increase: 1.10 [95% CI 1.01\u0026ndash;1.20], p\u0026thinsp;=\u0026thinsp;0.03) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of primary and secondary outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal n\u0026thinsp;=\u0026thinsp;231\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary outcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital mortality, n/total n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53/231 (22.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary outcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU mortality, n/total n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21/231 (9.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28-day mortality*, n/total n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35/229 (15.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e90-day mortality\u003csup\u003e\u0026dagger;\u003c/sup\u003e, n/total n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52/215 (24.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU LOS, median [IQR], day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.0 [4.0, 12.4]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU-free day survival at 28*, median [IQR], day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.0 [14.0, 23.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital LOS, median [IQR], day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.0 [18.4, 58.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital-free day survival at 90\u003csup\u003e\u0026dagger;\u003c/sup\u003e, median [IQR], day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.0 [0, 66.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e*Two patients lost to follow-up, \u0026dagger;16 patients lost to follow-up. There were no missing measurements in other outcomes. IQR: Interquartile range, LOS: Length of stay, IQR: Interquartile range, LOS: Length of stay\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between the quantity of diarrhea and in-hospital mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnadjusted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAdjusted\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRR [95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRR [95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary analysis (per 200-g diarrhea increase)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.10 [1.01, 1.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10 [1.01, 1.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSensitivity analyses (per 200-g diarrhea increase)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.09 [0.98, 1.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10 [1.01, 1.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.11 [1.02, 1.22]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10 [1.00, 1.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete case analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.10 [1.05, 1.15]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u0026gt;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10 [1.04, 1.17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExclude CDI or CMV diagnosed in ICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.10 [1.03, 1.17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14 [1.04, 1.24]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuantile-defined categories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild (\u0026lt;\u0026thinsp;250 g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate (250‒399 g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97 [0.38, 2.49]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02 [0.51, 2.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.963\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere (400‒649 g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.11 [0.46, 2.68]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.29 [0.69, 2.43]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery severe (\u0026ge;\u0026thinsp;650 g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.61 [0.85, 3.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.77 [0.99, 3.21]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003ePrimary model: CCI, SOFA score, and serum albumin, Model 1: age, sex, CCI without age score, SOFA score, and serum albumin. Model 2: CCI, APACHE II score, and serum albumin. Model 3: CCI, SAPS II score, and serum albumin. Model 4: CCI, SOFA score, serum albumin, and enteral nutrition\u003c/p\u003e \u003cp\u003eRR:\u0026nbsp;Risk ratio,\u0026nbsp;CI: Confidence interval,\u0026nbsp;CCI: Charlson comorbidity index, SOFA: Sequential Organ Failure Assessment, CDI: \u003cem\u003eClostridium difficile\u003c/em\u003e infection, CMV: Cytomegalovirus enteritis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eSensitivity analyses for the primary analysis\u003c/h2\u003e \u003cp\u003eThe association between the quantity of diarrhea and in-hospital mortality remained similar in various multivariable analysis models and other sensitivity analyses (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). We also performed a sensitivity analysis using the categories of the quantity of diarrhea. With no established criteria to distinguish the quantity of diarrhea, we used near-quantile-defined categories of the quantity of diarrhea. The quartiles of diarrhea were 230 g in the 25th percentile, 401 g in the 50th percentile, and 645 g in the 75th percentile. Therefore, the patients were divided into the following categories: mild (\u0026lt;\u0026thinsp;250 g), moderate (250\u0026ndash;399 g), severe (400\u0026ndash;649 g), and very severe (\u0026ge;\u0026thinsp;650 g). In-hospital mortality was 19.7% (12/61) for mild, 19.2% (10/52) for moderate, 21.3% (13/61) for severe, and 31.6% (18/57) for very severe. Multivariable-modified Poisson regression analysis using these categories, with the same adjustments as in the primary model, showed a trend toward increased in-hospital mortality as the quantity of diarrhea increased (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003eSecondary analyses\u003c/h2\u003e \u003cp\u003eFor secondary analyses, a similar association was observed between the quantity of diarrhea and ICU 28-day and 90-day mortalities (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Multivariable analysis showed a similar trend of higher mortality with higher quantities of diarrhea.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between 200-g increase in the quantity of diarrhea and secondary outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnadjusted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAdjusted\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRR [95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRR [95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.17 [1.07, 1.29]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.20 [1.07, 1.35]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28-day mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.11 [1.01, 1.23]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.11 [0.99, 1.23]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e90-day mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.10 [1.01, 1.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.11 [1.01, 1.21]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eAll analyses were adjusted for CCI, SOFA score, and serum albumin level. \u003c/p\u003e \u003cp\u003eRR: Risk ratio, CI: Confidence interval, CCI: Charlson comorbidity index, SOFA: Sequential Organ Failure Assessment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this retrospective study, we investigated the association between the quantity of diarrhea and in-hospital mortality in 231 patients with newly developed diarrhea in the ICU. Multivariable analysis revealed that diarrhea quantity was an independent predictor of in-hospital mortality. This association was consistent across several sensitivity analyses. Similarly, the greater the quantity of diarrhea, the higher the ICU 28-day and 90-day mortalities. To the best of our knowledge, this is the first study to show an association between the quantity of diarrhea and mortality.\u003c/p\u003e \u003cp\u003ePrevious studies have reported an association between the presence of diarrhea and mortality; however, no studies have examined whether mortality increases with a greater quantity of diarrhea [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. A systematic review of 12 studies, most of which used the definition of diarrhea as three or more loose or liquid stools, showed an association between diarrhea and mortality (RR: 1.43; 95% CI: 1.03\u0026ndash;1.98; I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;86.7%; n\u0026thinsp;=\u0026thinsp;11,866) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. We focused on the quantity of diarrhea in this study and showed that mortality increased with increasing quantity of diarrhea according to the adjusted RR in patients with newly developed diarrhea in the ICU. More diarrhea leads to worse electrolyte imbalance, nutritional deficit, and hemodynamic instability owing to water loss [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Clinicians need to correct electrolytes, adjust enteral nutrition, and increase fluid administration as diarrhea increases.\u003c/p\u003e \u003cp\u003eThe reason for the higher mortality rate among patients with a greater quantity of diarrhea remains unclear. Patients with CDI or cytomegalovirus enteritis, which are common diseases causing diarrhea, have been reported to have higher mortality, but they were excluded from our study. Indeed, diarrhea can cause dehydration, electrolyte abnormalities, metabolic acidosis, malnutrition, device contamination, and wound contamination [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, since dehydration and electrolyte abnormalities are carefully corrected in the ICU, it is questionable to assume that diarrhea directly contributes to mortality.\u003c/p\u003e \u003cp\u003ePossible explanations for the relationship between diarrhea and mortality are as follows. First, diarrhea can be a sign of gastrointestinal organ failure that is associated with a high risk of mortality [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Patients with diarrhea have higher severity scores than those without diarrhea [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In our study, most patients received treatments that could cause diarrhea, such as enteral nutrition and antimicrobials. These interventions are part of the treatment regimen for critically ill patients. In addition, approximately 60% of patients were on ventilation and used vasopressors, which means that patients with diarrhea have a higher severity of illness. In our analysis, we adjusted for the SOFA score, an organ disorder score that does not include gastrointestinal function and showed that diarrhea is a risk factor for mortality independent of other organ disorders. The quantity of diarrhea may be a candidate when adjusting for organ dysfunction. Second, diarrhea can be a sign of a disorder of the gut microbiota, which is called dysbiosis. This dysbiosis is believed to increase vulnerability to nosocomial infections, sepsis, organ failure, and mortality [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The development of diarrhea might be associated with dysbiosis in the gut microbiota of ICU patients [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. However, our data and analyses are not sufficiently conclusive to prove them. Further research is needed to test these hypotheses.\u003c/p\u003e \u003cp\u003eThis study had several limitations. First, the measurement of diarrhea was not completely accurate. If diarrhea spills out of the diaper, it may not be measured. In this case, this may have led to an underestimation of the quantity of diarrhea. However, we believe that this measurement of the quantity of diarrhea reflects real clinical practice. Second, the inter-rater reliability of BSCS was not confirmed in our study. The reliability of BSCS has been studied and widely used [\u003cspan additionalcitationids=\"CR27 CR28 CR29 CR30 CR31\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], and our nurses were trained to measure BSCS in clinical practice, which should have minimized the inter-rater variability. Third, we did not obtain information on urinary catheter insertion. However, we expect that most patients in this study had urinary catheters because only critically ill patients were admitted to our ICU (a median SOFA score of 9 and 63.6% of them were on ventilators). Finally, this was a single-center study, and the generalizability of the results is limited.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn ICU patients with newly developed diarrhea, greater quantity of diarrhea was associated with higher mortality. The quantity of diarrhea may be considered an indicator of disease severity in ICU patients. Further research is needed to determine if there is a causal relationship between the quantity of diarrhea and death.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntensive care unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRisk ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eESICM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEuropean Society of Intensive Care Medicine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCDI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eClostridium difficile\u003c/em\u003e infection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCMV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCytomegalovirus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSTROBE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStrengthening the Reporting of Observational studies in Epidemiology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBSCS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBristol stool chart scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCharlson Comorbidity Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAPACHE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcute Physiology and Chronic Health Evaluation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSAPS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSimplified Acute Physiology Score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSOFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSequential Organ Failure Assessment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved, and the need for informed consent was waived by the institutional review boards of the participating hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset of this study is not publicly available based on the decision of the first author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRY has complete access to the study data and takes responsibility for the data integrity. All authors contributed to the study concept and design. RY and YU contributed to data acquisition. RY and RU contributed to\u0026nbsp;data\u0026nbsp;analysis and interpretation. RY, RU, and HY drafted the manuscript. All authors are responsible for the critical revision of the manuscript for important intellectual content and\u0026nbsp;have\u0026nbsp;approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the staff of the ICU of the Kameda Medical Center. We thank the Japanese Society of Education for Physicians and Trainees in the Intensive Care Clinical Trial Group for their suggestions and comments on the earlier concept of this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eReintam Blaser A, Deane AM, Fruhwald S. Diarrhoea in the critically ill. Curr Opin Crit Care. 2015;21(2):142\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThibault R, Graf S, Clerc A, Delieuvin N, Heidegger C, Pichard C. Diarrhoea in the ICU: respective contribution of feeding and antibiotics. Crit Care. 2013;17(4):R153.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReintam Blaser A, Malbrain MLNG, Starkopf J, Fruhwald S, Jakob SM, De Waele J, et al. Gastrointestinal function in intensive care patients: terminology, definitions and management. Recommendations of the ESICM Working Group on Abdominal Problems. Intensive Care Med. 2012;38(3):384\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReintam A, Parm P, Kitus R, Kern H, Starkopf J. Gastrointestinal symptoms in intensive care patients. Acta Anaesthesiol Scand. 2009;53(3):318\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiesmayr M, Schindler K, Pernicka E, Schuh C, Schoeniger-Hekele A, Bauer P, et al. Decreased food intake is a risk factor for mortality in hospitalised patients: the NutritionDay survey 2006. Clin Nutr. 2009;28(5):484\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorges SL, Pinheiro BDV, Pace FHDL, Chebli JMF. Diarr\u0026eacute;ia nosocomial em unidade de terapia intensiva: incid\u0026ecirc;ncia e fatores de risco. Arq Gastroenterol. 2008;45(2):117\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOzgur M, Girgin NK, Akalin H, Iscimen R, Sinirtas M, Kahveci F. A retrospective evaluation of the incidence and risk factors of nosocomial diarrhea in critically ill adult patients. Acta Medica. 2016;32:741\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTirlapur N, Puthucheary ZA, Cooper JA, Sanders J, Coen PG, Moonesinghe SR, et al. Diarrhoea in the critically ill is common, associated with poor outcome and rarely due to Clostridium difficile. Sci Rep. 2016;6(1):24691.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu TJ, Liu ZJ, Zhao YM, Yang CL, Zhang CY. [Clinical analysis of the factors related to diarrhea in intensive care unit]. Zhongguo Wei Zhong Bing Ji Jiu Yi Xue. 2004;16(12):747\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJakob SM, B\u0026uuml;tikofer L, Berger D, Coslovsky M, Takala J. A randomized controlled pilot study to evaluate the effect of an enteral formulation designed to improve gastrointestinal tolerance in the critically ill patient\u0026mdash;the SPIRIT trial. Critical Care. 2017;21(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVieira LV, Pedrosa LAC, Souza VS, Paula CA, Rocha R. Incidence of diarrhea and associated risk factors in patients with traumatic brain injury and enteral nutrition. Metab Brain Dis. 2018;33(5):1755\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRodrigues de Barros J, Fraga Lobo IM, Melo Soares F, Ferreira de Almeida DSS. Factors associated with diarrhea in a unit of intensive therapy: cohort study. NUTRICION CLINICA Y DIETETICA HOSPITALARIA. 2018;38(2):122\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAtasever AG, Ozcan PE, Kasali K, Abdullah T, Orhun G, Senturk E. The frequency, risk factors, and complications of gastrointestinal dysfunction during enteral nutrition in critically ill patients. Ther Clin Risk Manag. 2018;14:385\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaito S, Kawai Y, Liu K, Ariie T, Tsujimoto Y, Banno M, et al. Diarrhea and patient outcomes in the intensive care unit: Systematic review and meta-analysis. J Crit Care. 2019;53:142\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAltman DG, Royston P. The cost of dichotomising continuous variables. BMJ. 2006;332(7549):1080.1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDawson NV, Weiss R. Dichotomizing Continuous Variables in Statistical Analysis. Med Decis Making. 2012;32(2):225\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWierdsma NJ, Peters JH, Weijs PJ, Keur MB, Girbes AR, Van Bodegraven AA, et al. Malabsorption and nutritional balance in the ICU: fecal weight as a biomarker: a prospective observational pilot study. Crit Care. 2011;15(6):R264.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnigilaje EA. Management of Diarrhoeal Dehydration in Childhood: A Review for Clinicians in Developing Countries. Front Pediatr. 2018;6:28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVon Elm E, Altman DG, Egger M, Pocock SJ, G\u0026oslash;tzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting Observational Studies. Ann Intern Med. 2007;147(8):573.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDiarrhoeal disease 2017 [updated 2. May 2017. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/en/news-room/fact-sheets/detail/diarrhoeal-disease\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeymour CW, Liu VX, Iwashyna TJ, Brunkhorst FM, Rea TD, Scherag A, et al. Assessment of Clinical Criteria for Sepsis. JAMA. 2016;315(8):762.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCharlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKnaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13(10):818\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLe Gall JR, Lemeshow S, Saulnier F. A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study. Jama. 1993;270(24):2957\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVincent JL, Moreno R, Takala J, Willatts S, De Mendon\u0026ccedil;a A, Bruining H, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22(7):707\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Donnell LJ, Virjee J, Heaton KW. Detection of pseudodiarrhoea by simple clinical assessment of intestinal transit rate. BMJ. 1990;300(6722):439\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLacy BE, Mearin F, Chang L, Chey WD, Lembo AJ, Simren M, et al. Bowel Disorders Gastroenterology. 2016;150(6):1393 \u0026ndash; 407.e5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCook DJ, Johnstone J, Marshall JC, Lauzier F, Thabane L, Mehta S, et al. Probiotics: Prevention of Severe Pneumonia and Endotracheal Colonization Trial\u0026mdash;PROSPECT: a pilot trial. Trials. 2016;17(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoh H, Lee MJ, Kim MJ, Shin JI, Chung KS. Simple diagnostic approach to childhood fecal retention using the Leech score and Bristol stool form scale in medical practice. J Gastroenterol Hepatol. 2010;25(2):334\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDionne JC, Sullivan K, Mbuagbaw L, Takaoka A, Duan EH, Alhazzani W, et al. Diarrhoea: interventions, consequences and epidemiology in the intensive care unit (DICE-ICU): a protocol for a prospective multicentre cohort study. BMJ Open. 2019;9(6):e028237.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaroff DA, Edelstein PH, Hamilton K, Pegues DA. The Bristol Stool Scale and Its Relationship to Clostridium difficile Infection. J Clin Microbiol. 2014;52(9):3437\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLewis SJ, Heaton KW. Stool Form Scale as a Useful Guide to Intestinal Transit Time. Scand J Gastroenterol. 1997;32(9):920\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBishop S, Young H, Goldsmith D, Buldock D, Chin M, Bellomo R. Bowel motions in critically ill patients: a pilot observational study. Crit Care Resusc. 2010;12(3):182\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchmidt SB, Kulig W, Winter R, Vasold AS, Knoll AE, Rollnik JD. The effect of a natural food based tube feeding in minimizing diarrhea in critically ill neurological patients. Clin Nutr. 2019;38(1):332\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgus MSD, Wypij D, Hirshberg EL, Srinivasan V, Faustino EV, Luckett PM, et al. Tight Glycemic Control in Critically Ill Children. N Engl J Med. 2017;376(8):729\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSelf WH, Semler MW, Wanderer JP, Wang L, Byrne DW, Collins SP, et al. Balanced Crystalloids versus Saline in Noncritically Ill Adults. N Engl J Med. 2018;378(9):819\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZou G. A Modified Poisson Regression Approach to Prospective Studies with Binary Data. Am J Epidemiol. 2004;159(7):702\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHolmberg MJ, Andersen LW. Estimating Risk Ratios and Risk Differences. JAMA. 2020;324(11):1098.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRubin DB. Multiple imputation for nonresponse in surveys. John Wiley \u0026amp; Sons; 2004.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGroothuis-Oudshoorn K, Van Buuren S. Mice: multivariate imputation by chained equations in R. J Stat Softw. 2011;45(3):1\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWasserstein RL, Lazar NA. The ASA Statement on p-Values: Context, Process, and Purpose. The American Statistician. 2016;70(2):129\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLebak KJ, Bliss DZ, Savik K, Patten-Marsh KM. What's New on Defining Diarrhea in Tube-Feeding Studies? Clinical Nursing Research. 2003;12(2):174\u0026ndash;204.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReintam Blaser A, Poeze M, Malbrain MLNG, Bj\u0026ouml;rck M, Oudemans-Van Straaten HM, Starkopf J. Gastrointestinal symptoms during the first week of intensive care are associated with poor outcome: a prospective multicentre study. Intensive Care Med. 2013;39(5):899\u0026ndash;909.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKitsios GD, Morowitz MJ, Dickson RP, Huffnagle GB, McVerry BJ, Morris A. Dysbiosis in the intensive care unit: Microbiome science coming to the bedside. J Crit Care. 2017;38:84\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcdonald D, Ackermann G, Khailova L, Baird C, Heyland D, Kozar R, et al. Extreme Dysbiosis of the Microbiome in Critical Illness mSphere. 2016;1(4):e00199-16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuan J, Meng X, Liu S, Zhou P, Zeng C, Fu C, et al. Gut Microbiota Composition Associated With Clostridium difficile-Positive Diarrhea and C. difficile Type in ICU Patients. Frontiers in Cellular and Infection Microbiology. 2020;10.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"intensive care, diarrhea, mortality, retrospective cohort study ","lastPublishedDoi":"10.21203/rs.3.rs-859799/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-859799/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePrevious studies have shown that diarrhea is associated with increased mortality of patients in intensive care units (ICUs). However, these studies used dichotomized cutoff values, even if diarrhea was a continuous condition. This study aimed to assess the association between diarrhea quantity and mortality in ICU patients with newly developed diarrhea.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted this single-center retrospective cohort study at the Kameda Medical Center ICU. We consecutively included all adult ICU patients with newly developed diarrhea in the ICU between January 2017 and December 2018. Newly developed diarrhea was defined based on a Bristol stool chart scale\u0026thinsp;\u0026ge;\u0026thinsp;6 and frequency of diarrhea\u0026thinsp;\u0026ge;\u0026thinsp;3 times per day. We excluded patients who already had diarrhea on the day of ICU admission among other criteria. We collected data on the quantity of diarrhea on the day when patients newly developed diarrhea. The primary outcome was in-hospital mortality. The risk ratio (RR) and 95% confidence interval (CI) for the association between the quantity of diarrhea and mortality were estimated using multivariable-modified Poisson regression models adjusted for the Charlson Comorbidity Index, sequential organ failure assessment score, and serum albumin levels.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 231 participants, 68.4% (158/231) were men; the median age of the patients was 72 years. The median quantity of diarrhea was 401 g (interquartile range [IQR] 230‒645 g), and in-hospital mortality was 22.9% (53/231). More diarrhea at baseline was associated with higher in-hospital mortality; the unadjusted RR (95% CI) per 200-g increase was 1.10 (1.01‒1.19). This association remained in the multivariable-adjusted analysis; the adjusted RR (95% CI) per 200-g increase was 1.10 (1.01‒1.20).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eA greater quantity of diarrhea was an independent risk factor for in-hospital mortality. The quantity of diarrhea may be an indicator of disease severity in ICU patients.\u003c/p\u003e","manuscriptTitle":"Association between diarrhea quantity and in-hospital mortality in intensive care unit patients: A retrospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-09-02 15:28:29","doi":"10.21203/rs.3.rs-859799/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bb1bd40d-5da7-49b2-9f4e-7c60e196a9f7","owner":[],"postedDate":"September 2nd, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":6894849,"name":"Critical Care \u0026 Emergency Medicine"},{"id":6894850,"name":"Molecular Epidemiology"}],"tags":[],"updatedAt":"2021-09-02T15:28:30+00:00","versionOfRecord":[],"versionCreatedAt":"2021-09-02 15:28:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-859799","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-859799","identity":"rs-859799","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}