martes, 31 de julio de 2018

Lactate clearance as a prognostic marker of mortality in severely ill febrile children in East Africa

Lactate clearance as a prognostic marker of
mortality in severely ill febrile children in
East Africa
A. Aramburo1, Jim Todd2, Elizabeth C. George3, Sarah Kiguli4, Peter Olupot-Olupot5,6, Robert O. Opoka4,




                                                                                Abstract

Background: 

Hyperlactataemia (HL) is a biomarker of disease severity that predicts mortality in patients with sepsis and malaria. Lactate clearance (LC) during resuscitation has been shown to be a prognostic factor of survival in critically ill adults, but little data exist for African children living in malaria-endemic areas.

Methods
In a secondary data analysis of severely ill febrile children included in the Fluid Expansion as Supportive Therapy (FEAST) resuscitation trial, we assessed the association between lactate levels at admission and LC at 8 h with all-cause mortality at 72 h (d72). LC was defined as a relative lactate decline ≥ 40% and/or lactate normalisation (lactate < 2.5 mmol/L).

Results: 
Of 3170 children in the FEAST trial, including 1719 children (57%) with Plasmodium falciparum malaria, 3008 (95%) had a baseline lactate measurement, 2127 (71%) had HL (lactate ≥ 2.5 mmol/L), and 1179 (39%) had severe HL (≥ 5 mmol/L). Within 72 h, 309 children (10.3%) died, of whom 284 (92%) had baseline HL. After adjustment for potential confounders, severe HL was strongly associated with mortality (Odds Ratio (OR) 6.96; 95% CI 3.52, 13.76, p < 0.001). This association was not modified by malaria status, despite children with malaria having a higher baseline lactate (median 4.6 mmol/L vs 3 mmol/L; p < 0.001) and a lower mortality rate (OR = 0.42; p < 0.001) compared to non-malarial cases. Sensitivity and specificity analysis identified a higher lactate on admission cut-off value predictive of d72 for children with malaria (5.2 mmol/L) than for those with other febrile illnesses (3.4 mmol/L). At 8 h, 2748/3008 survivors (91%) had a lactate measured, 1906 (63%) of whom had HL on admission, of whom 1014 (53%) fulfilled pre-defined LC criteria. After adjustment for confounders, LC independently predicted survival after 8 h (OR 0.24; 95% CI 0.14, 0.42; p < 0.001). Absence of LC (< 10%) at 8 h was strongly associated with death at 72 h (OR 4. 62; 95% CI 2.7, 8.0; p < 0.001).

Conclusions: 

Independently of the underlying diagnosis, HL is a strong risk factor for death at 72 h in children admitted with severe febrile illnesses in Africa. Children able to clear lactate within 8 h had an improved chance of survival. These findings prompt the more widespread use of lactate and LC to identify children with severe disease and monitor response to treatment.
Trial registration: ISRCTN69856593 Registered 21 January 2009.

Keywords: Hyperlactataemia, Children, Lactate clearance, East Africa, Mortality, Hospital admission, Clinical trials, Randomised, Sepsis, Malaria



Background

               Infection is a leading cause of death in children under 5 years of age in resource-poor countries in Africa, mainly related to pneumonia, diarrhea, and malaria [1]. Irrespective
of the underlying aetiology, children with severe infection in these settings usually present critically ill to health units with basic facilities, with most deaths occurring within the first 24 h of admission [2]. Immediate recognition and prompt appropriate resuscitation of those children at highest risk of death are crucial to improve survival. Clinical criteria have been proposed by the World Health Organization (WHO) [3, 4], and practical clinical bedside risk scores have been evaluated to identify those at greatest risk of death [5]; however, data on point-of-care diagnostics to refine and target management at the point of triage are still lacking. Hyperlactataemia (HL) is a well-known biomarker of severe disease that strongly predicts death in paediatric and adult patients with bacterial sepsis and malaria [6–9]. 
                  Its prognostic value, availability of point-of-care non-invasive testing, and immediate turnaround time have made lactate measurement one of the most widely recommended tools for early recognition and risk stratification of patients with severe sepsis [10–12]. In malaria-endemic areas, however, the use of point-ofcare lactate measurement is controversial due to lack of data to support wider implementation [5, 13]. Nevertheless, therapeutic strategies aimed at decreasing lactataemia in serial determinations of lactate clearance (LC) could be a simple tool and may be clinically more valuable than initial single lactate measurements, helping to guide resuscitation and potentially being a costeffective measure in these settings. In recent years, several studies including two metaanalyses have demonstrated that early LC and lactate normalisation are powerful independent predictors of survival in critically ill adults [14–17]. 
                   Furthermore, two randomised clinical trials [18, 19] showed that targeting initial treatment to a pre-specified LC was associated with non-inferior or even superior outcomes compared to central venous oxygen saturation, a surrogate marker of cardiac output and a standard invasive therapeutic goal in sepsis. To date, however, only a few small studies have explored the prognostic value of LC in severely ill children with sepsis or malaria [20–22]. A large multicentre randomised control trial of fluid resuscitation
strategies in severely ill febrile children in east Africa, the Fluid Expansion as Supportive Therapy (FEAST) trial, ISRCTN69856593 [23], provided a good opportunity to explore this question further. 
                   The main aim of the current study was to assess the prognostic value of LC at 8 h on all-cause mortality at 72 h (d72) in a large cohort of severely ill febrile children in a malaria-endemic area. Secondary aims were to  confirm the association between HL and d72, assess if this was modified by type of severe febrile illness (malaria vs non-malaria), and to determine the cut-off lactate level on admission that best predicts mortality in these
children.

Methods

         The current study is a secondary analysis derived from the FEAST trial [23]. The overall aim of the trial was to answer whether rapid expansion of intravascular volume was safe and improved survival compared to no bolus (maintenance only). The study was conducted between January 2009 and January 2011 at six clinical centres, including large regional and district hospitals in three east African countries (Kilifi, Kenya; Muheza, Tanzania; and Kampala, Mbale, Soroti, and Lacor in Uganda). Malaria transmission in Kilifi and Muheza was predominantly seasonal and of moderate intensity during the period of
the trial, whilst transmission at all sites in Uganda was perennial and intense.

Study population

          Children were eligible for the FEAST trial if they were between 60 days and 12 years of age, had a history of fever and/or abnormal temperature (pyrexia [≥ 37.5 °C] or hypothermia [< 36 °C]), and were admitted to hospital with severe illness (respiratory distress and/or impaired consciousness) plus at least one of the following signs of impaired peripheral perfusion: capillary refill time > 2 s; lower limb temperature gradient (defined as a notable
temperature change from cold [dorsum of foot] to warm [knee] when running the back of the hand from the toe to the knee); weak radial pulse; or severe tachycardia (defined as heart rate > 180 beats per minute [bpm] for children < 1 year old, > 160 bpm for those 1 to 4 years
old, > 140 bpm for those ≥ 5 years old). 
           Children were excluded from the trial if they presented with severe acute malnutrition, gastroenteritis, burns, or surgical conditions. Children were randomised to receive immediate boluses of 20–40 mL/kg of 5% human albumin solution or 0.9% saline solution over 1 h (intervention group) following by maintenance fluids, or maintenance intravenous fluids only at 4 mL/kg/h (control group) until able to drink. The primary endpoint was mortality at 48 h after randomisation. 

Clinical care

Standardised case report forms were completed at enrolment and at specific time points during the first 48 h. At enrolment, lactate, haemoglobin, and glucose point-ofcare measurements were conducted, together with an HIV antibody test, malaria blood film, and a rapid diagnostic test for malaria. At 8 h and 24 h, lactate and haemoglobin measurements were repeated. Lactate was  measured using a Lactate Pro® (Arkray KDK, Kyoto, Japan) hand-held analyser, which was calibrated daily, and each time a new box of Lactate Pro® Test Strips was used. The test results, available in 60 s, displayed ‘LO’ if the lactate level was below 0.8 mmol/L and ‘HI’ if the lactate level was above 23.3 mmol/L. Out-of-range results were repeated for verification. Haemoglobin was determined with the HemoCue® Hb 301 system, Angelholm, Sweden. Children were managed on general paediatric wards, with no facilities for ventilation other than short-term ‘bag-and-mask’ support. Training in triage, identification, and definitions of adverse events related to fluid management (including transfusion) was given prior to and throughout the trial and was included in the trial manual of operations that was given to every team member. The main outcome of the FEAST trial [23] and the transfusion practices [24] used in the study have been reported in detail previously.

Statistical analysis

The current secondary analysis was performed using the parent study database, cleaned and exported into STATA version 11 (StataCorp, LP, College Station, TX, USA). All children in the FEAST dataset with a valid lactate measurement at time of admission were included in the analysis, with a subsequent analysis of those who also had a lactate measurement 8 h after admission.

 Hyperlactataemia classification and lactate clearance definition 

           In the current study, we considered HL as a lactate > 2.5 mmol/L. We sub-categorised patients according to the lactate level on hospital admission as having moderate HL (lactate 2.5 to < 5 mmol/L), severe HL (lactate ≥ 5 mmol/L), or no HL (lactate < 2.5 mmol/L). An LC value was calculated for all children with an increased lactate level on admission (≥ 2.5 mmol/L) who were alive and had a lactate measurement at 8 h. Relative LC (percent) was defined by the equation [(lactate initial − lactate at 8 h)/lactate initial] × 100, for which lactate initial was the measurement at randomisation. Lactate normalisation was defined as a lactate decline to < 2.5 mmol/L at 8 h. The 8-h LC goal was defined by a relative lactate decrease of at least 40% from baseline and/or lactate normalisation. 
      Baseline clinical characteristics by survival status were described, combining randomisation groups. Frequencies and percentages were used for categorical variables, and medians with their inter-quartile range (IQR) for nonnormally distributed continuous data. Baseline clinical characteristics were compared across outcome categories using the chi-squared test or the Wilcoxon signedrank test as appropriate. Descriptive analysis reported both missing and available data  The main exposure of interest was LC at 8 h. The
primary outcome was all-cause in-hospital mortality at 72 h of randomisation (d72). As a first step in the LC analysis, the association between baseline HL and d72 was examined. For each of the exposures, HL and LC, the crude odds ratio (OR) with 95% confidence interval (CI) was calculated for the association with d72. To identify potential confounders, associations between patient characteristics and exposure and outcome variables were determined. Classic Mantel-Haenszel methods were used to explore for confounding and effect modification. A multivariable logistic regression model was fitted with a stepwise forward process selection to estimate the OR adjusted for several covariates simultaneously using all available data. Candidate variables were selected using previously defined risk factors of mortality and confounders identified in the univariate analysis. Age, sex, and study site were included a priori in both models due to their association with a wide range of health parameters. The effect of the trial intervention was included as a potential confounder and tested as an effect modifier of the association between LC and d72 with increased mortality in the FEAST trial. Likelihood ratio tests were used to assess for the model fit. Receiver operating characteristic (ROC) curve analysis was used to determine the cut-off value for lactate level at hospital admission that would best predict death at 72 h. As children with malaria had a higher prevalence of severe HL despite a lower mortality rate, ROC curves were also built separately for children with and without malaria to assess if the best prognostic cut-offs differed (Fig. 1). A ROC curve was also fitted for d72 based on the regression model for LC at 8 h.



Results
Of 3170 children randomised in the FEAST trial, 3008 (95%) had a lactate measurement on hospital admission and were included in the current analysis. In this group, there were 309 deaths (10.3%) in the first 72 h after randomisation, which accounted for 90% of the overall mortality by 28 days. The clinical and laboratory baseline characteristics of the children by primary outcome are summarised in Table 1. The median age was 24 months (IQR 13 to 39), and 1387 (46%) were female. The majority of children presented with respiratory distress (2463, 82%) and/or impaired consciousness (2326, 78%). All had at least one sign of impaired perfusion, including severe tachycardia (2120, 71%), a prolonged capillary refilling time of 2 s or longer (2030, 67%), or a lower limb temperature gradient (1777, 59%). Weak radial pulse volume, present in 635 children (21%) and bradycardia (in 36 children) were strongly associated with a poor outcome (unadjusted OR 4.24; 95% CI 3.30, 5.45; p < 0.001 and 13.13; 95% CI 6.62, 26; p < 0.001 respectively). Severe anaemia (Hb < 5 g/dL) was present in 958 children (33%) at admission. Plasmodium falciparum malaria was confirmed in 1719 children (57%) and HIV infection in 106 (4%) of the 2417 children tested. A blood culture was positive in 123 (12%) of the 1052 children in whom the test was performed.

Baseline lactate level and mortality

            At hospital admission 2127 children (71%) had a raised baseline lactate (≥ 2.5 mmol/L). Of these, 948 children (32%) had moderate HL (lactate 2.5 to < 5 mmol/L) and 1179 (39%) had severe HL (lactate ≥ 5 mmol/L). Children with severe HL had a higher prevalence of other clinical and laboratory markers of disease severity, including hypoxaemia (SpO2 < 90% by pulse oximetry) (p < 0.001), coma (p < 0.001), severe anaemia (p < 0.001), or severe acidosis (p < 0.001). Children with malaria parasitaemia had higher mean baseline lactate (4.6 vs 3 mmol/L, p < 0.001) and prevalence of severe HL (46% vs 30%, p < 0.001) than those with other febrile illnesses. Of the 309 children who died in the first 72 h, 238 (77%) had severe HL on admission and 46 (15%) had moderate HL. The median admission lactate in children who died was significantly higher (10.9 mmol/L; IQR 5.2–13.6) than in those who survived the first 72 h (3.4 mmol/L; IQR 2.2–6.9) (p < 0.001). 
              Amongst those children who died, the median admission lactate was higher when death occurred in the first 8 h (12.2 mmol/L; IQR 8.6–13.9) than when it occurred between 8 and 72 h (7.65 mmol/L; IQR 4.1–12.6) or after 72 h (3.2 mmol/L; IQR 2.1–5.2) of the admission respectively. In the univariate analysis, baseline severe HL strongly increased the odds of death at 72 h (OR 8.66; 95% CI 5.7, 13.2), whilst moderate HL had a weaker effect on  mortality (OR 1.75; 95% CI 1.06, 2.87). This association did not significantly vary amongst children with and without malaria, indicating that severe HL was equally prognostic for both conditions. Evidence for an effect modification, however, was found between HL and hyperglycaemia (glucose ≥ 8.3 mmol/L) (heterogeneity test p < 0.01), elevated blood urea nitrogen (BUN) (heterogeneity test p < 0.001), and presence of crackles on auscultation (heterogeneity test p = 0.025) (Additional file 1: Supplementary tables). After full adjustment for confounders (Table 2), severe HL on hospital admission remained strongly associated with death at 72 h (OR 6.96; 95% CI 3.52, 13.76), whilst moderate HL showed a weaker association (OR 1.57; 95% CI 0.80, 3.08). Coma was a strong independent risk factor (OR 6.87; 95% CI 3.36, 14.04), and elevated BUN and HIV infection were moderately strong independent risk factors of death identified in the model. Whilst a positive malaria test appeared to be more strongly associated with higher likelihood of survival, this cannot be interpreted as a protective effect of parasitaemia per se, since the model was controlling for other factors which are likely impacted by malaria and strongly associated with mortality. 
              The multivariable regression model accounting for the interaction between HL and hyperglycaemia demonstrated a weakened association between HL and mortality in the presence of hyperglycaemia (OR 3.22; 95% CI 1.56, 6.67; p < 0.01), although the effect of HL on the risk of mortality in the absence of hyperglycaemia (OR 8.55; 95% CI 4.63, 15.78; p < 0.001) was slightly greater. Furthermore, logistic regression analysis accounting for the additional interactions identified demonstrated that the association of HL with d72 was considerably lower in the 427 children (21%) with high admitting BUN (OR 2.33; 95% CI 1.11, 4.89; p = 0.025) and much higher in the 655 children (22%) with crackles on auscultation (OR 29.45; 95% CI 10.13, 85.55; p < 0.001) (Additional file 1).

Lactate clearance at 8 h and mortality

Of all children included in the analysis, 2748/3008 (91.4%) were alive and had a blood lactate level measured at 8 h of randomisation; 1906 (63.3%) of these had an elevated lactate level (≥ 2.5 mmol/L) on admission and contributed to the LC analysis. Table 3 summarises the absolute and relative LC and lactate normalisation parameters at 8 h by primary outcome. Overall, the median lactate at 8 h was 3.4 mmol/L (IQR 2.3–5.1), the median absolute LC (change from baseline in lactate level) was 1.6 mmol/L (IQR 0.1–4.6), and the median relative LC (from baseline value) was 36% (IQR 3.3– 59%). Children who survived to 72 h had a lower median lactate (3.3 vs 5.4 mmol/L, p < 0.001) and a higher








relative LC (37% vs 17%, p < 0.01) at 8 h. Median relative LC was significantly higher in children with severe HL (54%; IQR 28–70) than in those with moderate HL (15%; IQR −19 to 38) (p < 0.001). Children with malaria had a similar relative LC as those with other severe febrile illnesses (37% vs 35%, p = 0.4). At 8 h, 566 children (30%) had a relative LC < 10%,
whereas a total of 1014 (53%) met the pre-defined LC criteria (LC decline ≥ 40% [878, 46%] and/or lactate normalisation [< 2.5 mmol/L] [554, 29%]). After full adjustment for confounders, including the effects of lactate level on admission and the FEAST trial (fluid) intervention arm, failure to clear lactate (LC < 10%) at 8 h of treatment was strongly associated with death at 72 h (OR 4.62; 95% CI 2.7, 8; p < 0.001). Furthermore, achieving the combined LC pre-defined goal was the strongest prognostic factor of survival (OR 0.24; 95% CI 0.14, 0.42; p < 0.001) compared to relative LC or lactate normalisation
alone (Table 4).
             Persistent severe HL at 8 h remained a strong independent risk factor of death at 72 h (OR 4.60; 95% CI 2.61–8.1; p < 0.001). Of note, as previously demonstrated in the FEAST trial, fluid boluses were strongly associated with death at 72 h (OR 2.48; 95% CI 1.36,4.51; p < 0.01) in the full-adjusted logistic regression model. ROC analysis and lactate cut-offs The area under the receiver operator curve (AUROC) for d72 based on lactate at admission was 0.77 (95% CI 0.74–0.80), with no statistically significant difference in AUROC amongst children with and without malaria (p = 0.47) (Fig. 1). The AUROC based on lactate at 8 h was 0.73 (95% CI 0.68–0.77), with again no difference by malaria status (p = 0.55). The overall AUROC based on LC at 8 h was 0.58 (95% CI 0.53–0.64), and for the
group of children with severe HL (> 5 mmol/L) on admission it was greater (0.68; 95% CI 0.62–0.75). 
            Lastly, the AUROC for d72 based on a logistic regression model for LC at 8 h was even more predictive as 0.84 (95% CI 0.80–0.88) (Fig. 2). Sensitivity and specificity analysis identified that for children without falciparum malaria a lactate level on admission of ≥ 3.4 mmol/L had a sensitivity to predict mortality at 72 h of 80% and a specificity of 61.6%,
whereas for children with malaria a sensitivity of 80% corresponded with a lactate cut-off value of 5.2 mmol/L (specificity of 59.2%). For a baseline lactate level of ≥ 5





mmol/L, the sensitivity in children without malaria was 71.7% (specificity 75.53%), whereas in those with malaria it was 82.43% (specificity 57.7%). This indicates that in non-malaria cases, lower levels of HL have a similar effect on 72-h mortality.

Discussion

                Our study confirms the association between HL on hospital admission and mortality, and it demonstrates that a failure to clear lactate (relative LC < 10%) within the first 8 h of treatment is a relevant prognostic factor of early death in severely ill febrile children in a malaria-endemic area irrespective of the underlying diagnosis (malaria, sepsis, or other severe febrile illness). Importantly, this is the first paediatric study to demonstrate that a relative LC ≥ 40% and/or lactate normalisation within the first 8   h of treatment strongly predicts 72-h survival in this context.
               These results, derived from a very large multicentre randomised trial, are compelling and raise the question of whether LC could be a simple, valid and cost-effective riskstratification tool, as well as a potential therapeutic target to guide resuscitation in children with severe febrile illnesses in resource-poor settings. Furthermore, it is not limited to children with specific diagnoses, but rather covers different presentation syndromes, which reflects the population of children presenting to hospital in the setting in which the trial was conducted. Lastly, for research studies the inclusion of lactate level could be used for inter-site or intercentre comparisons of disease severity. Despite a paucity of paediatric data, our findings are supported by the literature. A recent meta-analysis [25




and a large systematic review [17] of acutely ill adults have reported a consistent lower mortality associated with LC, not limited to septic patients and regardless of the initial lactate value. Also, a recent secondary analysis of two large clinical trials on antimalarials has shown that lack of LC is an independent predictor of death in adults with severe malaria [26]. Amongst the few paediatric studies published, Krishna and colleagues measured
serial lactate concentrations during 24 h in a small cohort of 115 children with severe malaria in the Gambia,
               concluding that sustained HL was the most powerful prognostic indicator of fatal outcome [21]. In another cohort of 65 children admitted to a paediatric intensive
care unit (PICU) with septic shock in South Korea, Kim et al. [22] found that the area under the curve (AUC) of serial lactates measured during the first 24 h had a strong predictive power of mortality at 28 days (ROC AUC 0.828). Munde et al. [27] recently reported that a
relative LC < 30% at 6 h predicted mortality in PICU children in India comparably to the more complex Paediatric Risk of Mortality (PRISM) score, standard in paediatric intensive care. It is therefore possible that failure to clear lactate within the first hours of therapy could serve as a simpler risk stratification tool in malaria-endemic areas,potentially more reliable than absolute lactate values alone and easier to apply than more complex clinical scores.                     However, to have an outcome benefit, a similar lack of LC effect should likely be shown at an interval shorter than 8 h that would allow a therapeutic intervention or the appropriate recruitment into clinical trials of those children with a higher chance to die.
Moreover, to demonstrate an association between LC and survival in severely ill febrile children in a malariaendemic area is relevant at least in two aspects. On one hand, LC could serve as a valid surrogate endpoint of clinical trials of malaria aiming to improve mortality, as
recently demonstrated by Jeeyapant et al. in a large cohort of adult patients with malaria [26]. Thus, one could hypothesise that LC might help to guide the initial resuscitation of these children in a resource-poor setting, where invasive monitoring and intensive care is mostly unavailable. To date two multicentre randomised trials have assessed the clinical value of resuscitation strategies that included LC as a target in adults admitted to intensive  care units, showing that quantitative resuscitation based on LC was non-inferior or even superior to that based on ScvO2 alone [18, 19], and the most recent Surviving Sepsis Campaign guidelines suggest targeting resuscitation to lactate normalisation in adult septic



patients with HL, although accept a weak evidence exists for this recommendation [28]. Unfortunately, the observational design of our study does not allow one to answer whether targeting resuscitation to achieve a specific relative LC or lactate normalisation
improves outcomes in severely ill febrile children in this context. Interestingly, a recent study including 218 adult patients with severe infection at a regional referral hospital in Uganda [29] questioned whether serial assessment of vital signs combined with point-of-care lactate at 6 h could be a feasible method of monitoring patients being resuscitated from severe sepsis or malaria in a resource-poor setting. Despite an improvement in vital signs and lactate values at 6 h of resuscitation, the authors could not demonstrate an association between an LC ≥ 10% and improved in-hospital mortality. This study, however, was observational with a limited sample size where more than half of the participants had





advanced HIV infection, it did not use a pre-defined treatment algorithm to target LC, and it did not report adjusted OR for the association of interest. Some other limitations of our study should be taken into account. First, despite the optimal LC threshold or the LC rate not having been clearly defined, many studies on LC in sepsis have used a relative clearance rate of 10–20% in repeated samples measured at 2- to 3-h intervals during the first 6 h of resuscitation. Our definition of LC criteria was based on published data [14, 18, 19],
the median LC value in our cohort, and the 8-h interval between lactate samples. A more extreme or loose definition could have yielded slightly different results. Moreover, the fact that LC in the FEAST trial was calculated at 8 h after randomisation for all participants prevents one from determining the precise moment when lactate normalisation or LC occurred for each individual. If some of the participants cleared their lactate significantly
earlier than 8 h and that was associated with a better outcome, the true effect of lactate normalisation/LC on survival could be underestimated. However, 169/341 children (49.6%) died before 8 h, which again could have resulted in a relevant underestimation of the study results. 
               The key point is that we chose the 8-h correction as this could be compared to other studies [26–28]; given the high proportion of mortality that occurred before this time point, an early assessment of LC may be more relevant to this setting to identify high-risk patient and initial resuscitation (either at 2 or 4 h). Lastly, LC can be potentially useful when baseline HL exists, which was not the case for one third of our participants. Whilst lactate levels can falsely increase with haemolysis, frequent with difficult phlebotomies or with long
time span from extraction to processing, blood samples in the FEAST trial were obtained from a free-flowing vein and immediately measured at the bedside. Arterial lactates are recommended over peripheral venous lactates in sepsis studies looking at absolute values and clearance rate, due to poor agreement between both parameters [30]. Nevertheless, there are technical and ethical challenges in obtaining arterial samples in unsedated children, and the strong prognostic correlation with high admission venous lactate and LC with survival outcomes suggests that pragmatically venous samples should be suitable for critically sick children in resourcelimited hospitals. Lastly, lactate levels may increase with hyperglycaemia, unrelated to a tissue oxygen debt but related to a stress-induced increased glucose turnover.
              This so-called type B lactic acidosis usually resolves quickly after normalisation of glycaemia [31]. Only 6% of participants in the analysis had hyperglycaemia on admission, so it is unlikely this would have introduced a bias in the overall analysis. However, some evidence of an effect modification was found between HL and  hyperglycaemia (see Additional file 1), with a weakened association between HL and death in the presence of hyperglycaemia. Relevant to the FEAST Paediatric Emergency Triage (PET) clinical score [5], which includes the presence of crackles (lung crepitations) on auscultation as a predictive maker of death, we too found that lung crepitations in association with high lactate strongly predicts 72-h mortality (OR 29.90; 95% CI 11.43–78.14) in children with shock, which most likely indicates the aetiology was sepsis due to pneumonia. This observation may help refine definitions of severe pneumonia, which are broad and non-specific. Interestingly, in the PET score analysis hypoxaemia (pulse oximetry reading < 90%) did not independently predict poor outcome [5]. In this analysis, hypoxaemia was found to be independently associated with death at 72 h (OR 1.72, p = 0.01); however, as it did not confound or modify the association between HL and d72, it was not included in the logistic regression model.
                Moreover, children septic with pneumonia (defined as crackles on auscultation and presence of hyperlactataemia) were more likely to suffer from hypoxaemia (OR = 2.58; p < 0.0001). Owing to the poor specificity of signs for pneumonia, WHO promotes the use of pulse oximeters to direct children with signs of pneumonia for oxygen therapy. Yet, pulse oximetry remains poorly implemented [32]. One example, therefore, of the utility of the PET score and/or use of lactate screening at admission is using lung crepitations in the future to screen for clinical trials examining novel therapies specifically for pneumonia in those at high risk for poor outcome. Lastly, our findings suggest that the predictive values of lactate on admission for mortality are lower in children without malaria (3.4 mmol/L) than for those with malaria (5.2 mmol/L). 
                This is important, as a detailed pathogenesis of HL in septic shock and and in malaria is still imperfectly understood and may actually differ. Whereas in sepsis HL is mostly viewed as a result of anaerobic metabolism secondary to systemic hypoperfusion [33], HL in malaria is likely an even more complex phenomenon, involving additional factors like sequestration of parasitised erythrocytes in the microcirculation, acute severe haemolytic anaemia, seizure activity, and end-products of parasite metabolism [34–36]. We have previously described the relationship between baselines haemoglobin and lactate (Additional file 2). 
                  This likely diverse pathogenesis of HL in bacterial sepsis and malaria could have implied a different prognostic value for mortality that would explain the different definitions of HL used in studies of sepsis and malaria. Thus, while the current consensus cut-off value for sepsis is a lactate > 2 mmol/L [37], most studies on severe malaria, where HL is particularly frequent and profound, use a lactate cut-off of > 5 mmol/L, following the WHO definitioncriteria [38]. Our study indicates that appropriate lactate cut-off values, lower for children without malaria, should be included in the design of therapeutic algorithms for
early risk stratification of severely ill children admitted to hospital in malaria-endemic areas.

Conclusions

          In conclusion, severe HL, defined as a venous lactate level ≥ 5 mmol/L on hospital admission, is a strong risk factor for death within the first 72 h in children with severe febrile
illnesses in east Africa, independently of the underlying diagnosis. Failure to clear lactate (relative LC ≤ 10%) within 8 h is also strongly prognostic of death, which could serve as a simple risk-stratification tool or a surrogate endpoint of mortality in clinical trials. Those children able to normalise or clear their lactate by at least 40% within 8 h have an improved chance of survival. An LC measured at an earlier time point may have yielded even more relevant results owing to the high mortality prior to 8 h that occurred in our cohort. Whether LC alone, or in combination with other clinical markers, can be used as a cost-effective therapeutic target to guide initial resuscitation and ultimately improve clinical outcomes of severely ill febrile children in malaria-endemic areas, where lack of basic patient monitoring and intensive therapies is standard, remains uncertain. Given severe infection is the most
common cause of death in children under 5 years of age in these settings, and that early and aggressive initial resuscitation is key for survival, this question warrants further investigation. 
          These data provide the rationale for a clinical trial of lactate clearance as an early therapeutic resuscitation goal in children with severe infection in malaria-endemic areas. We encourage the use of point-ofcare lactate testing whenever possible in limited-resource
settings to identify high-risk patients.


References

1. CHERG-WHO methods and data sources for child causes of death 2000–
2013. Global Health Observatory data. http://www.who.int/gho/child_
health/mortality/causes/en. Accessed 1 Oct 2017.
2. Molyneux E. Paediatric emergency care in developing countries. Lancet.
2001;357:86–7.
3. Molyneux E, Ahmad S, Robertson A. Improved triage and emergency care
for children reduces inpatient mortality in a resource-constrained setting.
Bull World Health Organ. 2006;84:314–9.
4. World Health Organization. Pocket book of hospital care for children. 2nd
edition. Guidelines for the management of common childhood illnesses.
Geneva: World Health Oganization; 2013.


Which patients with advanced respiratory disease die in hospital?


Which patients with advanced respiratory disease die in hospital?

Irene J. Higginson1*, Charles C. Reilly1, Sabrina Bajwah1, Matthew Maddocks1, Massimo Costantini2, Wei Gao1,
on behalf of the GUIDE_Care project




                                                        Abstract
Background: 
Strategies in many countries have sought to improve palliative care and reduce hospital deaths for non-cancer patients, but their effects are not evaluated. We aimed to determine the trends and factors associated with dying in hospital in two common progressive respiratory diseases, and the impact of a national end of life care (EoLC) strategy to reduce deaths in hospital.

Methods: 
This population-based observational study linked death registration data for people in England dying from chronic obstructive pulmonary disease (COPD) or interstitial pulmonary diseases (IPD). We plotted age- and sex-standardised trends, assessed during the pre-strategy (2001–2004), first strategy phase (2004–2008), and strategy intensification (2009–2014) periods, and identified factors associated with hospital death using multiple adjusted
proportion ratios (PRs).

Results: 
Over 14 years, 380,232 people died from COPD (334,520) or IPD (45,712). Deaths from COPD and IPD increased by 0.9% and 9.2% annually, respectively. Death in hospital was most common (67% COPD, 70% IPD). Dying in hospice was rare (0.9% COPD, 2.9% IPD). After a plateau in 2004–2005, hospital deaths fell (PRs 0.92–0.94). Co-morbidities and deprivation independently increased the chances of dying in hospital, with larger effects in IPD (PRs 1.01–1.55) than COPD (PRs 1.01–1.39) and dose-response gradients. The impact of multimorbidity increased over time; hospital deaths did not fall for people with two or more co-morbidities in COPD, nor one or more in IPD. Living in rural areas (PRs 0.94 0.94) or outside London (PRs, 0.89–0.98) reduced the chances of hospital death. In IPD, increased age reduced the likelihood of hospital death (PR 0.81, ≥ 85 versus ≤ 54 years); divergently, in COPD, being aged 65–74 years was associated with increased hospital deaths (PR 1.13, versus ≤ 54 years). The independent effects of sex and marital status differed for COPD versus IPD (PRs 0.89–1.04); in COPD, hospital death was associated with being married.

Conclusions
The EoLC strategy appeared to have contributed to tangible reductions in hospital deaths, but did not reach people with multimorbidity and this gap widened over time. Integrating palliative care earlier in the disease trajectory especially in deprived areas and cities, and where multimorbidity is present, should be boosted, taking into account the different demographic factors in COPD and IPD.

Keywords: 
Hospital, Palliative care, End of life care, Chronic obstructive pulmonary disease, Interstitial pulmonary diseases, Interstitial lung disease, Respiratory, Policy, Place of death.

                                          
                                        Background


Chronic diseases and multimorbidity are common and increasing. Respiratory diseases are major contributors, especially chronic obstructive pulmonary disease (COPD) and interstitial pulmonary disease (IPD). More than 3 million people worldwide died of COPD in 2012,
representing 6% of all deaths that year [1]. Mortality from IPDs is climbing, with current age-standardized mortality ranging from 4 to 10 per 100,000 population (highest in UK and lowest in Sweden) [2]. Both conditions result in a high use of hospital services across all
medical areas, especially among people in advanced stages, when the systemic effects of disease lead to dependency [3]; this leads to high healthcare costs. UK population-based data on admissions suggests that, in IPD, the estimated financial burden of hospitalisation in
2010 was £16.2 million per year [4]. Despite this expenditure, there are concerns that care in advanced disease is suboptimal, inadequately co-ordinated, and with patients suffering an average of 14 symptoms, plus psychological and information concerns [5–8]. For most patients with a progressive illness, the hospital is among the least preferred places of death [9]. In the UK, the National Institute of Clinical Excellence (NICE) published Guidance on Supportive and Palliative
              Care in 2004 [10], and an extra £50 million was allocated to palliative care services. Building from this Guidance, the End of Life Care (EoLC) Programme was developed to improve care in the last year of life, with a specific goal to reach patients in general medical care and with diseases beyond cancer [11]. Roll out was intensified after 2008 within the EoLC Strategy [12]. The Programme and Strategy prioritised home care as an alternative to hospital, promoting initiatives to elicit preferred place of death and boost support from general practitioners. However, whether policies altered care for those dying from major diseases, apart from cancer [11, 13], is unknown. Where people die is a common quality marker. Whilst place of death has been widely studied internationally in cancer [13–15], only one Spanish study has assessed factors associated with place of death from COPD [16], and none for IPD, despite the greater prevalence of respiratory conditions and the imminent global epidemic [3].
               Understanding which factors affect place of death is vital for service planning and
care improvement, especially given population ageing, rising chronic diseases worldwide and the high costs of hospital admissions [17]. Information to reduce hospitalisations is needed internationally both to meet patient preferences and to ease healthcare costs [18–21]. Therefore, we aimed to compare the trends and factors associated with place of death in people with two common progressive respiratory diseases. We sought to determine whether hospital deaths for individuals dying  from COPD or IPD fell after the Strategy was introduced, and after roll out was intensified. To aid future interventions, we also evaluated which factors affected place of death, and whether these were similar across COPD and IPD.

Methods
Study design

Population-based observational study (as per STROBE and RECORD [22] guidelines, Additional file 1) as part of our study of Geographical and Temporal Variations in Place of Death in England (GUIDE_Care) [23].

Data sources

The Office for National Statistics death registrations in England, which detail decedents’ age, sex, marital status, usual residence, place and year of death, and, based on the clinician’s death certificate, the underlying and contributing causes of death using the International Classification of Diseases Tenth Revision (ICD-10), employed since 2001. Office for National Statistics death registration records were linked with area level indices of multiple deprivation (IMD) 2010 [24]. The IMD 2010 is a composite measure of deprivation, providing a weighted average of seven domains: income, employment, health
and disability, education, skills and training, living environment and crime, and barriers to housing and services. These are based on the Lower Super Output Area (LSOA) of the decedents’ usual residence. There are 32,482 LSOAs in England, with each area having a minimum of 1000 residents and an average of 1500. LSOAs were grouped into quintiles based on their IMD scores [13, 24, 25].

Study population

All deaths between 2001 and 2014 (inclusive) with COPD or IPD as an underlying cause of death (ICD-10 codes: J40-J44, J47 (COPD); J84 (Interstitial pulmonary disease, encompassing all progressive fibrotic interstitial lung diseases including idiopathic pulmonary fibrosis and idiopathic interstitial pneumonia)) were extracted.

Variables

The main outcome was place of death grouped into six categories: hospital, home, hospice (an inpatient specialist palliative care unit, freestanding or clearly specified within a hospital, 75% are voluntary, 25% NHS managed), nursing home, care home or residential home,
and elsewhere [13]. Explanatory variables were age at death (≤54, 55–64, 65–74, 75–84, 85+), sex (men, women), year of death (grouped into 2001–2004 (pre-Strategy), 2005–2008
(Strategy first phase, which included the implementation  of the NICE Guidance and first phase of the EoLC Programme and Strategy), and 2009–2014 (Strategy intensification)),
marital status (married, widowed, divorced, single, not stated/unknown), number of co-morbidities assessed from contributory cause(s) of death (0, 1, 2, 3, 4 +), type of settlement (rural, urban), socioeconomic status (as measured by IMD of area of residence), and region
(defined by Clinical Senate, 2013). We analysed age as an ordered five-category rather than a continuous variable to aid interpretation and comparison with other studies; category boundaries were chosen based on the data distribution [26–28].

Statistical analysis

We plotted the time trend of age- and sex-standardised proportion of deaths in hospital for COPD and IPD. Proportions were standardised using the 2010–2015 mortality structure for more developed countries from the United Nations standard population [29]. We used Modified Poisson Regression to evaluate the relationship between place of death and potential explanatory variables (selected from those available, according to existing literature and univariable analysis results), including age, sex, marital status, co-morbidity, year of death, IMD, rural/urban indicator and region of the usual residential address (Table 2). The dependentmvariable was binary (1 = hospital, 0 = non-hospital). We
focused on hospital death as this was most common and reducing it was a target of the Strategy. The strength of association was measured using proportion ratios (PRs). Two separate models were constructed for COPD and IPD. The Modified Poisson regression was chosen over the binomial model as the latter failed to converge in IPD [30]. Sensitivity analysis entered year of death as a continuous rather than categorical variable. All analyses were performed using the SAS 9.4 (SAS Institute, Cary, NC, USA).

Results

          Over the 14 years, 334,520 people died from COPD and 45,712 from IPD (Table 1), representing 5.3% and 0.7% of the total 6,368,760 non-accidental deaths during the period. Annual deaths from COPD increased slightly from 23,303 (2001–2004) to 24,717 (2009–2014), representing a yearly increase of 0.9%. The annual number of IPD deaths, although much smaller, almost doubled from 2403 (2001–2004) to 4091 (2009–2014); representing a yearly increase of 9.2%. Across both conditions, more than 65% of deaths occurred among people aged over 75 years. Hospital was the most common place of death (67.3% for COPD, 70.1% IPD), followed by home (19.9% COPD, 19.1% IPD). Deaths within hospices accounted for just 0.9% of COPD and 2.9% of IPD cases (Table 1).
            The pattern of higher proportions of hospital deaths in IPD was consistent over the years, even when standardised by age and sex. For both groups, the proportion of hospital deaths peaked between 2003 and 2005 (Fig. 1). The proportion of age- and sex-standardised deaths in hospital fell slightly between 2005 and 2014 for people with COPD (from 67% to 61%) and IPD (from 71 to 68%). In multivariable analysis (Table 2), hospital deaths reduced significantly over time in both COPD and IPD, with a fall occurring after 2005. Female sex was independently associated with higher hospital deaths in COPD (PR 1.04) but lower in IPD (PR 0.97). In COPD, there was a U-shaped relationship regarding age, with those aged 65–74 years having the highest hospital deaths (PR 1.12); whereas in IPD, increased age was independently associated with fewer hospital deaths (PR 0.81). Being married increased the chance of dying in hospital for COPD but not for IPD (Table 2).
Having co-morbidities and living in deprived areas independently increased the chance of dying in hospital, with larger effects for IPD (PRs 1.01–1.55) than COPD (PRs 1.01–1.39) and a “dose–response” relationship (Fig. 2). Living in rural areas as opposed to cities reduced the chances of hospital death (PRs 0.94–0.95). When plotted over the period (Fig. 2), after 2005 hospital deaths fell chiefly for people with no co-morbidities. Hospital deaths
did not fall for people with two or more co-morbidities in COPD, or with any co-morbidity in IPD. For deprivation and urban areas, the dose–response relationship appeared to stay constant over time (Fig. 2). Significant variations by region were observed for both COPD and IPD. For COPD and IPD groups, “London” had the highest hospital deaths, and the “South West” and “South East Coast” regions had lower hospital deaths than most other regions. Sensitivity analysis, with year of death as a continuous variable, produced similar
results (Table 3).

Discussion

In this large population-based study assessing place of death in respiratory disease over 14 years, we found hospital was the most common place of death, and remained constantly higher for people with IPD (67.5–74.7%, standardised by age and sex) than COPD (61.3–67.4%). During the period following the introduction of the NICE Guidance on Supportive and Palliative Care, and the introduction and intensification of the EoLC Strategy, hospital deaths fell slightly, by 6% for people with COPD and 3% for IPD. In regression analysis, the change after 2005 was significant for both COPD and IPD. Our design is observational; therefore, as in other population studies, we cannot infer causality. However,






our findings meet many of the Bradford-Hill and related criteria [31] for providing evidence supporting a causal relationship. There is strength, consistency, specificity and coherence in our findings. We observed a similar but more pronounced and immediate effect in adults who died from cancer – the traditionally best served condition by palliative and end of life care [13]. Conversely, in children and young people with cancer, a patient population rarely accessing palliative and end of life care services, the Strategy made little impact on where people die [32]. There is strong evidence of temporality, with the changes emerging after the Strategy was introduced and increased after it was intensified. For both conditions, multimorbidity, social deprivation and living in urban areas were associated with dying in hospital, with larger effects for IPD than COPD. We found a “dose–response” effect, with higher deprivation and multimorbidity producing the largest effects on dying in hospital. Increased age and being female were associated with higher hospital deaths in COPD but lower in IPD. In both groups, being single, widowed or divorced, and living in rural or outside London areas were  associated with reduced chances of dying in hospital.
                     These data are ecological, and may be subject to the ecological fallacy, whereby the risk-associations apparent for social deprivation, multimorbidity, or other factors may not accurately reflect the true association between individuals within those groups. However, our findings meet the Bradford-Hill criteria of a dose–response relationship. These associations could be examined further in prospective research. Our findings suggest the EoLC Strategy contributed to tangible impact in reducing hospital deaths for people with respiratory diseases. However, the effects were mainly for people with few or no co-morbidities; people with two or more co-morbidities had no reduction in hospital deaths over the period. Most healthcare systems are dominantly established for people with individual
diseases [33, 34]. Many different specialists can become involved during multimorbidity. This can be duplicative, burdensome and unsafe for patients because of poor coordination
and integration, with some patients inversely receiving less care [33, 35, 36]. Another reason might be that the more medical specialists are involved, the higher











during the last year of life, is problematic when patients have multimorbidity. Patients with COPD and IPD often suffer refractory breathlessness, which can result in panic and distress [42]. Breathlessness is often unpredictable and episodic [5, 43], with multiple other symptoms that can result in accident and emergency attendance [44]. Managing refractory breathlessness and issues in multimorbidity is therefore more complex and time consuming than for single conditions, especially responding to the needs for ‘joined-up’ co-ordination, communication and symptom management [35, 36]. Organising some specific treatments, such as non-invasive ventilation in COPD, also may take time in the community. Taken together, these findings suggest that earlier palliative care is needed, with an integrated short-term assessment and review. Two challenges exist regarding access to end of life or palliative care for a patient with organ failure.
              Firstly, when and how to trigger care? As prognostication is difficult, professionals can have ‘prognostic paralysis’, and may postpone discussions with patients about the future. Secondly, patients may not realise or acknowledge that they have a life-limiting disease. This is often not clearly communicated by the healthcare professionals, which implies that preferred place of death is not discussed [45]. Early palliative care could be triggered by multimorbidity and complexity in terms of symptoms and needs rather than waiting until the end of life is apparent or acknowledged. Evidence supports such services; strong evidence supports early integration in cancer [46, 47] and evidence is emerging in respiratory and mixed conditions for integrated breathlessness support services [48, 49], hospital to home [50] and multiprofessional teams [51]. Perhaps multimorbidity should be a specific focus for palliative  care. 
             A recent study found the cost-savings of palliative care were largest among patients with multimorbidity, costs were 22% lower than standard care for patients with a co-morbidity score of 2–3 and with 32% lower for those with a score of 4 or higher [52]. There may be a role for tools to understand and elicit discussions earlier in care, including in Intensive Care Units [53, 54], and for palliative care units in the acute hospital where noninvasive ventilation can be provided. Exactly how integration should occur needs to be tailored to the characteristics of the healthcare system and the local resources but evidence suggests that identification based on clinical characteristics is more reliable than relying on clinicians to remember to make referrals [46]. 
          The factors identified in this study, along with the symptom of breathlessness, could be applied to trigger more integrated palliative support, with models such as a breathlessness support service [49]. Hospices, which in the UK provide inpatient specialist palliative care, remained a rare place of death, yet these may be appropriate places  outside of hospitals to care for more complex patients with multimorbidity. Our findings support other research that found deprivation is associated with higher hospital and fewer home deaths in cancer and COPD [15, 55, 56], and studies in COPD suggesting that deprivation and co-morbidity are associated with hospital admission and readmission for acute exacerbation [17, 57, 58]. We could find no literature on deprivation in IPD; ours appears to be the first study to consider this group. It would seem plausible that more hospital admissions may lead to greater chances of dying in hospital. McAllister et al.’s [55] study in Scotland found that winter and socioeconomic deprivation-related factors appear to act synergistically, increasing the rate of COPD admissions to hospital more among deprived people and in winter. 
          The results suggest there may be a role for targeting initiatives in deprived areas and in winter. Interestingly, we found both diseases were still increasing in frequency as a cause of death over the period and for COPD this appears to run contrary to other European trends [59]. Factors such as being widowed or divorced making hospital deaths less likely in COPD are surprising; this is independent of age and may suggest the presence of family members increased the chance of patients being admitted to hospitals. Qualitative work has identified gaps in information and support for patients, families and professionals, who are often invisible to services [60]. The findings highlight more work is needed to support patients and family members at home, who often struggle in knowing what to do when breathlessness escalates [61]. For COPD, our findings of age and sex run contrary to those of a study of 4983 decedents in Andalusia, Spain [16], where older age and female sex were associated with home death. 
     However, the Andalusia study controlled for a smaller number of potential confounders, e.g. deprivation and co-morbidities were not assessed, whereas both were important in our study. It also considered only one year, 2009, and focussed on factors associated with deaths at home versus elsewhere rather than with hospital versus elsewhere. In accordance with our results, the Andalusia study found rural residents were more likely to die at home. Our study was limited by the nature of data available. We do not have information to address the appropriateness of the place of end of life care and the quality of the care provided. COPD and IPD can be characterised by a trajectory of a prolonged phase of recurrent exacerbations with recovery. Patients and their families are often acutely distressed during an exacerbation. 
          Standard medical treatments are often appropriate in correcting reversible processes, and also in providing symptom relief in these circumstances. Thus, palliative and end of  life care strategies may well need to be different for these patients than for cancer patients. Approximately 70% of the patients died in hospital, with patients admitted to hospital rather than remaining at home. Primary care and hospital teams may have thought that admission was the best option [61]. Many services have now moved on from the limitations of applying the generic EoLC strategy to COPD and IPD patients, to a model of care whereby standard medical and palliative care are delivered in parallel, in an integrated way, particularly in diseases where the patient has a good prospect of recovery from an acute exacerbation. 
         Other research indicates that people with COPD and IPD often miss out on the best care in advanced stages of illness, in the community, in hospital, and from palliative care [8, 62, 63]. Our finding of high hospital use may be a result of lower quality care and forward planning, driving emergency admissions [61, 63, 64]. There is little research on the preferences for place of care and death of people with respiratory disease, but there is no data to indicate that their preferences are especially different from other groups [14]. It is possible that COPD and IPD were misclassified as a cause of death, but as we focussed on recent years, this effect is likely to be minimised. 
           The increase in mortality from IPD has been partly linked to better identification of the disease [2, 4]. The apparent growth in IPD in our study may also be as a result of this trend. It is also possible that classification of IPD and COPD as a cause of death is influenced by setting, and other conditions, such as pneumonia, are more commonly recorded in community settings, thus underestimating COPD and IPD deaths in these settings. However, these limitations would be unlikely to affect the trends over time or the associated factors. The only concern would be if the Strategy helped to identify people with COPD and IPD earlier, which lead to increased community identification and recording as a cause of death. If this occurred, the effect of the Strategy found here would be over-estimated. 
         Multimorbidity is usually defined as the presence of two or more chronic diseases within an individual. We used the reported contributing causes of death to determine the number of co-morbidities. It may have been that only more major co-morbidities were recorded and therefore the number of co-morbidities may be underestimated. However, the presence of the clear trend shows the need to focus more clearly in the future on multimorbidity and its potential role. Our factors and trends point the way to potential interventions to improve care.

Conclusions

                Hospital deaths from COPD and IPD fell by 3–6% in the 8 years following the introduction of the EoLC strategy; however, those with multimorbidity did not show a fall  in hospital deaths. Multimorbidity, deprivation, living in cities, and living in London play a greater role in affecting where people with IPD die than those with COPD. Age and sex affect the chance of hospital death differently for COPD and IPD. Being married rather than single, widowed or divorced made hospital death more likely in COPD, but not in IPD. 
            Thus, the results suggest that the EoLC Strategy may have helped to shift some deaths out of hospital for people with respiratory disease but more integrated approaches of earlier palliative care are needed, targeting those at highest risk, especially with multimorbidity, and in deprived areas and cities. Further initiatives and trials are needed to understand and to improve the quality of care for people both in hospital (where most people are dying) and at home.


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FALSE COGNATES OR FALSE FRIENDS

False cognates  are words that have the same root, sound alike, but have different meanings. In addi...