Regional differences and mortality-associated risk factors among older patients with septic shock: Administrative data analysis with multilevel logistic regression modeling

Regional differences and mortality-associated risk factors among older patients with septic shock: Administrative data analysis with multilevel logistic regression modeling | 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 article Regional differences and mortality-associated risk factors among older patients with septic shock: Administrative data analysis with multilevel logistic regression modeling Shinichiro Yoshida, Akira Babazono, Ning Liu, Reiko Yamao, Reiko Ishihara, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2148391/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 Older patients with septic shock are generally difficult to treat, have poor outcomes because of frailty and vulnerability, and may be highly sensitive to the quality of clinical care. Therefore, differences in treatment that arise from variations in intensive care unit (ICU) policies and each physician may influence mortality. We hypothesized that regional variability exists in mortality among older patients with septic shock, and investigated mortality-associated factors. Methods Administrative medical claims data were analyzed; participants were enrolled from April 2015 to March 2020. In Japan, engagement of at least one ICU physician exclusively at the ICU is a mandatory requirement to claim governmental incentive. In this study, ICU physicians were differentiated as “intensivist” and “ICU-dedicated physician” based on whether they were board-certified or not, respectively, in intensive care medicine. The primary outcome was the 28-day mortality after ICU admission. Data from nine secondary medical areas with ICU facilities were analyzed. We calculated and compared the 28-day mortality by each area. To adjust for patient characteristics and hospital profiles, multilevel logistic regression analyses were conducted. Results Among our 1,238 participants, mortality varied from 18.3–41.4% across nine areas. Based on multilevel logistic analyses, the model including variables on patient characteristics and hospital profiles was best-fitted, and these variables did not vary significantly across the nine areas. Age group, post-surgical admission, and the number of ICU beds per intensivist were significantly associated with mortality. The adjusted odds ratio for the ratio of ICU beds to intensivist was 2.25 (95% CI [1.36–3.72], p < 0.01), compared with no intensivist versus one or more intensivists for four ICU beds. Conclusions Regional mortality variability of older patients with septic shock was ascertained through our analysis. Mortality may be influenced by whether the ICU physicians are board-certified in intensive care medicine. To ensure quality care of older patients with septic shock, standard criteria, similar to those applied to intensivists, should be considered and applied to ICU physicians. Intensive care unit Septic shock Older adults Mortality Regional variability Board-certified intensivist Figures Figure 1 Background The treatment of septic shock necessitates clinical experience and knowledge as well as multidisciplinary care. Therefore, septic shock is a critical illness wherein the outcome represents the quality of the intensive care that is provided [ 1 ]. Septic shock-related mortality remains high, despite decreasing over the past several years [ 2 – 4 ], especially in older patients [ 5 , 6 ]. Closed intensive care unit (ICU) management and high-intensity intensivist consultation may contribute to an improved mortality risk in septic shock [ 7 – 11 ]. However, variability in septic shock mortality has been reported. For example, physician staffing [ 7 , 12 , 13 ], ICU admission rate [ 14 ], racial and ethnic minority status [ 15 – 17 ], and insurance type [ 18 ] are factors that are associated with septic shock mortality. These settings are difficult to fully optimize across hospitals; therefore, septic shock mortality could differ by hospital and by region. The proportion of the older population is increasing in most developed countries, especially in Japan and European countries. Worldwide, tools for early recognition of sepsis and recent advances in the treatment of septic shock increase the possibility of treatment for older patients with septic shock; however, studies that investigated and reported septic shock mortality have rarely been focused on the older population. We hypothesized that regional variability in septic shock mortality exists and occurs because of unreported hospital characteristic measures, such as the number of beds per board-certified intensivist. This study involved a descriptive data analysis of the mortality risk in older patients with septic shock with the aim to examine regional differences in septic shock mortality. Methods Study design and participants We conducted a retrospective open cohort study by using the administrative claims data of older patients who were beneficiaries of Fukuoka Prefecture Wide-Area Association of Latter-Stage Elderly Healthcare, Japan. In 2018, this health insurance program covered approximately 606,000 individuals, or approximately 95% of residents aged 75 years or more in the Fukuoka Prefecture (Additional Table 1 ). Basically, all individuals aged 75 years or over are insured. Individuals aged 65 to 74 years, who have a specific disability, are also insured. We screened patients (age ≥ 75 years) who were admitted from April 2015 to March 2020 to 35 ICUs with the disease name and diagnostic code of sepsis that are used for health insurance claims in Japan. We identified eligible patients by using codes that included the terms “sepsis” or “septic” (Additional Table 2 ). We included only patients with any vasopressor or antibiotic use during ICU admission and who were admitted to the ICU for more than 1 day. To ensure accurate data collection, we excluded the data of patients who lost qualification for health insurance for a reason other than death (e.g., change in residence to outside Fukuoka Prefecture), as well as records of the second or later ICU admissions, in case of multiple admissions for septic shock. Data on hospitalization in areas outside the Fukuoka Prefecture were excluded. Table 1 Comparison of the participants’ characteristics and treatments Variable Secondary Medical Area 1 2 3 4 5 6 7 8 9 p N 295 29 41 70 186 20 157 372 68 Age, y (median, IQR) 83 (9) 84 (10) 84 (6) 83.5 (8) 83 (8) 86 (7) 84 (8) 83 (8) 83 (7) 0.20 Sex, male (%) 57.3 65.5 53.7 48.6 60.8 50 53.5 55.1 48.5 0.55 CCI, median (IQR) 2 (2) 2 (3) 1 (2) 2 (2) 2 (2) 0 (2.5) 2 (2) 2 (2) 2 (2) 0.88 Postoperative (%) 30.5 44.8 31.7 45.7 41.4 35 34.4 42.2 25 0.01* Vasopressor use (%) Noradrenaline 84.4 82.8 70.7 82.9 82.8 65 91.7 86.8 83.9 0.02* Vasopressin 5.4 3.5 2.4 1.4 22 0 49.7 8.1 17.7 < 0.01* Dopamine 54.6 55.2 63.4 31.4 31.2 55 21.7 38.2 36.8 < 0.01* Adrenaline 6.8 6.9 4.9 7.1 9.1 5 15.9 11.6 8.8 0.09 Antibiotic use (%) Carbapenems 64.4 65.5 58.5 58.6 54.3 25 75.2 53.2 48.5 < 0.01* Anti-MRSA agents** 9.2 10.3 2.4 4.3 18.8 5 32.5 12.6 8.8 < 0.01* IQR, interquartile range; CCI, Charlson Comorbidity Index; MRSA, methicillin-resistant Staphylococcus aureus * p < 0.05. **Anti-MRSA agents include vancomycin, teicoplanin, daptomycin, and linezolid. Table 2 Mortality rates in the secondary medical areas Secondary medical area n 28-Day mortality (%) OR (95% CI) SE Z-score p 1 295 32.2 2.12 (1.36–3.31) 0.482 3.32 < 0.01* 2 29 41.4 3.16 (1.38–7.22) 1.332 2.72 < 0.01* 3 41 31.7 2.08 (0.98–4.42) 0.800 1.89 0.06 4 70 25.7 1.55 (0.81–2.97) 0.515 1.31 0.19 5 186 18.3 Reference 6 20 40.0 2.98 (1.13–7.85) 1.473 2.21 0.03* 7 157 22.9 1.33 (0.79–2.25) 0.357 1.06 0.29 8 372 33.6 2.26 (1.47–3.48) 0.496 3.73 < 0.01* 9 68 38.2 2.77 (1.50–5.12) 0.868 3.25 < 0.01* OR, odds ratio; SE, standard error; CI, confidence interval * p < 0.05. ICU admission was identified by detecting the reimbursement of a specialized intensive care management (SICM) fee (here, “specialized” does not refer to specific diseases such as stroke and acute coronary syndrome). This study was approved by the Institutional Review Board of Kyushu University (Clinical Bioethics Committee of the Graduate School of Medical Sciences, Kyushu University [approved no. 2021 − 335]), which waived the requirement of informed consent for this noninterventional study because information from an anonymized dataset was analyzed. ICU settings in Japan Hospitals can submit claims for the SICM fee as an incentive for a specially organized department if their ICU meets the specific government-stipulated conditions. Two types of SICM fee broadly exist: ordinary and superior, which are referred to as “standard ICU” and “resource-rich ICU,” respectively [ 19 ]. The aforementioned conditions include full-time availability of in-house dedicated physicians in the ICU and an ICU bed/nurse ratio ≤ 2. Moreover, in each ICU, the number of cases that need to be monitored, procedures, and devices for life support must be accounted for in ≥ 70% of all ICU cases. However, the superior type of SICM fee is designed to provide aggressive treatment by adding sufficient human resources to ensure the previously mentioned conditions. More specifically, two or more ICU physicians with experience in intensive care medicine for 5 years or more must be dedicatedly assigned to ICU services, an in-house clinical engineer should be available at all times, and an experienced nurse who has completed the given intensive care course must be dedicated to ICU nursing for at least 20 hours per week. For ICU physicians at a hospital that claims the ordinary type of SICM fee, specific specialty and clinical careers in intensive care are not required. For both types of SICM fee, the specialties of the ICU physician’s background, which popularly include anesthesiology, emergency medicine, cardiovascular medicine/surgery, neurology/neurosurgery, and abdominal surgery, are not required in Japan. In our study, we refer to only ICUs that can claim the SICM fee, although ICUs exist which do not claim the SICM fee. Board certification in intensive care medicine in Japan is administered only by Japanese Society of Intensive Care Medicine (JSICM). However, whether an ICU physician is a board-certified by the JSICM is not an eligibility requirement for the SICM fee. Therefore, some ICUs have ICU-dedicated physicians who are not board-certified in intensive care medicine by the JSICM. Neither unit format nor consultation intensity (e.g. closed/open ICU and high/low-intensity consultation to intensivist) are required for the SICM fee. Although we did not investigate ICU format and intensity, we used the JSICM-board-certified physician list to accurately ascertain the number of JSICM-board-certified physicians at each hospital. In this study, “intensivist” indicates a physician with JSICM-board-certification in intensive care and “ICU-dedicated physician” refers to ICU physicians without a JSICM certification in intensive care; whereas “ICU physician” refers to both. Regional and hospital profiles The Japanese government defines a secondary medical area (SMA) as a designated area wherein residents of that area can receive complete conventional inpatient care, based on geographical area, population, and hospital distribution. Fukuoka Prefecture has 13 SMAs, of which 4 SMAs do not have any hospitals that are allowed to claim the SICM fee; therefore, we included 9 SMAs in this study. Four academic hospitals are in 3 SMAs, and 10 tertiary emergency medical centers are in 5 SMAs, all of which have an ICU with SICM fee-reimbursement eligibility. The number of hospital beds in this study ranged from 150 beds to 1275 beds, as described in the Report on Medical Functions of Hospital Beds in Fukuoka Prefecture [ 20 ]. Primary outcome and study variables The primary outcome was the 28-day mortality after ICU admission. To quantify mortality variations that are attributable to a patient’s characteristics or hospital profiles, we employed multilevel logistic analysis, after conducting univariate and multivariate analyses. Age, sex, year of admission, and the Charlson Comorbidity Index (CCI) were recorded as the patients’ characteristics. Patients in whom surgical procedures were performed within 7 days preceding an ICU admission were recorded as a case of postoperative admission. Hospital location, the number of beds and proportion of ICU beds within each hospital, the ICU bed-to-intensivist ratio, and type of SICM fee were investigated in the hospital profile. Statistical analysis We compared the participants’ characteristics for each SMA. For variables recorded as dichotomous measures, the chi-square test was performed to examine regional differences. The Kruskal–Wallis test was performed for continuous variables. Mortality was compared, using odds ratios, by performing univariate logistic regression analysis with the SMA term as the explanatory variable. We were concerned that more severely ill patients may be treated at specific hospitals such as ICUs in university hospitals. Moreover, ICU physicians in regions that are geographically distant from each other may not treat patients in the same manner because they are likely to be trained at different educational facilities such as university hospitals, which have different interests. To address potential biases, we examined the variance at the hospital or regional level with multivariate logistic regression analysis by using multilevel modeling. The null model included no variables, Model 1 included participant characteristics, and Model 2 included Model 1 variables and the hospital profiles. The Z-score, which suggests the significance of variance in each model and the necessity of multilevel analysis, was calculated. The Z-score was calculated by dividing the variance estimate by the estimated standard error. When the Z-score is > 2, the variables included in the model may have a contextual effect. Therefore, multilevel analysis was employed. However, if the Z-score is < 2, multilevel logistic analysis is suitable for statistical analysis. Furthermore, the median odds ratio (MOR) was calculated for quantifying variation or heterogeneity in outcomes between clusters by using the between-cluster variance; a higher MOR indicates a greater contextual effect of the model, whereas a MOR close to 1 implies very small inter-cluster variability of outcomes. All analyses were performed by using Stata/IC 14 (StataCorp, College Station, TX, USA). All reported p -values were two-tailed, and the level of significance was set at p < 0.05. Results We identified 2,658 patients who were diagnosed with sepsis and had received vasopressors and antibiotics. However, after excluding patients because of insurance qualification, hospital location, short ICU stay, and missing data, we included the data from 1,238 patients in the final analysis (Fig. 1 ). Regional differences in postoperative admission, medication usage, and clinical outcome were identified (Tables 1 and 2 ). The 28-day mortality after ICU admission ranged from 18.3–41.4% across SMAs (Table 2 ). The Z-scores in the multilevel logistic regression analysis showed that multilevel modeling did not differ significantly from that of the multivariable logistic model (Table 3 ). This finding suggested that explanatory variables pertaining to the patients’ characteristics and hospital profiles in this study may not vary across SMAs. Furthermore, the MOR (approximately 1.0) implied homogeneity among these variables. Based on the log likelihood results, the full variable model (i.e., Model 2) was the best-fitted model among the three models. In Model 2, the 28-day mortality after ICU admission was significantly influenced by the age group, sex, postoperative admission, and the number of ICU beds per intensivist (Table 3 ). Table 3 Results of multilevel logistic regression analysis on regional variations Variable Univariate Multivariate OR (95% CI) P AOR (95% CI) p Age group, y 75–79 Reference Reference 80–84 1.20 (0.86–1.66) 0.29 1.28 (0.91–1.79) 0.16 85–89 1.39 (0.99–1.94) 0.06 1.49 (1.05–2.11) 0.02* ≥ 90 1.56 (1.05–2.32) 0.03* 1.86 (1.23–2.83) < 0.01* Sex Male Reference Reference Female 0.77 (0.60–0.98) 0.04* 0.73 (0.56–0.94) 0.02* Fiscal year 2015 Reference Reference 2016 1.03 (0.70–1.52) 0.87 1.09 (0.73–1.63) 0.66 2017 1.09 (0.74–1.60) 0.68 1.15 (0.77–1.71) 0.50 2018 0.87 (0.59–1.28) 0.47 0.87 (0.59–1.29) 0.50 2019 1.01 (0.69–1.50) 0.95 1.09 (0.73–1.62) 0.68 CCI Mild Reference Reference Moderate 1.07 (0.84–1.36) 0.61 1.09 (0.85–1.41) 0.49 Severe 1.09 (0.33–3.59) 0.89 1.30 (0.38–4.41) 0.68 Procedure Postoperative 0.63 (0.48–0.81) < 0.01* 0.62 (0.47–0.81) < 0.01* Number of hospital beds ≥ 400 Reference Reference < 400 1.08 (0.84–1.38) 0.57 0.82 (0.59–1.15) 0.26 Proportion of ICU beds to hospital beds 4 1.18 (0.75–1.85) 0.47 1.41 (0.84–2.36) 0.20 No certified physician 1.64 (1.06–2.53) 0.03* 2.25 (1.36–3.72) < 0.01* Type of SICM fee Expensive Reference Reference Ordinary 1.06 (0.81–1.37) 0.69 0.81 (0.57–1.16) 0.25 OR, odds ratio; CI, confidence interval; AOR, adjusted odds ratio; CCI, Charlson Comorbidity Index; ICU, intensive care unit; SICM, specialized intensive care management * p < 0.05. Table 4 Results of the multilevel logistic regression analyses Null model Model 1 Model 2 Level Estimate (95% CI) Estimate (95% CI) Estimate (95% CI) Log likelihood −747.96 −734.35 −729.94 Variance SMA 0.06 (0.01–0.44) 0.05 (0.01–0.51) 0.03 (0.00–0.50) Hospital 0.03 (0.00–0.43) 0.04 (0.00–0.42) 0.01 (0.00–17.07) Z-score SMA 0.97 0.85 0.66 Hospital 0.76 0.86 0.26 ICC SMA 0.02 (0.00–0.12) 0.02 (0.00–0.13) 0.01 (0.00–0.13) Hospital 0.03 (0.01–0.09) 0.03 (0.01–0.09) 0.01 (0.00–0.07) MOR SMA 1.26 (1.09–1.88) 1.24 (1.07–1.97) 1.16 (1.04–1.97) Hospital 1.19 (1.05–1.87) 1.22 (1.07–1.86) 1.10 (1.00–51.44) PCV (%) SMA Reference 13.90 56.31 Hospital Reference −35.35 71.04 CI, confidence interval; SMA, secondary medical area; ICC, intraclass correlation coefficient; MOR, median odds ratio; PCV, proportional change in variance Discussion Older patients with septic shock have poor outcomes because of frailty and the severity of organ failure [ 2 , 5 , 6 ], and are likely to be highly sensitive to the quality of care. We proved our hypothesis of regional mortality variability among older patients with septic shock, which varied across regions, which was potentially attributable mortality-associated factors, including sex, being a nonsurgical patient, and the ICU bed-to-intensivist ratio. The results of multilevel analysis showed that the contextual effect in an SMA or in hospitals was small; therefore, the impact of variations in patient characteristics among our study clusters (i.e. SMA and hospitals) was too small to ascertain mortality variation. However, the intraclass correlation coefficients in Model 2 decreased to less than one-half of that in the null model, when controlling for hospital profiles. In particular, the intensivist density for ICU beds significantly influenced mortality. The present study included two types of ICU physicians: JSICM-board-certified intensivists and ICU-dedicated physicians. Intensivists in Japan must regularly satisfy the requirements for revalidation of their certification every 5 years by attaining some achievements such as conducting research activity, participating in learning sessions, and instructing trainees with regard to intensive care medicine. ICU-dedicated physicians do not have any requirement for maintaining the accreditation of the SICM fee, and ICU-dedicated physicians have an uncertain training history and an uncertain updating of knowledge and skills with regard to intensive care. Physicians without board certification but with a greater ability for intensive care realistically exist; however, our study clearly revealed the advantage of board-certified intensivists for older patients with septic shock. Our results suggest that some potential weaknesses exist in the definition of ICU physician for the reimbursement of intensive care management in Japan. After ICU physicians are approved by the government in the context of approval of the application for reimbursement of the SICM fee, ICU physicians are not usually required to undergo cumulative activities after approval, unlike the requirement to maintain JSICM certification. Our findings may reflect the importance of regularly updating knowledge and skills of ICU physicians. Furthermore, based on the findings, we recognize that commonality across subspecialties needs to be considered to enable the intensivist to provide appropriate critical care without resorting to specialty-biased decision-making [ 21 ]. Increasing the number of trained intensivists remains challenging due to the time, cost, and effort involved; however, regular accreditation of ICU physicians, based on specific criteria similar to those used for certification of intensivists, should be considered to ensure that adequately trained physicians can assure good quality sepsis care. Another concern about the weakness of ICU-dedicated physicians is the intensity of commitment to ICU patients. ICU physicians are permitted to provide the clinical practices of their own specialty, in addition to providing intensive care within an ICU, as long as the ICU physicians are in the ICU ward. Thus, even ICU-dedicated physicians may limit their involvement with ICU patients because of their duties in their own specialty, especially in the situation of an open ICU format in which attending physicians primarily commit to an ICU patient. As mentioned later, to improve the outcomes of older patients with septic shock, sufficient commitment of the ICU physician to a patient or attending physicians is highly desirable. Recent studies [ 13 , 22 , 23 ] have shown that a closed ICU format and night-time staffing of intensivists were not necessarily beneficial for patients’ outcomes after ICU admission. However, particularly in septic shock treatment, a higher ratio of patients to intensivist and the lack of the availability of intensivists during the night may be associated with poor outcomes [ 13 , 24 ]. One study [ 25 ] indicated that the case volume may have a positive effect on improving the outcome of septic shock. Additionally, in view of our findings, the intensity of commitment by intensivists is likely to remain important in the treatment of older patients with septic shock. Moreover, increasing the number of intensivists should be considered, based on the number of patients. This finding is consistent with the results of a study [ 26 ] that showed that the number of intensivists per bed was associated with the efficiency of an ICU. A previous study [ 27 ] on patient-to-intensivist ratios reported that a positive effect on mortality is optimized at 7.5. This value was obtained from a case-mix population and may have been modified by the number of board-certified intensivists in older patients with septic shock. In the present study, we stratified the cohort with a four bed/intensivist ratio to enable the analysis of a comparable number of hospitals. A lower ICU bed-to-intensivist ratio seems to improve septic shock outcomes. However, the aforementioned strategy is not necessarily advantageous from the perspective of the case volume effect [ 27 ]. To optimize efficiency and improve septic shock outcomes, regionalization and centralization of intensivists should be considered [ 28 ]. Some researchers have reported results that reflect the diversity of proficiency among ICU physicians and the extent of training in intensive care, and these need to be demonstrated by an appropriate approach [ 7 , 29 ]. As heterogeneity in ICU physicians has not been considered in most studies that have examined outcome variations in critically ill patients, the results potentially reflect the intensivist attribution and should be interpreted with caution when applying this study’s findings to ICU management policy. Our study population has some strengths in selection, compared to other studies. For example, in Japan, most older residents were universally covered by social insurance. Therefore, disparities due to insurance plans are smaller than those of studies in other countries. Moreover, the Japanese population has small racial differences. However, our study had several limitations because we used administrative data. First, we could not collect data on the laboratory tests, vital signs, and physical examination findings, or information about the stage of septic shock on ICU admission. However, we rigorously selected the study population to address these weaknesses. For example, vasopressors and antibiotics, in addition to a diagnosis of sepsis, were essential for patient enrollment. The aforementioned agents are likely to be used by any physician who decides to treat a patient, regardless of whether the ICU physician is an intensivist. Moreover, we could not calculate severity scores such as the Sequential Organ Failure Assessment (SOFA) score and Acute Physiology and Chronic Health Evaluation 2 (APACHE 2) score. In this study, the CCI was used as a substitute for measures that may reflect severity and exacerbation of sepsis. The CCI could predict mortality in ICU patients to a similar extent as a physiology-based score such as the Simplified Acute Physiology Score 2 (SAPS 2). [ 30 ]. Second, we have no data on limitations in life-sustaining treatment. We considered circumstances, including those wherein the patient refused any treatment just before or after ICU admission, or the physicians proposed the withdrawal of invasive treatment because they judged that the patient was too severely ill to survive. These patients and patients with mild symptoms potentially distort the evaluation for quality of care because the patient does not receive sufficient treatment for evaluation. To address this problem, we excluded patients who were discharged from the ICU within 1 day. Third, we could not ascertain how ICU physicians provide clinical services in the ICU. This perspective includes a combination of intensity and unit format, total number of ICU physicians, and staffing. No nationwide hospital survey has previously demonstrated the number of ICU physicians, intensivists, and closed unit format in Japan. Furthermore, the intensivists in our study may be merely listed on the JSICM-board-certified physician list and may not necessarily work in an ICU. Therefore, we needed to assume several conditions about the number of ICU physicians and the influence of intensivists. In Japan, ICUs are likely to have only one ICU physician because staffing an ICU physician is difficult for each hospital because of the shortage of physicians. The number of intensivists that we analyzed represented the largest number of intensivists as a workforce at each hospital; however, if a hospital has even one intensivist, we assumed that the intensivist contributed to at least some part of the quality of care in the ICU. Finally, we could not distinguish the reason for death during the study period. For our study population, death is likely to be caused by aging or other comorbidities. We tried to set the timing of outcome to ensure that extraneous factors were unlikely to influence mortality. Moreover, we considered that the outcome needs to reflect of the quality of care, and we accordingly evaluated the 28-day mortality after ICU admission. Conclusions Intensivists whose certification is conferred by a society of intensive care medicine are more beneficial for older patients with septic shock with regard to 28-day mortality than are physicians who do not hold a certification. An important factor to ensure the quality of septic shock care for older patients is to require regular updating of knowledge and commonality across subspecialties. Moreover, heterogeneity of ICU physicians is preferable when reporting outcomes on the quality of ICU care. Further investigation is required to reveal the robustness and accuracy of the relationship between physician background and outcome. Abbreviations APACHE Acute Physiology and Chronic Health Evaluation CCI Charlson Comorbidity Index ICU intensive care unit ICC intraclass correlation coefficient JSICM Japanese Society of Intensive Care Medicine MOR median odds ratio SMA secondary medical area SOFA Sequential Organ Failure Assessment SAPS Simplified Acute Physiology Score SICM specialized intensive care management Declarations Ethics approval and consent to participate This study was approved by the Institutional Review Board of Kyushu University (Clinical Bioethics Committee of the Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan; approval no. 2021-335), which waived the requirement of informed consent because the information from an anonymized dataset was analyzed and no intervention was performed. Consent for publication Not applicable. Availability of data and materials The data that support the findings of this study are available from Fukuoka Prefecture and the Japanese Society of Intensive Care Medicine (JSICM), but restrictions apply to the availability of these data, which were used under license for the current study, and therefore are not publicly available. Data are however available from the authors upon reasonable request and with permission of Fukuoka Prefecture government and JSICM. Declaration of Competing Interest The authors declare that they have no competing interests. Funding None. Authors' contributions Conceptualization: SY and AB Data Curation: SY Formal analysis: SY, AB and NL Writing - Original Draft: SY Writing - Review & Editing: SY and AB Supervision: NL, RY, RI and TF All authors interpreted the data, critically revised the manuscript for important intellectual content, and approved the final manuscript. 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Crit Care 2011;15:R130. Ohbe H, Sasabuchi Y, Matsui H, Fushimi K, Yasunaga H. Resource-rich intensive care units vs. standard intensive care units on patient mortality: a nationwide inpatient database study. JMA J 2021;4:397-404. Fukuoka Prefectural Government. Report on medical functions of hospital beds in Fukuoka Prefecture in the FY 2015, nos. 22660–22663, 22665, 22666, 22668, 22671, 22671; https://www.pref.fukuoka.lg.jp/contents/bed-function-report-h27.html. Accessed 11 Jul 2019 [In Japanese] Tisherman SA, Spevetz A, Blosser SA, Brown D, Chang C, Efron PA, et al. A case for change in adult critical care training for physicians in the United States: A white paper developed by the Critical Care as a Specialty Task Force of the Society of Critical Care Medicine. Crit Care Med 2018;46:1577-84. Checkley W, Martin GS, Brown SM, Chang SY, Dabbagh O, Fremont RD, et al. Structure, process, and annual ICU mortality across 69 centers: United States Critical Illness and Injury Trials Group Critical Illness Outcomes Study. Crit Care Med 2014;42:344-56. Kerlin MP, Adhikari NK, Rose L, Wilcox ME, Bellamy CJ, Costa DK, et al. An official American Thoracic Society systematic review: the effect of nighttime intensivist staffing on mortality and length of stay among intensive care unit patients. Am J Respir Crit Care Med 2017;195:383-93. Neuraz A, Guérin C, Payet C, Polazzi S, Aubrun F, Dailler F, et al. Patient mortality is associated with staff resources and workload in the ICU: a multicenter observational study. Crit Care Med 2015;43:1587-94. Gaieski DF, Edwards JM, Kallan MJ, Mikkelsen ME, Goyal M, Carr BG. The relationship between hospital volume and mortality in severe sepsis. Am J Respir Crit Care Med 2014;190:665-74. Wortel SA, de Keizer NF, Abu-Hanna A, Dongelmans DA, Bakhshi-Raiez F. Number of intensivists per bed is associated with efficiency of Dutch intensive care units. J Crit Care 2021;62:223-9. Gershengorn HB, Harrison DA, Garland A, Wilcox ME, Rowan KM, Wunsch H. Association of intensive care unit patient-to-intensivist ratios with hospital mortality. JAMA Intern Med 2017;177:388-96. Prin M, Wunsch H. International comparisons of intensive care: informing outcomes and improving standards. Curr Opin Crit Care 2012;18:700-6. Viglianti EM, Iwashyna TJ. Toward the ideal ratio of patients to intensivists: finding a reasonable balance. JAMA Intern Med 2017;177:396-8. Quan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, et al. Updating and validating the Charlson Comorbidity Index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol 2011;173:676-82. Supplementary Files etable.docx Additional Table 1,.docx, Geographic profiles (2015) SMA secondary medical area The value was calculated as 1 USD = 120.13 JPY (the average rate in 2015). ** The sum of SMA 2 and SMA 3. *** Includes one pediatric intensive care unit. Additional Table 2,.docx, Disease names, codes and corresponding ICD 10 codes that were used in this study ICD-10 , International Classification of Diseases, 10 th revision (World Health Organization, Geneva, Switzerland, 1994). 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-2148391","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":157983561,"identity":"faf7df4d-9369-4c34-a5ec-e7cc7266e928","order_by":0,"name":"Shinichiro Yoshida","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYHACNoYENhsIkwdMHiBKSxqpWhjYDiNrIQAMjrc/e/Cg7Lw9/+zuxAdvGOzkGRjP4rfG4MwZc4OEc7cTZ9w5u9lwDkOyYQPDuQT8Wm7ksEkktt1OYLiRu02ah4EZqPyMAQEt6c+AWs7Zy9/I3f6bh6GeGC0JZkAtBxg3AG1h5mE4TFiL5JkzZhIJ55ITNwL9IjnH4LhhGyG/8AFDTPJHmZ293O3ejR/eVFTL80sQCDEFuLQE2J3AOJI4g1cHg3wDihYQ4O/Br2UUjIJRMApGHAAAxeZLW7/Nn4IAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-0916-8446","institution":"Graduate School of Medical Science, Kyushu University","correspondingAuthor":true,"prefix":"","firstName":"Shinichiro","middleName":"","lastName":"Yoshida","suffix":""},{"id":157983562,"identity":"5c0c290f-e34c-4858-bb7a-78f7587672f9","order_by":1,"name":"Akira Babazono","email":"","orcid":"","institution":"Department of Healthcare Administration and Management, Faculty of Medical Sciences, Kyushu University","correspondingAuthor":false,"prefix":"","firstName":"Akira","middleName":"","lastName":"Babazono","suffix":""},{"id":157983563,"identity":"033f900d-dbd9-457a-a244-fe3bea0843e9","order_by":2,"name":"Ning Liu","email":"","orcid":"","institution":"Department of Preventive Medicine and Community Health, University of Occupational and Environmental Health","correspondingAuthor":false,"prefix":"","firstName":"Ning","middleName":"","lastName":"Liu","suffix":""},{"id":157983564,"identity":"015259bc-6edd-409b-9056-e0324d2de854","order_by":3,"name":"Reiko Yamao","email":"","orcid":"","institution":"Department of Medical Sciences, Graduate School of Medical Sciences, Kyushu University","correspondingAuthor":false,"prefix":"","firstName":"Reiko","middleName":"","lastName":"Yamao","suffix":""},{"id":157983565,"identity":"34a231cb-aba4-4819-bc92-2fe61421df81","order_by":4,"name":"Reiko Ishihara","email":"","orcid":"","institution":"Department of Management Walfare Business, Faculty of Human Sociology, Kobe University of Future Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Reiko","middleName":"","lastName":"Ishihara","suffix":""},{"id":157983566,"identity":"5477c208-1495-4407-b746-cae5cee710ff","order_by":5,"name":"Takako Fujita","email":"","orcid":"","institution":"Department of Health Sciences, Faculty of Mdeical Sciences, Kyushu University","correspondingAuthor":false,"prefix":"","firstName":"Takako","middleName":"","lastName":"Fujita","suffix":""}],"badges":[],"createdAt":"2022-10-09 17:17:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2148391/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2148391/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":30074756,"identity":"3be039b3-4597-4cfe-86f0-b1affb7c7d29","added_by":"auto","created_at":"2022-12-08 16:05:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":34165,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of patient identification and selection. Patients were excluded because (1) the patient was an older insurance beneficiary with a disability (age, ≥65 to \u0026lt;75 years) potentially prevents fairly evaluation, and because the patient lost insurance qualification for reasons other than death (e.g. the relocation of beneficiaries) prevent follow-up; (2) the ICU stay was too short (several days may elapse before the quality of care is reflected), and (3) data were missing.\u003c/p\u003e\n\u003cp\u003eICU, intensive care unit\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2148391/v1/c0fb956584387cbdb034de84.png"},{"id":36050280,"identity":"e022b76d-1ea9-464d-95aa-5f17ceae0792","added_by":"auto","created_at":"2023-04-20 09:05:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":400367,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2148391/v1/619920d5-77e5-4ab1-b358-42e03044922c.pdf"},{"id":30074757,"identity":"b9eecc99-8f4c-4f4e-920d-b437e1e1a637","added_by":"auto","created_at":"2022-12-08 16:05:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":29213,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional Table 1,.docx, Geographic profiles (2015)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSMA\u003c/em\u003e secondary medical area\u003c/p\u003e\n\u003cp\u003e* The value was calculated as 1 USD = 120.13 JPY (the average rate in 2015).\u003c/p\u003e\n\u003cp\u003e** The sum of SMA 2 and SMA 3.\u003cbr\u003e\n*** Includes one pediatric intensive care unit.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdditional Table 2,.docx, Disease names, codes and corresponding ICD 10 codes that were used in this study\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eICD-10\u003c/em\u003e, \u003cem\u003eInternational Classification of Diseases, 10\u003c/em\u003e\u003csup\u003e\u003cem\u003eth\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e revision\u003c/em\u003e (World Health Organization, Geneva, Switzerland, 1994).\u003c/p\u003e","description":"","filename":"etable.docx","url":"https://assets-eu.researchsquare.com/files/rs-2148391/v1/b78febb8561bf269eff028e4.docx"}],"financialInterests":"","formattedTitle":"Regional differences and mortality-associated risk factors among older patients with septic shock: Administrative data analysis with multilevel logistic regression modeling","fulltext":[{"header":"Background","content":"\u003cp\u003eThe treatment of septic shock necessitates clinical experience and knowledge as well as multidisciplinary care. Therefore, septic shock is a critical illness wherein the outcome represents the quality of the intensive care that is provided [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Septic shock-related mortality remains high, despite decreasing over the past several years [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], especially in older patients [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Closed intensive care unit (ICU) management and high-intensity intensivist consultation may contribute to an improved mortality risk in septic shock [\u003cspan additionalcitationids=\"CR8 CR9 CR10\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, variability in septic shock mortality has been reported. For example, physician staffing [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], ICU admission rate [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], racial and ethnic minority status [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and insurance type [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] are factors that are associated with septic shock mortality. These settings are difficult to fully optimize across hospitals; therefore, septic shock mortality could differ by hospital and by region.\u003c/p\u003e \u003cp\u003eThe proportion of the older population is increasing in most developed countries, especially in Japan and European countries. Worldwide, tools for early recognition of sepsis and recent advances in the treatment of septic shock increase the possibility of treatment for older patients with septic shock; however, studies that investigated and reported septic shock mortality have rarely been focused on the older population.\u003c/p\u003e \u003cp\u003eWe hypothesized that regional variability in septic shock mortality exists and occurs because of unreported hospital characteristic measures, such as the number of beds per board-certified intensivist. This study involved a descriptive data analysis of the mortality risk in older patients with septic shock with the aim to examine regional differences in septic shock mortality.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective open cohort study by using the administrative claims data of older patients who were beneficiaries of Fukuoka Prefecture Wide-Area Association of Latter-Stage Elderly Healthcare, Japan. In 2018, this health insurance program covered approximately 606,000 individuals, or approximately 95% of residents aged 75 years or more in the Fukuoka Prefecture (Additional Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Basically, all individuals aged 75 years or over are insured. Individuals aged 65 to 74 years, who have a specific disability, are also insured. We screened patients (age\u0026thinsp;\u0026ge;\u0026thinsp;75 years) who were admitted from April 2015 to March 2020 to 35 ICUs with the disease name and diagnostic code of sepsis that are used for health insurance claims in Japan. We identified eligible patients by using codes that included the terms \u0026ldquo;sepsis\u0026rdquo; or \u0026ldquo;septic\u0026rdquo; (Additional Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). We included only patients with any vasopressor or antibiotic use during ICU admission and who were admitted to the ICU for more than 1 day. To ensure accurate data collection, we excluded the data of patients who lost qualification for health insurance for a reason other than death (e.g., change in residence to outside Fukuoka Prefecture), as well as records of the second or later ICU admissions, in case of multiple admissions for septic shock. Data on hospitalization in areas outside the Fukuoka Prefecture were excluded.\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\u003eComparison of the participants\u0026rsquo; characteristics and treatments\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c11\" namest=\"c2\"\u003e \u003cp\u003eSecondary Medical Area\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\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, y (median, IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83.5 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e86 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e84 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e83 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e83 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, male (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e53.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e55.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e48.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCI, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e42.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVasopressor use (%)\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNoradrenaline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e91.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e86.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e83.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.02*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVasopressin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e49.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDopamine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e38.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e36.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdrenaline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntibiotic use (%)\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbapenems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e75.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e53.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e48.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-MRSA agents**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eIQR, interquartile range; CCI, Charlson Comorbidity Index; MRSA, methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e**Anti-MRSA agents include vancomycin, teicoplanin, daptomycin, and linezolid.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\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\u003eMortality rates in the secondary medical areas\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary medical area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28-Day mortality (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eZ-score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.12 (1.36\u0026ndash;3.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.16 (1.38\u0026ndash;7.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.08 (0.98\u0026ndash;4.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.55 (0.81\u0026ndash;2.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.98 (1.13\u0026ndash;7.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.33 (0.79\u0026ndash;2.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.26 (1.47\u0026ndash;3.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.77 (1.50\u0026ndash;5.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eOR, odds ratio; SE, standard error; CI, confidence interval\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e* \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eICU admission was identified by detecting the reimbursement of a specialized intensive care management (SICM) fee (here, \u0026ldquo;specialized\u0026rdquo; does not refer to specific diseases such as stroke and acute coronary syndrome).\u003c/p\u003e \u003cp\u003e This study was approved by the Institutional Review Board of Kyushu University (Clinical Bioethics Committee of the Graduate School of Medical Sciences, Kyushu University [approved no. 2021\u0026thinsp;\u0026minus;\u0026thinsp;335]), which waived the requirement of informed consent for this noninterventional study because information from an anonymized dataset was analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eICU settings in Japan\u003c/h2\u003e \u003cp\u003eHospitals can submit claims for the SICM fee as an incentive for a specially organized department if their ICU meets the specific government-stipulated conditions. Two types of SICM fee broadly exist: ordinary and superior, which are referred to as \u0026ldquo;standard ICU\u0026rdquo; and \u0026ldquo;resource-rich ICU,\u0026rdquo; respectively [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The aforementioned conditions include full-time availability of in-house dedicated physicians in the ICU and an ICU bed/nurse ratio\u0026thinsp;\u0026le;\u0026thinsp;2. Moreover, in each ICU, the number of cases that need to be monitored, procedures, and devices for life support must be accounted for in \u0026ge;\u0026thinsp;70% of all ICU cases. However, the superior type of SICM fee is designed to provide aggressive treatment by adding sufficient human resources to ensure the previously mentioned conditions. More specifically, two or more ICU physicians with experience in intensive care medicine for 5 years or more must be dedicatedly assigned to ICU services, an in-house clinical engineer should be available at all times, and an experienced nurse who has completed the given intensive care course must be dedicated to ICU nursing for at least 20 hours per week. For ICU physicians at a hospital that claims the ordinary type of SICM fee, specific specialty and clinical careers in intensive care are not required. For both types of SICM fee, the specialties of the ICU physician\u0026rsquo;s background, which popularly include anesthesiology, emergency medicine, cardiovascular medicine/surgery, neurology/neurosurgery, and abdominal surgery, are not required in Japan. In our study, we refer to only ICUs that can claim the SICM fee, although ICUs exist which do not claim the SICM fee.\u003c/p\u003e \u003cp\u003eBoard certification in intensive care medicine in Japan is administered only by Japanese Society of Intensive Care Medicine (JSICM). However, whether an ICU physician is a board-certified by the JSICM is not an eligibility requirement for the SICM fee. Therefore, some ICUs have ICU-dedicated physicians who are not board-certified in intensive care medicine by the JSICM. Neither unit format nor consultation intensity (e.g. closed/open ICU and high/low-intensity consultation to intensivist) are required for the SICM fee. Although we did not investigate ICU format and intensity, we used the JSICM-board-certified physician list to accurately ascertain the number of JSICM-board-certified physicians at each hospital.\u003c/p\u003e \u003cp\u003eIn this study, \u0026ldquo;intensivist\u0026rdquo; indicates a physician with JSICM-board-certification in intensive care and \u0026ldquo;ICU-dedicated physician\u0026rdquo; refers to ICU physicians without a JSICM certification in intensive care; whereas \u0026ldquo;ICU physician\u0026rdquo; refers to both.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eRegional and hospital profiles\u003c/h2\u003e \u003cp\u003eThe Japanese government defines a secondary medical area (SMA) as a designated area wherein residents of that area can receive complete conventional inpatient care, based on geographical area, population, and hospital distribution. Fukuoka Prefecture has 13 SMAs, of which 4 SMAs do not have any hospitals that are allowed to claim the SICM fee; therefore, we included 9 SMAs in this study. Four academic hospitals are in 3 SMAs, and 10 tertiary emergency medical centers are in 5 SMAs, all of which have an ICU with SICM fee-reimbursement eligibility. The number of hospital beds in this study ranged from 150 beds to 1275 beds, as described in the Report on Medical Functions of Hospital Beds in Fukuoka Prefecture [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003ePrimary outcome and study variables\u003c/h2\u003e \u003cp\u003eThe primary outcome was the 28-day mortality after ICU admission. To quantify mortality variations that are attributable to a patient\u0026rsquo;s characteristics or hospital profiles, we employed multilevel logistic analysis, after conducting univariate and multivariate analyses. Age, sex, year of admission, and the Charlson Comorbidity Index (CCI) were recorded as the patients\u0026rsquo; characteristics. Patients in whom surgical procedures were performed within 7 days preceding an ICU admission were recorded as a case of postoperative admission. Hospital location, the number of beds and proportion of ICU beds within each hospital, the ICU bed-to-intensivist ratio, and type of SICM fee were investigated in the hospital profile.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe compared the participants\u0026rsquo; characteristics for each SMA. For variables recorded as dichotomous measures, the chi-square test was performed to examine regional differences. The Kruskal\u0026ndash;Wallis test was performed for continuous variables. Mortality was compared, using odds ratios, by performing univariate logistic regression analysis with the SMA term as the explanatory variable.\u003c/p\u003e \u003cp\u003eWe were concerned that more severely ill patients may be treated at specific hospitals such as ICUs in university hospitals. Moreover, ICU physicians in regions that are geographically distant from each other may not treat patients in the same manner because they are likely to be trained at different educational facilities such as university hospitals, which have different interests. To address potential biases, we examined the variance at the hospital or regional level with multivariate logistic regression analysis by using multilevel modeling. The null model included no variables, Model 1 included participant characteristics, and Model 2 included Model 1 variables and the hospital profiles. The Z-score, which suggests the significance of variance in each model and the necessity of multilevel analysis, was calculated. The Z-score was calculated by dividing the variance estimate by the estimated standard error. When the Z-score is \u0026gt;\u0026thinsp;2, the variables included in the model may have a contextual effect. Therefore, multilevel analysis was employed. However, if the Z-score is \u0026lt;\u0026thinsp;2, multilevel logistic analysis is suitable for statistical analysis. Furthermore, the median odds ratio (MOR) was calculated for quantifying variation or heterogeneity in outcomes between clusters by using the between-cluster variance; a higher MOR indicates a greater contextual effect of the model, whereas a MOR close to 1 implies very small inter-cluster variability of outcomes.\u003c/p\u003e \u003cp\u003eAll analyses were performed by using Stata/IC 14 (StataCorp, College Station, TX, USA). All reported \u003cem\u003ep\u003c/em\u003e-values were two-tailed, and the level of significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eWe identified 2,658 patients who were diagnosed with sepsis and had received vasopressors and antibiotics. However, after excluding patients because of insurance qualification, hospital location, short ICU stay, and missing data, we included the data from 1,238 patients in the final analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRegional differences in postoperative admission, medication usage, and clinical outcome were identified (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The 28-day mortality after ICU admission ranged from 18.3\u0026ndash;41.4% across SMAs (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The Z-scores in the multilevel logistic regression analysis showed that multilevel modeling did not differ significantly from that of the multivariable logistic model (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This finding suggested that explanatory variables pertaining to the patients\u0026rsquo; characteristics and hospital profiles in this study may not vary across SMAs. Furthermore, the MOR (approximately 1.0) implied homogeneity among these variables. Based on the log likelihood results, the full variable model (i.e., Model 2) was the best-fitted model among the three models. In Model 2, the 28-day mortality after ICU admission was significantly influenced by the age group, sex, postoperative admission, and the number of ICU beds per intensivist (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\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\u003eResults of multilevel logistic regression analysis on regional variations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eMultivariate\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eOR (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eP\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eAOR (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ep\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAge group, y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u0026ndash;84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.20 (0.86\u0026ndash;1.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.28 (0.91\u0026ndash;1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85\u0026ndash;89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.39 (0.99\u0026ndash;1.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.49 (1.05\u0026ndash;2.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.56 (1.05\u0026ndash;2.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.86 (1.23\u0026ndash;2.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77 (0.60\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.73 (0.56\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eFiscal year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03 (0.70\u0026ndash;1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.09 (0.73\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.09 (0.74\u0026ndash;1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.15 (0.77\u0026ndash;1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87 (0.59\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87 (0.59\u0026ndash;1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01 (0.69\u0026ndash;1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.09 (0.73\u0026ndash;1.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07 (0.84\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.09 (0.85\u0026ndash;1.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.09 (0.33\u0026ndash;3.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.30 (0.38\u0026ndash;4.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcedure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePostoperative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.63 (0.48\u0026ndash;0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62 (0.47\u0026ndash;0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber of hospital beds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08 (0.84\u0026ndash;1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82 (0.59\u0026ndash;1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eProportion of ICU beds to hospital beds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5\u0026ndash;3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.16 (0.86\u0026ndash;1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.22 (0.84\u0026ndash;1.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92 (0.69\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93 (0.65\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eICU bed-to-board certified physician ratios\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.18 (0.75\u0026ndash;1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.41 (0.84\u0026ndash;2.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo certified physician\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.64 (1.06\u0026ndash;2.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.25 (1.36\u0026ndash;3.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eType of SICM fee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExpensive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrdinary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06 (0.81\u0026ndash;1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.81 (0.57\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eOR, odds ratio; CI, confidence interval; AOR, adjusted odds ratio; CCI, Charlson Comorbidity Index; ICU, intensive care unit; SICM, specialized intensive care management\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e* \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \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\u003eResults of the multilevel logistic regression analyses\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNull model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel 2\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\u003e\u003cb\u003eLevel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eEstimate (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eEstimate (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eEstimate (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLog likelihood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;747.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;734.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;729.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSMA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06 (0.01\u0026ndash;0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05 (0.01\u0026ndash;0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03 (0.00\u0026ndash;0.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03 (0.00\u0026ndash;0.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04 (0.00\u0026ndash;0.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01 (0.00\u0026ndash;17.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZ-score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSMA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSMA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02 (0.00\u0026ndash;0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02 (0.00\u0026ndash;0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01 (0.00\u0026ndash;0.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03 (0.01\u0026ndash;0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03 (0.01\u0026ndash;0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01 (0.00\u0026ndash;0.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSMA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.26 (1.09\u0026ndash;1.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24 (1.07\u0026ndash;1.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.16 (1.04\u0026ndash;1.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.19 (1.05\u0026ndash;1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.22 (1.07\u0026ndash;1.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.10 (1.00\u0026ndash;51.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCV (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSMA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;35.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eCI, confidence interval; SMA, secondary medical area; ICC, intraclass correlation coefficient; MOR, median odds ratio; PCV, proportional change in variance\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOlder patients with septic shock have poor outcomes because of frailty and the severity of organ failure [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and are likely to be highly sensitive to the quality of care. We proved our hypothesis of regional mortality variability among older patients with septic shock, which varied across regions, which was potentially attributable mortality-associated factors, including sex, being a nonsurgical patient, and the ICU bed-to-intensivist ratio. The results of multilevel analysis showed that the contextual effect in an SMA or in hospitals was small; therefore, the impact of variations in patient characteristics among our study clusters (i.e. SMA and hospitals) was too small to ascertain mortality variation. However, the intraclass correlation coefficients in Model 2 decreased to less than one-half of that in the null model, when controlling for hospital profiles. In particular, the intensivist density for ICU beds significantly influenced mortality.\u003c/p\u003e \u003cp\u003eThe present study included two types of ICU physicians: JSICM-board-certified intensivists and ICU-dedicated physicians. Intensivists in Japan must regularly satisfy the requirements for revalidation of their certification every 5 years by attaining some achievements such as conducting research activity, participating in learning sessions, and instructing trainees with regard to intensive care medicine. ICU-dedicated physicians do not have any requirement for maintaining the accreditation of the SICM fee, and ICU-dedicated physicians have an uncertain training history and an uncertain updating of knowledge and skills with regard to intensive care. Physicians without board certification but with a greater ability for intensive care realistically exist; however, our study clearly revealed the advantage of board-certified intensivists for older patients with septic shock.\u003c/p\u003e \u003cp\u003eOur results suggest that some potential weaknesses exist in the definition of ICU physician for the reimbursement of intensive care management in Japan. After ICU physicians are approved by the government in the context of approval of the application for reimbursement of the SICM fee, ICU physicians are not usually required to undergo cumulative activities after approval, unlike the requirement to maintain JSICM certification. Our findings may reflect the importance of regularly updating knowledge and skills of ICU physicians. Furthermore, based on the findings, we recognize that commonality across subspecialties needs to be considered to enable the intensivist to provide appropriate critical care without resorting to specialty-biased decision-making [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Increasing the number of trained intensivists remains challenging due to the time, cost, and effort involved; however, regular accreditation of ICU physicians, based on specific criteria similar to those used for certification of intensivists, should be considered to ensure that adequately trained physicians can assure good quality sepsis care.\u003c/p\u003e \u003cp\u003eAnother concern about the weakness of ICU-dedicated physicians is the intensity of commitment to ICU patients. ICU physicians are permitted to provide the clinical practices of their own specialty, in addition to providing intensive care within an ICU, as long as the ICU physicians are in the ICU ward. Thus, even ICU-dedicated physicians may limit their involvement with ICU patients because of their duties in their own specialty, especially in the situation of an open ICU format in which attending physicians primarily commit to an ICU patient. As mentioned later, to improve the outcomes of older patients with septic shock, sufficient commitment of the ICU physician to a patient or attending physicians is highly desirable.\u003c/p\u003e \u003cp\u003eRecent studies [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] have shown that a closed ICU format and night-time staffing of intensivists were not necessarily beneficial for patients\u0026rsquo; outcomes after ICU admission. However, particularly in septic shock treatment, a higher ratio of patients to intensivist and the lack of the availability of intensivists during the night may be associated with poor outcomes [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. One study [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] indicated that the case volume may have a positive effect on improving the outcome of septic shock. Additionally, in view of our findings, the intensity of commitment by intensivists is likely to remain important in the treatment of older patients with septic shock. Moreover, increasing the number of intensivists should be considered, based on the number of patients. This finding is consistent with the results of a study [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] that showed that the number of intensivists per bed was associated with the efficiency of an ICU. A previous study [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] on patient-to-intensivist ratios reported that a positive effect on mortality is optimized at 7.5. This value was obtained from a case-mix population and may have been modified by the number of board-certified intensivists in older patients with septic shock. In the present study, we stratified the cohort with a four bed/intensivist ratio to enable the analysis of a comparable number of hospitals. A lower ICU bed-to-intensivist ratio seems to improve septic shock outcomes. However, the aforementioned strategy is not necessarily advantageous from the perspective of the case volume effect [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. To optimize efficiency and improve septic shock outcomes, regionalization and centralization of intensivists should be considered [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSome researchers have reported results that reflect the diversity of proficiency among ICU physicians and the extent of training in intensive care, and these need to be demonstrated by an appropriate approach [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. As heterogeneity in ICU physicians has not been considered in most studies that have examined outcome variations in critically ill patients, the results potentially reflect the intensivist attribution and should be interpreted with caution when applying this study\u0026rsquo;s findings to ICU management policy.\u003c/p\u003e \u003cp\u003eOur study population has some strengths in selection, compared to other studies. For example, in Japan, most older residents were universally covered by social insurance. Therefore, disparities due to insurance plans are smaller than those of studies in other countries. Moreover, the Japanese population has small racial differences.\u003c/p\u003e \u003cp\u003eHowever, our study had several limitations because we used administrative data. First, we could not collect data on the laboratory tests, vital signs, and physical examination findings, or information about the stage of septic shock on ICU admission. However, we rigorously selected the study population to address these weaknesses. For example, vasopressors and antibiotics, in addition to a diagnosis of sepsis, were essential for patient enrollment. The aforementioned agents are likely to be used by any physician who decides to treat a patient, regardless of whether the ICU physician is an intensivist. Moreover, we could not calculate severity scores such as the Sequential Organ Failure Assessment (SOFA) score and Acute Physiology and Chronic Health Evaluation 2 (APACHE 2) score. In this study, the CCI was used as a substitute for measures that may reflect severity and exacerbation of sepsis. The CCI could predict mortality in ICU patients to a similar extent as a physiology-based score such as the Simplified Acute Physiology Score 2 (SAPS 2). [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Second, we have no data on limitations in life-sustaining treatment. We considered circumstances, including those wherein the patient refused any treatment just before or after ICU admission, or the physicians proposed the withdrawal of invasive treatment because they judged that the patient was too severely ill to survive. These patients and patients with mild symptoms potentially distort the evaluation for quality of care because the patient does not receive sufficient treatment for evaluation. To address this problem, we excluded patients who were discharged from the ICU within 1 day. Third, we could not ascertain how ICU physicians provide clinical services in the ICU. This perspective includes a combination of intensity and unit format, total number of ICU physicians, and staffing. No nationwide hospital survey has previously demonstrated the number of ICU physicians, intensivists, and closed unit format in Japan. Furthermore, the intensivists in our study may be merely listed on the JSICM-board-certified physician list and may not necessarily work in an ICU. Therefore, we needed to assume several conditions about the number of ICU physicians and the influence of intensivists. In Japan, ICUs are likely to have only one ICU physician because staffing an ICU physician is difficult for each hospital because of the shortage of physicians. The number of intensivists that we analyzed represented the largest number of intensivists as a workforce at each hospital; however, if a hospital has even one intensivist, we assumed that the intensivist contributed to at least some part of the quality of care in the ICU.\u003c/p\u003e \u003cp\u003eFinally, we could not distinguish the reason for death during the study period. For our study population, death is likely to be caused by aging or other comorbidities. We tried to set the timing of outcome to ensure that extraneous factors were unlikely to influence mortality. Moreover, we considered that the outcome needs to reflect of the quality of care, and we accordingly evaluated the 28-day mortality after ICU admission.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIntensivists whose certification is conferred by a society of intensive care medicine are more beneficial for older patients with septic shock with regard to 28-day mortality than are physicians who do not hold a certification. An important factor to ensure the quality of septic shock care for older patients is to require regular updating of knowledge and commonality across subspecialties. Moreover, heterogeneity of ICU physicians is preferable when reporting outcomes on the quality of ICU care. Further investigation is required to reveal the robustness and accuracy of the relationship between physician background and outcome.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\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\"\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\"\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\"\u003eICC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eintraclass correlation coefficient\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eJSICM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eJapanese Society of Intensive Care Medicine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emedian odds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSMA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esecondary medical area\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 \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\"\u003eSICM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003especialized intensive care management\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 by the Institutional Review Board of Kyushu University (Clinical Bioethics Committee of the Graduate School of Medical Sciences, Kyushu University,\u0026nbsp;Fukuoka, Japan; approval no. 2021-335), which waived the requirement of informed consent because the information from an anonymized dataset was analyzed and no intervention was performed.\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 data that support the findings of this study are available from Fukuoka Prefecture and the Japanese Society of Intensive Care Medicine (JSICM), but restrictions apply to the availability of these data, which were used under license for the current study, and therefore are not publicly available. Data are however available from the authors upon reasonable request and with permission of Fukuoka Prefecture government and JSICM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: SY and AB\u003c/p\u003e\n\u003cp\u003eData Curation: SY\u003c/p\u003e\n\u003cp\u003eFormal analysis: SY, AB and NL\u003c/p\u003e\n\u003cp\u003eWriting - Original Draft: SY\u003c/p\u003e\n\u003cp\u003eWriting - Review \u0026amp; Editing: SY and AB\u003c/p\u003e\n\u003cp\u003eSupervision: NL, RY, RI and TF\u003c/p\u003e\n\u003cp\u003eAll authors interpreted the data, critically revised the manuscript for important intellectual content, and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the Wide-Area Association of Latter-Stage Elderly Healthcare of Fukuoka Prefecture for their provision of a health care claims database. We would also like to thank Editage (www.editage.com) for English language editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWalkey AJ, Shieh MS, Liu VX, Lindenauer PK. Mortality measures to profile hospital performance for patients with septic shock.\u003cem\u003e Crit Care Med \u003c/em\u003e2018;46:1247-54.\u003c/li\u003e\n\u003cli\u003eWardi G, Tainter CR, Ramnath VR, Brennan JJ, Tolia V, Castillo EM, et al. Age-related incidence and outcomes of sepsis in California, 2008-2015.\u003cem\u003e J Crit Care \u003c/em\u003e2021;62:212-7.\u003c/li\u003e\n\u003cli\u003evan Zanten AR, Brinkman S, Arbous MS, Abu-Hanna A, Levy MM, de Keizer NF, et al. Guideline bundles adherence and mortality in severe sepsis and septic shock.\u003cem\u003e Crit Care Med \u003c/em\u003e2014;42:1890-8.\u003c/li\u003e\n\u003cli\u003eVakkalanka JP, Harland KK, Swanson MB, Mohr NM. Clinical and epidemiological variability in severe sepsis: an ecological study.\u003cem\u003e J Epidemiol Community Health \u003c/em\u003e2018;72:741-5.\u003c/li\u003e\n\u003cli\u003eNasa P, Juneja D, Singh O, Dang R, Arora V. Severe sepsis and its impact on outcome in elderly and very elderly patients admitted in intensive care unit.\u003cem\u003e J Intensive Care Med \u003c/em\u003e2012;27:179-83.\u003c/li\u003e\n\u003cli\u003eIbarz M, Boumendil A, Haas LEM, Irazabal M, Flaatten H, de Lange DW, et al. Sepsis at ICU admission does not decrease 30-day survival in very old patients: a post-hoc analysis of the VIP1 multinational cohort study.\u003cem\u003e Ann Intensive Care \u003c/em\u003e2020;10:56.\u003c/li\u003e\n\u003cli\u003eWilcox ME, Chong CA, Niven DJ, Rubenfeld GD, Rowan KM, Wunsch H, et al. Do intensivist staffing patterns influence hospital mortality following ICU admission? A systematic review and meta-analyses.\u003cem\u003e Crit Care Med \u003c/em\u003e2013;41:2253-74.\u003c/li\u003e\n\u003cli\u003eSinger JP, Kohlwes J, Bent S, Zimmerman L, Eisner MD. The impact of a \u0026ldquo;low-intensity\u0026ldquo; versus \u0026ldquo;high-intensity\u0026ldquo; medical intensive care unit on patient outcomes in critically ill veterans.\u003cem\u003e J Intensive Care Med \u003c/em\u003e2010;25:233-9.\u003c/li\u003e\n\u003cli\u003eOgura T, Nakamura Y, Takahashi K, Nishida K, Kobashi D, Matsui S. Treatment of patients with sepsis in a closed intensive care unit is associated with improved survival: a nationwide observational study in Japan.\u003cem\u003e J Intensive Care \u003c/em\u003e2018;6:57.\u003c/li\u003e\n\u003cli\u003eTreggiari MM, Martin DP, Yanez ND, Caldwell E, Hudson LD, Rubenfeld GD. Effect of intensive care unit organizational model and structure on outcomes in patients with acute lung injury.\u003cem\u003e Am J Respir Crit Care Med \u003c/em\u003e2007;176:685-90.\u003c/li\u003e\n\u003cli\u003eVincent JL. Evidence supports the superiority of closed ICUs for patients and families: Yes.\u003cem\u003e Intensive Care Med \u003c/em\u003e2017;43:122-3.\u003c/li\u003e\n\u003cli\u003eZampieri FG, Salluh JIF, Azevedo LCP, Kahn JM, Damiani LP, Borges LP, et al. ICU staffing feature phenotypes and their relationship with patients\u0026rsquo; outcomes: an unsupervised machine learning analysis.\u003cem\u003e Intensive Care Med \u003c/em\u003e2019;45:1599-607.\u003c/li\u003e\n\u003cli\u003eWallace DJ, Angus DC, Barnato AE, Kramer AA, Kahn JM. Nighttime intensivist staffing and mortality among critically ill patients.\u003cem\u003e N Engl J Med \u003c/em\u003e2012;366:2093-101.\u003c/li\u003e\n\u003cli\u003eAdmon AJ, Wunsch H, Iwashyna TJ, Cooke CR. Hospital contributions to variability in the use of ICUs among elderly Medicare recipients.\u003cem\u003e Crit Care Med \u003c/em\u003e2017;45:75-84.\u003c/li\u003e\n\u003cli\u003eColon Hidalgo D, Tapaskar N, Rao S, Masic D, Su A, Portillo J, et al. Lower socioeconomic factors are associated with higher mortality in patients with septic shock.\u003cem\u003e Heart Lung \u003c/em\u003e2021;50:477-80.\u003c/li\u003e\n\u003cli\u003eRush B, Danziger J, Walley KR, Kumar A, Celi LA. Treatment in disproportionately minority hospitals is associated with increased risk of mortality in sepsis: a national analysis.\u003cem\u003e Crit Care Med \u003c/em\u003e2020;48:962-7.\u003c/li\u003e\n\u003cli\u003eJones JM, Fingar KR, Miller MA, Coffey R, Barrett M, Flottemesch T, et al. Racial disparities in sepsis-related in-hospital mortality: using a broad case capture method and multivariate controls for clinical and hospital variables, 2004\u0026ndash;2013.\u003cem\u003e Crit Care Med \u003c/em\u003e2017;45:e1209-17.\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Brien JM, Lu B, Ali NA, Levine DA, Aberegg SK, Lemeshow S. Insurance type and sepsis-associated hospitalizations and sepsis-associated mortality among US adults: a retrospective cohort study.\u003cem\u003e Crit Care \u003c/em\u003e2011;15:R130.\u003c/li\u003e\n\u003cli\u003eOhbe H, Sasabuchi Y, Matsui H, Fushimi K, Yasunaga H. Resource-rich intensive care units vs. standard intensive care units on patient mortality: a nationwide inpatient database study.\u003cem\u003e JMA J \u003c/em\u003e2021;4:397-404.\u003c/li\u003e\n\u003cli\u003eFukuoka Prefectural Government. Report on medical functions of hospital beds in Fukuoka Prefecture in the FY 2015, nos. 22660\u0026ndash;22663, 22665, 22666, 22668, 22671, 22671; https://www.pref.fukuoka.lg.jp/contents/bed-function-report-h27.html. Accessed 11 Jul 2019 [In Japanese]\u003c/li\u003e\n\u003cli\u003eTisherman SA, Spevetz A, Blosser SA, Brown D, Chang C, Efron PA, et al. A case for change in adult critical care training for physicians in the United States: A white paper developed by the Critical Care as a Specialty Task Force of the Society of Critical Care Medicine.\u003cem\u003e Crit Care Med \u003c/em\u003e2018;46:1577-84.\u003c/li\u003e\n\u003cli\u003eCheckley W, Martin GS, Brown SM, Chang SY, Dabbagh O, Fremont RD, et al. Structure, process, and annual ICU mortality across 69 centers: United States Critical Illness and Injury Trials Group Critical Illness Outcomes Study.\u003cem\u003e Crit Care Med \u003c/em\u003e2014;42:344-56.\u003c/li\u003e\n\u003cli\u003eKerlin MP, Adhikari NK, Rose L, Wilcox ME, Bellamy CJ, Costa DK, et al. An official American Thoracic Society systematic review: the effect of nighttime intensivist staffing on mortality and length of stay among intensive care unit patients.\u003cem\u003e Am J Respir Crit Care Med \u003c/em\u003e2017;195:383-93.\u003c/li\u003e\n\u003cli\u003eNeuraz A, Gu\u0026eacute;rin C, Payet C, Polazzi S, Aubrun F, Dailler F, et al. Patient mortality is associated with staff resources and workload in the ICU: a multicenter observational study.\u003cem\u003e Crit Care Med \u003c/em\u003e2015;43:1587-94.\u003c/li\u003e\n\u003cli\u003eGaieski DF, Edwards JM, Kallan MJ, Mikkelsen ME, Goyal M, Carr BG. The relationship between hospital volume and mortality in severe sepsis.\u003cem\u003e Am J Respir Crit Care Med \u003c/em\u003e2014;190:665-74.\u003c/li\u003e\n\u003cli\u003eWortel SA, de Keizer NF, Abu-Hanna A, Dongelmans DA, Bakhshi-Raiez F. Number of intensivists per bed is associated with efficiency of Dutch intensive care units.\u003cem\u003e J Crit Care \u003c/em\u003e2021;62:223-9.\u003c/li\u003e\n\u003cli\u003eGershengorn HB, Harrison DA, Garland A, Wilcox ME, Rowan KM, Wunsch H. Association of intensive care unit patient-to-intensivist ratios with hospital mortality.\u003cem\u003e JAMA Intern Med \u003c/em\u003e2017;177:388-96.\u003c/li\u003e\n\u003cli\u003ePrin M, Wunsch H. International comparisons of intensive care: informing outcomes and improving standards.\u003cem\u003e Curr Opin Crit Care \u003c/em\u003e2012;18:700-6.\u003c/li\u003e\n\u003cli\u003eViglianti EM, Iwashyna TJ. Toward the ideal ratio of patients to intensivists: finding a reasonable balance.\u003cem\u003e JAMA Intern Med \u003c/em\u003e2017;177:396-8.\u003c/li\u003e\n\u003cli\u003eQuan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, et al. Updating and validating the Charlson Comorbidity Index and score for risk adjustment in hospital discharge abstracts using data from 6 countries.\u003cem\u003e Am J Epidemiol \u003c/em\u003e2011;173:676-82.\u003c/li\u003e\n\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 unit, Septic shock, Older adults, Mortality, Regional variability, Board-certified intensivist","lastPublishedDoi":"10.21203/rs.3.rs-2148391/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2148391/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eOlder patients with septic shock are generally difficult to treat, have poor outcomes because of frailty and vulnerability, and may be highly sensitive to the quality of clinical care. Therefore, differences in treatment that arise from variations in intensive care unit (ICU) policies and each physician may influence mortality. We hypothesized that regional variability exists in mortality among older patients with septic shock, and investigated mortality-associated factors.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eAdministrative medical claims data were analyzed; participants were enrolled from April 2015 to March 2020. In Japan, engagement of at least one ICU physician exclusively at the ICU is a mandatory requirement to claim governmental incentive. In this study, ICU physicians were differentiated as \u0026ldquo;intensivist\u0026rdquo; and \u0026ldquo;ICU-dedicated physician\u0026rdquo; based on whether they were board-certified or not, respectively, in intensive care medicine. The primary outcome was the 28-day mortality after ICU admission. Data from nine secondary medical areas with ICU facilities were analyzed. We calculated and compared the 28-day mortality by each area. To adjust for patient characteristics and hospital profiles, multilevel logistic regression analyses were conducted.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong our 1,238 participants, mortality varied from 18.3\u0026ndash;41.4% across nine areas. Based on multilevel logistic analyses, the model including variables on patient characteristics and hospital profiles was best-fitted, and these variables did not vary significantly across the nine areas. Age group, post-surgical admission, and the number of ICU beds per intensivist were significantly associated with mortality. The adjusted odds ratio for the ratio of ICU beds to intensivist was 2.25 (95% CI [1.36\u0026ndash;3.72], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), compared with no intensivist versus one or more intensivists for four ICU beds.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eRegional mortality variability of older patients with septic shock was ascertained through our analysis. Mortality may be influenced by whether the ICU physicians are board-certified in intensive care medicine. To ensure quality care of older patients with septic shock, standard criteria, similar to those applied to intensivists, should be considered and applied to ICU physicians.\u003c/p\u003e","manuscriptTitle":"Regional differences and mortality-associated risk factors among older patients with septic shock: Administrative data analysis with multilevel logistic regression modeling","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-12-08 16:05:28","doi":"10.21203/rs.3.rs-2148391/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":"50f292f3-848f-47c8-9189-7ed95283bf47","owner":[],"postedDate":"December 8th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-04-20T09:05:15+00:00","versionOfRecord":[],"versionCreatedAt":"2022-12-08 16:05:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2148391","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2148391","identity":"rs-2148391","version":["v1"]},"buildId":"J0_U0BvcaRcwD8yVFaRlm","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}